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BNT162b2 (COVID -19 vaccine)
C4591012 NON- INTERVENTIONAL STUDY PROTOCOL
Version 2.0, 31 Aug 2021
PFIZER CONFIDENTIAL
Page 1of 194NON-INTERVENTIONAL ( NI) STUDY CONCEPT PR OTOCOL
Title Post-Emergency  Use Authorization Active 
Safety Surveillance Study  among Individuals 
in the Veteran’s Affairs Health Sy stem 
Receiving Pfizer -BioNTech Coronavirus 
Disease 2019 (COVID -19) Vaccine
Protocol number C4591012
Protocol version identifier Version 2.0
Date of last version of protocol 27January2021
EUPost Authori zation Study (PAS) 
register numberEUPAS39779
Activesubstance COVID-19 mRNA Vaccine is single -stranded, 
5’-capped messenger RNA (mRNA) produced 
using a cell -free in vitro transcription from the 
corresponding DNA templates, encoding the 
viral spike (S) protein of SARS -CoV-2.
Medicinal product Pfizer-BioNTech COVID- 19 Vaccine
Research question and objectives Research question: what are the incidence rates 
of safety events of interest (based on adverse
events of special interest[AESI]) among 
individuals vaccinated with the Pfizer-
BioNTech COVID-19 vaccine within the US 
Veterans Health Administration (VHA) s ystem
overall and in sub- cohorts of interest, as 
compared to expected rates of those events?
Primary study objectives:
To assess whether individuals in the 
VHA system experience increased risk 
of safety events of interest following 
receipt of the Pfizer- BioNTech 
COVID-19 vaccine;
To assess whether sub- cohorts of 
interest (i.e., immunocompromised, 
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Page 2of 194elderly, individuals with specific 
comorbidities, individuals receiving 
only one dose of the Pfizer -BioNTech 
COVID-19 vaccine, and individuals 
with prior SARS -CoV-2 infection) in 
the VHA s ystem experience increased 
risk of safet y events of interest 
following receipt of the Pfizer-
BioNTech COVID -19 vaccine.
Secondary study objective :
To characterize utili zation patterns of 
the Pfizer -BioNTech COVID-19 
vaccine among individuals within the 
VHA, including estimating the 
proportion of individuals receiving 
vaccine, 2 -dose vaccine completion 
rate, and distribution of time gaps 
between the first and second dose,
demographics and health histories of 
recipients, overall and among the sub-
cohorts of interest. 
Authors Yinong Young- Xu, ScD, MA, MS
Director, Clinical Epidemiology  Program
Veterans Affairs Medical Center
White River Junction, VT 
Cynthia de Luise, PhD, MPH
Senior Epidemiologist/ Safety Surveillance 
Research Scientist ; Risk Management and 
Safety Surveillance Research
Pfizer, Inc.
New York, NY
Mei Sheng Duh, ScD, MPH 
Managing Principal and Chief Epidemiologist 
Analysis Group, Inc.
Boston, MA
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Page 3of 1941.TABLE OF CONTENTS
1.TABLE OF CONTENTS.......................................................................................................3
2. LIST OF ABBREVIAT IONS................................ ................................ ................................ 5
3. RESPONSIBLE PARTI ES................................ ................................ ................................ ....8
4.ABSTRACT ................................ ................................ ................................ ........................... 9
5.AMENDMENTS AND UP DATES................................ ................................ ..................... 23
6.MILESTONES ................................ ................................ ................................ ..................... 29
7. RATIONALE AND BAC KGROUND ................................ ................................ ................ 30
8. RESEARCH QUESTION AND OBJECTI VES................................ ................................ .31
9. RESEARCH METHODS................................ ................................ ................................ ....32
9.1. Study  Design................................ ................................ ................................ ...........32
9.1.1. Self -Controlled Risk I nterval (SCRI) Design with Post -Vaccination 
Control Interval................................ ................................ ................................ 32
9.1.2. Active Comparator Design ................................ ................................ .........35
9.1.3. Additional Study  Designs in the Signal Evaluation Phase ......................... 36
9.1.4. Study  Period................................ ................................ ................................ 36
9.2. Setting ................................ ................................ ................................ ...................... 36
9.2.1. Inclusion Criteria ................................ ................................ ........................ 36
9.2.2. Exclusion criteria ................................ ................................ ........................ 36
9.2.3. Subgroups ................................ ................................ ................................ ...36
9.3. Variables ................................ ................................ ................................ .................. 38
9.3.1. Exposure of I nterest................................ ................................ .................... 38
9.3.1.1. Pfizer -BioNTech COVID- 19 Vaccine Groups of Interest ........38
9.3.2. Baseline Characteristics ................................ ................................ ..............39
9.3.3. Outcomes ................................ ................................ ................................ ....40
9.4. Data Source................................ ................................ ................................ .............47
9.5. Study  Size................................ ................................ ................................ ................ 48
9.5.1. Power ................................ ................................ ................................ ..........48
9.6. Data Management ................................ ................................ ................................ ...51
9.6.1. Case report forms (CRFs)/Electronic data record ................................ ......51
9.6.2. Recor d retention ................................ ................................ .......................... 51
9.7. Data Anal ysis................................ ................................ ................................ ..........52
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Page 4of 1949.7.1. Baseline Characteristics ................................ ................................ ..............52
9.7.2. Vaccine Utilization Patterns ................................ ................................ .......53
9.7.3. Safet y Signal Analyses ................................ ................................ ...............53
9.7.3.1. Signal Detection ................................ ................................ ........54
9.7.3.2. Signal Evaluation ................................ ................................ ......58
9.7.3.3. Signal Verification ................................ ................................ ....61
9.7.4. Seasonality -Adjusted Cases -Centered Method ................................ ...........62
9.7.5. End-of- Season and End -of-Surveillance Analy ses................................ .....62
9.7.6. Subgroup Analy sis................................ ................................ ...................... 63
9.7.7. Incidence Rates and Time to Safety  Event of Interest Anal ysis................. 64
9.7.8. Prioritized Safety  Analysis of Myocarditis/Pericarditis ............................. 64
9.8. Quality  Control................................ ................................ ................................ ........65
9.9. Strengths and Limitations of the Research Methods ................................ ...............66
9.10. Other Aspects ................................ ................................ ................................ ........67
10. PROTECTI ON OF HU MAN SUBJECTS ................................ ................................ ........68
10.1. Patient I nformation ................................ ................................ ................................ 68
10.2. Patient Consent ................................ ................................ ................................ ......68
10.3. Institutional Review board (I RB)/Independent Ethics Committee (I EC).............68
10.4. Ethical Conduct of the Study ................................ ................................ ................ 68
11. MANAGEMENT AND R EPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS................................ ................................ ................................ ...................... 69
12. PLANS FOR DI SSEMINATING AND COMMUNI CATING STUDY RESUL TS........70
13. REFERENCES ................................ ................................ ................................ .................. 71
14. LIST OF TABLES ................................ ................................ ................................ .............76
15. LIST OF FIGURES ................................ ................................ ................................ ...........76
16. ANNEX 1. LIST OF STAND ALONE DOCUMEN TS................................ ................... 76
17. ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOL S................................ ...76
18. ANNEX 3. ADDITIO NAL INFORMATION ................................ ................................ ...77
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Page 5of 1942. LIST OF ABBREVIATIONS
Abbreviation Definition
ACIP Advisory Committee on Immunization Practices
ACOS Associate Chief of Staff
AE Adverse event
AEM Adverse event monitoring
AESI Adverse event of special interest
AIDS Acquired immunodeficiency  syndrome
AMI Acute myocardial infarction 
BMI Body mass index
CAD Coronary  artery disease
CBER Center for Biologics Evaluation and Research
CI Confidence Interval
CCI Charlson comorbidity  index
CDC Centers for Disease Control and Prevention
CDW Corporate Data Warehouse
CEP Clinical Epidemiology  Program
CMA Conditional Marketing Authorization
CMS Centers for Medicare & Medicaid Services
COPD Chronic obstructive pulmonary  disease
COVID-19 Coronavirus Disease 2019
CPT Current Procedural Terminology
CRADA Cooperative Research and Data Agreement
CRFs Case report forms
DIC Disseminated intravascular coagulation
DVT Deep vein thrombosis
Tdap Diphtheria, tetanusand (acellular) pertussis
Td Diphtheria and tetanus
ED Emergency department
EMA European Medicines Agency
EMR Electronic medical records
EU European Union
EUA Emergency  Use Authorization
EU PAS European Union Post -Authorization Safety
FDA Food and Drug Administration
GBS Guillain-Barré syndrome
GEP Good Epidemiological Practice
GPP Good Pharmacoepidemiology  Practices
H0 Null hypothesis
Ha Alternative h ypothesis
HBV Hepatitis B virus 
HCPCS Healthcare Common Procedure Coding S ystem
HCV Hepatitis C virus
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Page 6of 194Abbreviation Definition
HIV Human immunodeficiency virus
HPV Human papillomavirus
ICD-10-CM International Classification of Diseases, Tenth Revision, Clinical 
Modification
ICD-10-PCS International Classification of Diseases, Tenth Revision, Procedure 
Coding Sy stem
IEA International Epidemiological Association
IEC Independent Ethics Committee
IPTW Inverse probability  of treatment weighting
IQR Interquartile range
IRB Institutional Review Board
KD Kawasaki disease
LLR Log-likelihood ratio
MaxSPRT Maximized sequential probability  ratio test
MenACWY Meningococcal conjugate
MenB Serogroup B meningococcal 
MIS-A Multisystem inflammatory  syndromein adults
mRNA Messenger RiboNucleic Acid
MS Multiple sclerosis
NDC National Drug Codes
NIS Non-interventional study
NNERC VAMC Northern New England Research Consortium VA Medical Centers
NSAID Non-steroidal anti -inflammatory  drug
ON Optic neuritis
PASS Post-Authorization Safety  Study
PE Pulmonary  embolism
PRISM Post-Licensure Rapid Immunization Safety  Monitoring
PS Propensity  score
R&D Research and Development
RCA Rapid cycle analysis
RR Relative risk
SAP Statistical analy sis plan
SARS-CoV-2 Severe acute respiratory  syndrome coronavirus 2
SAS SAS Institute
SCCS Self-controlled case series
SCRI Self-controlled risk interval
SD Standard deviation
SJS Stevens-Johnson sy ndrome
SPEAC Safety Platform for Emergency  vACcines
SRSS Subcommittee on Research Safet y and Securit y
TEN Toxic epidermal necrol ysis
TM Transverse m yelitis
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Page 7of 194Abbreviation Definition
TTS Thrombosis with thrombocy topenia sy ndrome
UK United Kingdom
US United States
VA Department of Veterans Affairs
VAIRRS VA Innovation and Research Review Sy stem
VAERS Vaccine Adverse Event Reporting S ystem
VHA Veterans Health Administration
VINCI VA Informatics and Computing Infrastructure
VINNE Veteran’s IRB of Northern New England 
VISN Veterans Integrated Service Networks
VSD Vaccine Safet y Datalink
VTE Venous thromboembolism
WHO World Health Organization
WOC Without compensation
YRR Your Reporting Responsibilities
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Page 8of 1943.RESPONSIBLE PARTIES
Name, degree(s) Job Title Affiliation Address
Principal Investigator:
Yinong Young -Xu, 
ScD, MA, MSDirector, Clinical Epidemiology 
ProgramVeterans Affairs 
(VA) Medical 
Center163 Veterans Drive, 
White River Junction, 
VT 05009
Cynthia de Luise, 
PhD, MPHSenior Epidemiologist /Safety 
Surveillance Research Scientist ;
Risk Management and Safety 
Surveillance ResearchPfizer, Inc. 235 East 42ndStreet, 
New York, NY 10017
Mei Sheng Duh, 
ScD, MPHManaging Principal and Chief 
Epidemiologist
Visiting Scientist, Department of 
BiostatisticsAnalysis Group, 
Inc.
Harvard T. H. 
Chan School of 
Public Health111 Huntington Ave
14thFloor
Boston, MA 02199
677 Huntington Ave
Boston, MA 02115
Maral DerSarkissian, 
PhD Vice President and Senior 
Epidemiologist
Adjunct Assistant ProfessorAnalysis Group, 
Inc.
Fielding School of 
Public Health, 
University of 
California, Los 
Angeles333 South Hope Street
27thFloor
Los Angeles, CA
90071
650 Charles E Young 
DriveSouth
Los Angeles, CA 
90095
Rachel Bhak, MS Manager and Senior Biostatistician Analysis Group, 
Inc.111 Huntington Ave
14thFloor
Boston, MA 02199
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Page 9of 1944.ABSTRACT
Title:Post-Emergency  Use Authorization Active Safety  Surveillance Study  among 
Individuals in the Veteran’s Affairs Health S ystem Receiving Pfizer -BioNTech Coronavirus 
Disease 2019 (COVID -19) Vaccine
Protocol Version: 2.0; Dateof Protocol : 31 Aug2021
Authors: Yinong Young Xu, ScD, MA, MS , Veterans Affairs Medical Center; Cy nthia de 
Luise, PhD, MPH, Pfizer, I nc.; Mei Sheng Duh, ScD, MPH, Anal ysis Group, I nc.
Rationale and b ackground :
In March 2020, the World Health Organization (WHO) declared a global pandemic for the 
coronavirus disease 2019 (COVID -19) due to the severe acute respiratory  syndrome 
coronavirus 2 (SARS -CoV-2), which w as first identified by  public health officials in China 
in December 2019.1The COVID -19 pandemic presents an unprecedented public health 
crisis. As of January  7, 2021, over 21.4million COVID -19 cases and 364,000 deaths have 
been reported in the United States (US) alone.2
Pfizer and BioNTech have partnered to develop a novel messenger RiboNucleic Acid 
(mRNA)vaccine against SARS -CoV-2 for the prevention of COVID -19 (Candidate 
BNT162b2). Pfizer is conducting a Phase 1/2/3, randomized, placebo -controlled, observer -
blind, dose -finding, vaccine candidate- selection, and efficacy  study among healthy  
individua ls (NCT04368728). The Food and Drug Administration (FDA) reviewed the 
available safet y data from 37,586 participants 16 years of age and older and did not identify  
any specific safet y concerns. In addition, the anal ysis of available efficacy  data from 36,523 
participants 12 years of age and older without evidence of prior SARS- CoV-2 infection at 
least 7 day s after receiving the second dose demonstrated 95% efficacy  of the vaccine in the 
prevention of COVID -19 (as confirmed by  8 vs. 162 COVID -19 cases in the vaccine and 
placebo groups, respectively ).3,4Based on these safety  and efficacy  data, as well as a review 
of manufacturing information regarding product quality  and consistency , the FDA 
determined that the known and potential benefits of the vaccine outweighed the known and 
potential risks for the prevention of COVID -19 in individuals 16 y ears of age and older.4
Therefore on December 11, 2020, the Pfizer -BioNTech COVID-19 vaccine was granted an 
Emergency  Use Authorization (EUA) by  the FDA to prevent COVID -19 in individuals 16 
years of age and older.5
With respect to geographic regions other than the US, on December 2, 2020, the United 
Kingdom (UK) was the first country  in the world to grant temporary  authorization for 
emergency  use of the Pfizer -BioNTech COVID -19 vaccine.6On December 21, 2020, the 
European Medicines Agency  (EMA) grant ed the Pfizer -BioNTech COVID- 19 vaccine a 
conditional marketing authorization (CMA) for use among individuals 16 years of age and 
older throughout all of the European Union’s (EU) 27 member states.7
As required b y the EUA, post-authorization observational studies using real -world data are 
needed in order to assess the association between Pfizer -BioNTech COVID- 19 vaccine and 
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Page 10of 194pre-determined safet y events of interest (including deaths , hospitalizations, and severe 
COVID-19)among individuals administered the vaccine in both the population at large and 
in populations of interest ( e.g., immunocompromised individuals, elderl y, and those with 
specific comorbidities) .4Pfizer in collaboration with the US Veterans Health Administration 
(VHA) and Anal ysis Groupherein propose post -EUA active safet y surveillance of safety 
events of interest based primarily on the Priorit y List of Adverse Events of Special Interest 
from the Brighton Collaboration’s Saf ety Platform for Emergency  vACcines (SPEAC) 
Project and from the preliminary  list of safet y events of interest presented at the September 
22, 2020, meeting of Centers for Disease Control and Prevention’s (CDC ’s) Advisory  
Committee on I mmunization Practices (ACIP)on the enhanced safet y monitoring of 
COVID-19 vaccines.8,9This safety  surveillance study  willidentify and evaluate rapid ,near 
real-time potential safet y signals associated with the Pfizer -BioNTech COVID-19 vaccine in 
the large-scale VHA electronic medical record (EMR) database. The observed safet y event of 
interest rates will be compared to expected rates derived from self -controls and active 
comparators receiving seasonal influenza vaccination. Part of the methodologies used in this 
study are constructed based on approaches previously  used by the Post -Licensure Rapid 
Immunization Safet y Monitoring (PRI SM) program for the H1N1 vaccine .10This non-
interventi onal study  is designated as a Post -Authorization Safety Study (PASS) commitment 
to the US FDA and is a Category  3 commitment in the EU Risk Management Plan .
Research question and objectives : 
Research question: what arethe incidence rates of safet y events of interest (based on adverse 
events of special interest [AESI ])among individuals vaccinated with the Pfizer-BioNTech 
COVID-19 vaccine within the US VHA system overall and in sub -cohorts of interest, as 
compared to ex pected rates of those events?
Primary study objectives:
To assess whether individuals in the VHA s ystem experience increased risk of safet y 
events of interest following receipt of the Pfizer- BioNTech COVID -19 vaccine;
To assess whether sub- cohorts of inter est (i.e., immunocompromised, elderly , 
individuals with specific comorbidities, individuals receiving onl y one dose of the 
Pfizer-BioNTech COVID
-19 vaccine, and individuals with prior SARS -CoV-2 
infection) in the VHA s ystem experience increased risk of saf ety events of interest 
following receipt of the Pfizer-BioNTech COVID- 19 vaccine. 
Secondary study objective:
To characterize utilization patterns of thePfizer -BioNTech COVID -19 vaccine 
among individuals within the VHA ,including estimating the proportion of 
individuals receiving vaccine, 2-dose vaccine completion rate,anddistribution of 
time gaps between the first and second dose , demographics and health histories of 
recipients, overall and among the sub-cohorts of interest .
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Page 11of 194Study design: This post-EUAactive safet y surveillance program will employ  a rapid-cycle, 
longitudinal, observational cohort study  designto provide early  real-world safet y 
information . 
The self-controlled risk interval (SCRI) design will be used to sequentially  monitor 
occurrence of safety events of interest while controlling for time- invariant
confounders. The SCRI  design uses data from cases ( i.e., individuals who experience 
safety events of interest following vaccination) to compare the risk interval following 
vaccination t o post-vaccination non -risk intervals (“post-vaccination control 
interval”) in the same individual.
An active comparator design will be used to sequentially  monitor occurrence of safety 
eventsof interest with Pfizer -BioNTech COVID -19 vaccinations as compared to 
recipients of influenza vaccinein the VHA during 2014/2015 through 2018/2019 flu 
seasons. Data in peri -COVID time periods from January  2020 to present are excluded 
because of pandemic- associated under -utilization of health resources and under -
reporting of medical events. 
There will be additional study  designs conducted during the signal evaluation phase if a 
signal is detected from the above anal yses. These include self -controlled case series (SCCS) 
andcomparison to unvaccinated contemporary  controls. Additionally , signal evaluation 
analyses may also be conducted based on signa ls detected in external sources or based on 
regulatory  request.   
Population : The exposed population will be kept as broad as possible in order to capture 
safety events of inte rest that occur among all individuals receiving the Pfizer -BioNTech 
COVID-19 vaccine in the period from December 11, 2020 to present . Individuals will be 
included if they  have a record of at least one dose of Pfizer -BioNTech COVID-19 vaccine. 
Individuals w ho receive at least one dose of COVID -19 vaccine from a manufacturer other 
than Pfizer -BioNTech will be identified and summarized , but they will be excluded from 
further anal ysis. All individuals will be required to be enrolled in and not disenrolled from 
VHA benefits during the 1 y ear prior to vaccination date ( i.e., baseline period). Depending on 
the attrition rate, the length of the baseline period may  be modified to 6 months.
The influenza vaccine comparator cohort will be identified based on a record o f at least one 
dose of seasonal influenza vaccine during prior flu seasons, from 2014/2015 through 
2018/2019.
Variables :
Exposure s: Administration of Pfizer-BioNTech COVID- 19 vaccine post -EUA 
approval will be identified based on the following (seeAppendix Table3for 
additional details) : 
oCurrent Procedural Terminology  (CPT) and associated vaccine administration 
Healthcare Common Procedure Coding S ystem (HCPCS)codes; OR
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Page 12of 194o10 and 11- digit National Drug Codes (NDCs); OR
oImmunization records that contain data on vaccine code descriptor, vaccine 
manufacturer ( i.e., Pfizer), lot number, injection site, and date(s) of 
immunization;11
Relevant codes will be continuously  reviewed and amended if new codes are added.
Administration of the seasonal influenza vaccine during 2014/2015 through 
2018/2019 flu seasons will be identified based on the following (see
Appendix Table3for additional details) :
oCPT codes and associated vaccine administration HCPCS codes ; OR
o10 and 11- digit NDCs; OR
oImmunization records that contain data on vaccine code descriptor, vaccine 
manufacturer, lot number, injection site, and date(s) of immunization. 
Outcomes : Safety events of interest for active surveillance (see Appendix Table2) are 
based on the Priority  List of Adverse Events of Special Interest from the Brighton 
Collaboration’s SPEAC Project, the FDA and the CDC’sACIPenhanced safet y 
monitoring recommendations . 
The list of safet y events of interest may be re vised over the course of the study , and if 
unanticipated potential safety eventsof interest are identified during the course of 
surveillance, they  will be added to the list and included in the anal yses. The risk and 
control intervals for each safet y event of interest are based on biological plausibility 
and precedents in the literature (see Table 1). Outpatient , emergency department
(ED),and/or inpatient settings will be used to identify  safety events of interest 
depending on the t ype of event. The specific encounter setting to be considered for 
each safet y event of interest is summarized in Table 1and can be assigned to 1) the 
risk interval following vaccination Pfizer-BioNTech COVID- 19 vaccin ation, 2) the 
post-vaccination self -control interval, or 3 ) risk interval for the active comparators of 
receiving seasonal influenza vaccine . Events outside the intervals will not be counted.    
Only the individual’s first instance of asafety eventof interest following a specified 
clean window ( i.e., the occurrence -free baseline period usedto define incide nt 
outcomes during which individuals enter the study cohort only  if the safety  event of 
interest did not occur during this period) will be captured; this means that if a safety 
event of interest is identified but diagnosis codes corresponding to the safety  event of 
interest are also observed during the clean window, it will not be counted . The 
duration of the pre-specified clean window will differ by  safety event of interest (see
Appendix Table2) in order to rule out pre -existing events.
Key Covariates: Baseline demographic ( i.e., age, sex, race/ethnicit y, service region ) 
and clinical characteristics ( i.e., smoking, body  mass index [ BMI],history of 
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Page 13of 194anaphylaxis/allergic reactions, previous anaphy laxis to vaccine component, history  of 
hospitalizations, frailty index, Charlson Comorbidity  Index [CCI ], selected 
comorbidities, and concurrent immunizations )12will be assessed based on available 
data (i.e., during 1- year baseline ) prior to the date of vaccination with Pfizer -
BioNTech COVID -19 vaccine and date of seasonal influenza vaccination for active 
comparators .
Subgroups : Immunocompromised individuals (i.e., individuals diagnosed with 
symptomatic human immunodeficiency  virus(HIV)/acquired immunodeficiency  
syndrome (AIDS), hematologic malignancy , or other immune conditions; individuals 
diagnosed with solid malignancy , organ transplant, or rheumatologic/inflammatory
conditions, all of whom were administered chemotherap y or immune modulators; 
individuals diagnosed with rheumatologic/inflammatory  conditions and administered 
systemic corticosteroids; individuals who were administered chemotherap y, immune 
modulators, or systematic steroids for at least 14 day s),13elderly, individuals with 
specific comorbidities,12those receiving onl y one dose of Pfizer -BioNTech COVID-
19 vaccine, those with prior SARS -CoV-2 infection, those with regular use of VHA 
medical care, and VA priority  group 1 veterans will be identified .Analyseswillalso 
be performed among individuals enrolled in the VHA with dual coverage who are 
also identified in linkedCenters for Medicare & Medicaid Services (CMS) Medicare 
administrative claims data. 
Data source :The VHA is the largest integrated health care s ystem in the US, providing both 
inpatient and outpatient clinical care to over 9 million Veterans enrolled at mor e than 170 
medical centers and 1,074 community -based outpatient clinics.14This studywill use data 
from VHA’s Corporate Data Warehouse (CDW), which is an integrated EMR system with a 
centralized data warehouse that is updat ed on a daily  basis.The CDW does not include 
information on an y care received outside of a VHA facility .The VA offers eligible Veterans 
long-term care services ranging from nursing homes and assisted- living centers to caregiver 
support in the Veterans’ o wn homes.15In a subgroup anal ysis of individuals with both VHA 
and Medicare coverage, CDW data will be supplemented and linked with Medicare 
administrative claims data at the patient level to ensure a more comprehensive eval uation of 
the care an individual receives.
Study size: The sample size achieved will depend on the number of recipients of Pfizer -
BioNTech COVID -19 vaccine within the VHA database, which will increase over time with 
subsequent anal yses. As of January  21, 2021, 112,201 doses of Pfizer -BioNTech COVID -19 
vaccine have been administered within the VHA (based on CPT code 91300) to a total of 
107,458 patients.
Data analy sis: A stepwise approach, illustrated in the diagram , will be performed for signal 
detection, evaluation, and verification.   
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Page 14of 194Notes: 
[1] List of safety events of interest and corresponding definitions may be refined as the study progresses based on additiona l 
available information.
[2] The risk and cont rol intervals selected for the SCRI analysis for each safety event of interest are based on biological 
plausibility and precedents in the literature. Only the individual’s first instance during the specified clean window ( i.e., the 
interval used to define incident outcomes) will be included.  Note that only the first inpatient or outpatient occurrence of a 
safety event of interest following the clean window will be used to identify incident events ( e.g., if an inpatient safety event 
of interest occurs in th e clean window, a repeat occurrence will not be counted in the risk interval). However, event 
worsening will be counted as a safety event of interest. For example, if an outpatient safety event of interest occurs in the
clean window and an inpatient occurr ence for the same type of safety event of interest occurs in the risk interval, the 
inpatient occurrence will be counted as a safety event of interest. 
1) Signal detection: The goal is to provide rapid -cycle, near real -time safety  surveillance. In 
the signal detection phase, the SCRI  analysis will include post -vaccination control intervals
for certain safety  events of interest that require a COVID -19 diagnosis (i.e., severe COVID -
19, multisystem inflammatory  syndrome in adults [MIS-A]). To account for mult iple testing 
and bi-weekly review of the data, the maximized sequential probability ratio test (MaxSPRT )
using a binomial probability  model will be applied. For comparison with individuals who 
received seasonal influenza vaccination, the Poisson -based MaxS PRT will be applied for all 
other safet y events of interest . 
Sequential anal yses for each safet y event of interest will commence once at least 3 events 
occur. This approach is consistent with the FDA’s COVID -19 Vaccine Safety  Surveillance 
Projectto avoid spurious signals from a few early events .16Signals will be detected if the 
critical values are reached via the SCRI or active comparator anal ysis.Critical values will be 
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Page 15of 194determined for each safety event of inter est based on historical incidence rate, expected upper 
limit of the number of events under the null hy pothesis, and pre -specified significance level 
and power. 
2) Signal evaluation: If signals are detected for safety  events of interest based on the anal ysis 
described above, further evaluation will be conducted to refine and confirm such detections.  
This will include comprehensive quality  assurance ( for example, check for possible 
duplications of claims or medical records, checking for unusual clustering i n claim or 
medical record accrual by service date for potential coding issues, check for geographical 
distribution of cases that may  be related to lot numbers or diagnostic practice ) and 
multivariate adjustment using Poisson regression to account for basel ine differences between 
Pfizer-BioNTech COVID-19 vaccinated and active comparator cohorts. SCRI analyses using 
the post-vaccination control intervals and SCCS using post -vaccination control time periods 
will be conducted as an additional inferential analys is once enough post -vaccination time has 
accumulated. To address potential period effects, a comparison to contemporary  
unvaccinated controls will also be performed , with adjustment using inverse probability  of 
treatment weighting (IPTW). The assessment of temporal clustering will also be conducted. 
Incidence rates will also be calculated and Kaplan -Meier methods wi llbe used to anal yze 
time to safety event of interest. Signal evaluation anal yses will be conducted every  six 
months.
3) Signal verification: diagnostic validation of the detected safety eventsof interest via 
adjudication of medical records by VHA clinicians for outcome verification will be 
conducted in a representative sample of cases. For rare events, potentiall y all cases may  be 
adjudicated.
End-of-season anal yses (over the course of the 30 -month period) and an end-of- surveillance 
analysis (i.e., at 30 months) will be conducted. Various subgroup anal yses will also be 
conducted, examining different age groups, immunocompromised individuals,13individuals 
with specific comorbidities,12those who only  received one dose of the Pfizer -BioNTech 
COVID-19 vaccine, those with prior SARS -CoV-2 infection based on medical history  or pre-
vaccination serology , those receiving care regularly  at VA facilities ,those with VA Priority  
group 1 status, which determines these individuals are of highest priority  for VHA care and 
likely receive all of their care within the VHA s ystem, and lastly, those with a dditional 
Medicare coverage whose Medicare data can be linked to the CDW.
Notably, CDC recentl y investigated my ocarditis/pericarditis following mRNA COVID -19 
vaccinations.17To provide additional context to the investiga tion conducted by  CDC, 
separate safety  analyses will be prioritized and performed to assess the risk of 
myocarditis/pericarditis following Pfizer -BioNTech COVID-19 vaccination. These analy ses 
will be conducted to align with the rapid- cycle analysis perform ed by the Vaccine Safet y 
Datalink (VSD).18The number of m yocarditis/pericarditis events in the risk interval will be 
identified, and incidence rates per million doses will be summarized . Subgroup anal yses will 
also be perform ed, stratified by  age (e.g.,12-39 years, 40-49 years, 50-64 years, 65+ years), 
gender, and race/ethnicity , respectivel y.Incidence rate ratios will be summarized to compare 
the rate of m yocarditis/pericarditis events between vaccinated individuals who se event occurs 
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Page 16of 194in a pre-specified risk interval versus vaccinated individuals who se event occurs in a 
comparison interval on the same calendar day . Myocarditis/pericarditis events will also be 
adjudicated via chart review and validated using the Brighton Collaboration’s case 
definitions.19Risk factor anal ysis may also be conducted among confirmed cases. Lastly, 
additional data surrounding risk factors, clinical course, and sequelae of identified 
myocarditis/pericardi tis event up to 365 day s following the event will be collected and 
summarized . 
Milestones:
VHA CRADA execution: 8 January  2021;
Determination of Institutional Review Board ( IRB)exemption: 10 February 2021 ;
Determination of Research Safet y and Securit y exemption: 17 February  2021;
Approval b y Designated Member Review: 26 February 2021 ;
Registration in the EU PAS register: 5 March 2021 ;
Start of data collection: 11 May2021;
Interim reports: 30 June 2021; 31 December 2021; 30June 2022, 31 December 2022;
End of data collection : 30 June2023;
Final study  report: 31 December 2023
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Page 17of 194SUMMARY
ObjectivePrimary 1 Primary 2 Secondary
Aim To assess whether individuals in the 
Veterans Health Administration 
(VHA) system experience increased 
risk of safety events of interest 
following receipt of the Pfizer -
BioNTech COVID-19 vaccine. To assess whether sub -cohorts of 
interest (i.e.immunocompromised, 
elderly, with specific comorbidities, 
individuals receiving only one dose 
of the Pfizer -BioNTech COVID -19 
vaccine, and individuals with prior 
SARS-CoV-2 infection ) in the VHA 
system experience increased risk of 
safety events of interest following 
receipt of the Pfizer -BioNTech 
COVID-19 vaccine. To characterize utilization patterns of
thePfizer-BioNTech COVID -19 
vaccine among individuals within the 
VHA including estimati ng the 
proportion of individuals receiving 
vaccine, 2 -dose vaccine completion 
rate, and distribution of time gaps 
between the first and second dose, 
demographics and health histories of 
recipients, overall and among the 
sub-cohorts of interest.
Study design This post-EUA active safety surveillance program will employ a rapid -cycle, longitudinal, observational cohort study 
design to provide early real -world safety information.
The self-controlled risk interval (SCRI) design to sequentially monitor occur rence of safety events of interest 
while controlling for time -invariant confounders. This design allows inclusion of a post -vaccination control 
interval.
An active comparator design will be used to sequentially monitor occurrence of safety events of inter est with 
Pfizer-BioNTech COVID -19 vaccinations as compared to recipients of influenza vaccine in the VHA during 
2014/2015 through 2018/2019 flu seasons. Data in peri- COVID time periods from January 2020 to present are 
excluded because of pandemic -associated under -utilization of health resources and under -reporting of medical 
events.
There will be additional study designs conducted during the signal evaluation phase if a signal is detected from the 
above analyses. These include self -controlled case series (S CCS) and comparison of vaccinated to unvaccinated 
contemporary control s. Additionally, signal evaluation analyses may also be conducted based on signals detected in 
external sources or based on regulatory request (e.g., myocarditis/pericarditis) .   
Studypopulation The study will be kept as broad as possible in order to capture safety events of interest that occur among vaccinated 
individuals.
Inclusion criteria:
Record of at least one dose of Pfizer -BioNTech COVID -19 vaccine in the period of December 11, 2020 to 
present, or
Record of at least one dose of seasonal influenza vaccine during prior flu seasons, from 2014/2015 through 
2018/2019 ( applies to active comparator s only); and
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Page 18of 194ObjectivePrimary 1 Primary 2 Secondary
At least 1 year of enrollment in and no disenrollment from VHA benefits ( i.e., the baseline period) prior to 
Pfizer-BioNTech COVID -19 or seasonal influenza vaccination date. 
Exclusion criteria:
Individuals who receive at least one dose of Pfizer -BioNTech COVID -19 vaccine in addition to a COVID -19 
vaccine from a manufacturer o ther than Pfizer -BioNTech will be identified and summarized , but they will be 
excluded from further analysis. .
Study Period The study will be conducted for a period of 30 months, starting on December 11, 2020 onward, with data collection 
concluding on June 10, 2023.
Exposure Administration of Pfizer -BioNTech COVID -19 vaccine post -EUA approval will be identified based on records of the 
following (seeAppendix Table3for additional details) :
Current Procedural Terminology (CPT) and associated vaccine administration HCPCS codes; OR
10 and 11 -digit National Drug Codes (NDCs); OR
Immunization records that contain data on vaccine code descriptor, vaccine manufacturer ( i.e., Pfizer), lot 
number, injection site, and date(s) of immunization; 
Administration of the seasonal influenza vaccine during 2014/2015 through 2018/2019 flu seasons will be identified 
based on records of the following (seeAppendix Table3for additional details) :
CPT codes and associated vaccine administration HCPCS codes ; OR
10 and 11 -digit NDCs; OR
Immunization records that contain data on vaccine code descriptor, vaccine manufacturer, lot number, 
injection site, and date(s) of immunization. 
Safety Events of Interest Safety events of interest for active surveillance were identified based on the Priority List of Adverse Events of Special 
Interest from the Brighton Collaboration’s Safety Platform for Emergency vACcines (SPEAC) Project, the FDA and 
the Centers for Disease Control and Prevention’s (CDC) Advisory Committee on Immunization Practices (ACIP) 
enhanced safety monitoring recommendations. The list of safety events may be revised over the course of the study, 
and if unanticipated potential safety events of interest are identified during the course of surveillance, they will be 
added to the list and included in the analyses. The risk and control intervals for each safety event of interest are based 
on biological plausibility and precedents in the literature. Outpatient , emergency department ,and/or inpatient settings
will be used to identify safety events of interest depending on the type of event. Safety events of interest can be 
assigned to 1) the risk interval following vaccination Pfizer -BioNTech COVID -19 vaccination, 2) the post -vaccination 
self-control interval, or 3) risk interval for the active comparators of receiving seasonal influenza vaccine. Events 
outside the intervals will not be counted. Only the individual’s first instance of a safety event of interest following a 
specified clean window ( i.e., the occu rrence-free baseline period used to define incident outcomes during which 
individuals enter the study cohort only if the safety event of interest did not occur during this period) w ill be included;
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Page 19of 194ObjectivePrimary 1 Primary 2 Secondary
this means that if a safety event is identified but diagno sis codes corresponding to the safety event are also observed 
during the clean window , it will not be counted . The duration of the pre -specified clean window  will differ by type of 
safety event of interest in order to rule out pre -existing events. 
Neurologic:
Aseptic meningitis
Bell’s palsy
Cerebrovascular non -hemorrhagic stroke
Convulsions/seizures in individuals with controlled epilepsy
Encephalitis/encephalomyelitis
Guillain-Barré Syndrome (GBS) 
Generalized convulsion/seizures
Multiple sclerosis (MS)
Optic neuritis (ON) 
Other acute demyelinating diseases
Transverse myelitis (TM)
Immunologic :
Anaphylaxis
Arthritis and arthralgia/joint pain
Autoimmune thyroiditis
Fibromyalgia
Kawasaki disease (KD)
Multisystem inflammatory syndrome in adults (MIS -A)
Vasculitides
Cardiac:
Acute myocardial infarction (AMI)
Arrhythmia
Coronary artery disease (CAD)
Heart failure and cardiogenic shock
Microangiopathy
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Page 20of 194ObjectivePrimary 1 Primary 2 Secondary
Myocarditis
Pericarditis
Stress cardiomyopathy
Hematologic:
Cerebrovascular hemorrhagic stroke
Chilblain-like lesions
Disseminated intravascular coagulation (DIC)
Deep vein thrombosis (DVT)
Hemolytic anemia
Hemorrhagic disease
Limb ischemia
Pulmonary embol ism(PE)
Single organ cutaneous vasculitis
Thrombocytopenia
Thrombosis with thrombocytopenia syndrome (TTS)
Other:
Acute kidney injury
Appendicitis
Death
Erythema multiforme
Liver injury
Narcolepsy and cataplexy
Non-anaphylactic allergic reactions
Severe COVID- 19 disease
Stevens-Johnson syndrome (SJS)/Toxic epidermal necrolysis (TEN)
Data source The VHA Corporate Data Warehouse (CDW) database w ill be used and maybe supplemented with Medicare 
administrative claims data from the Centers for Medicare & Medicaid Services (CMS) .
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Page 21of 194ObjectivePrimary 1 Primary 2 Secondary
Data analysis A stepwise approach w ill be performed for signal detection, evaluation, and verification.
1) Signal detection: The goal is to provide rapid -cycle, near real -time safety surveillance. SCRIanalyses using the 
post-vaccination control intervals will be conducted for certain safety events of interest that require a COVID -19 
diagnosis (i.e., severe COVID -19 illness, MIS -A). To account for multiple testing and bi -weekly review of the data, the 
maximized sequential probability ratio test (MaxSPRT) using a binomial probability model w ill be applied. For 
comparison with individuals who received seasonal influenza vaccination, the Poisson -based MaxSPRT w ill be applied
for all other safety events of i nterest. 
Sequential analyses for each safety event of interest will commence once at least 3 events occur. This approach is 
consistent with the FDA’s COVID -19 Vaccine Safety Surveillance Project to avoid spurious signals from a few early 
events.  Signals will be detected if the critical values are reached via the SCRI or active comparator analysis. Critical 
values will be determined for each safety event of interest based on historical incidence rate, expected upper limit of 
the number of events under the null hypothesis, and pre -specified significance level and pow er. Incidence rates will 
also be calculated and Kaplan -Meier methods will be used to analyze time to safety event of interest.
2) Signal evaluation: If signals are detected for safety events of i nterest based on the analysis described above, further 
evaluation will be conducted to refine and confirm such detections. This will include comprehensive quality assurance 
(for example, check for possible duplications of claims or medical records, checkin g for unusual clustering in claim or 
medical record accrual by service date for potential coding issues, check for geographical distribution of cases that may 
be related to lot numbers or diagnostic practice) and multivariate adjustment using Poisson regre ssion to account for 
baseline differences between Pfizer -BioNTech COVID -19 vaccinated and active comparator cohorts. SCRI analyses 
using the post -vaccination control intervalsand the SCCS design with post -vaccination control time period will be 
conducted as an additional inferential analysis once enough post -vaccination time has accumulated. To address 
potential period effects, a comparison to contemporary unvaccinated controls will also be performed with adjustment 
using inverse probability of treatment w eighting (IPTW). The assessment of temporal clustering will also be 
conducted. Signal evaluation analyses will be conducted very six months.
3) Signal verification: diagnostic validation of the detected safety events of interest via adjudication of medical records 
by VHA clinicians for outcome validation will be conducted in a representative sample of cases. For rare events, 
potentially all cases may be adjudicated.
End-of-season analyses (over the course of the 30 -month period) and an end -of-surveillance analysis ( i.e., at 30 
months) will be conducted. Various subgroup analyses will also be conducted, examining different age groups, 
immunocompromised individuals, individuals with specific comorbidities, those who only received one dose of the 
Pfizer-BioNTech COVID -19 vaccine, those with prior SARS -CoV-2 infection based on medical history or pre -
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Page 22of 194ObjectivePrimary 1 Primary 2 Secondary
vaccination serology, those receiving care regularly at VA facilities, those with VA Priority group 1 status, which 
determines these individuals are of highest priori ty for VHA care and likely receive all of their care within the VHA 
system, and lastly, those with additional Medicare coverage whose Medicare data can be linked to the CDW .
Notably, CDC recently investigated myocarditis/pericarditis following mRNA COVID -19 vaccinations. To provide 
additional context to the investigation conducted by CDC, separate safety analyses will be prioritized and performed to 
assess the risk of myocarditis/p ericarditis follow ing Pfizer -BioNTech COVID -19 vaccination .These analyses will be 
conducted to align with the rapid -cycle analysis performed by the Vaccine Safety Datalink (VSD).  The number of 
myocarditis/pericarditis events in the risk interval will be identified, and incidence rates per million doses will be 
summarized . Subgroup analyses will also be performed, stratified by age ( e.g., 12-39 years, 40 -49 years, 50 -64 years, 
65+ years ), gender, and race/ethnicity, respectively. Incidence rate ratios w illbe summarized to compare the rate of 
myocarditis/pericarditis events betw een vaccinated individuals who se events occur in a pre-specified risk interval 
versus vaccinated individuals who se events occur in a comparison interval on the same calendar day. 
Myocarditis/pericarditis events will also be adjudicated via chart review and validated using the Brighton 
Collaboration’s case definitions. Risk factor analysis may also be conducted among confirmed cases. Lastly, additional 
data surrounding the risk factors , clinical course, and sequelae of the identified myocarditis/pericarditis event up to 365 
days following the event will be collected and summarized .
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Page 23of 1945.AMENDMENTS AND UPDAT ES
Amendment number Date Protocol 
section(s) 
changedSummary of amendment(s) Reason
1 31 August 
20216 UpdatedtheMilestones section. To add additional information that 
became available after the initial
protocol was submitted to FDA
regarding IRB review, EU PAS 
registration, and data collection 
dates. 
1 31 August 
20219.1.1 Added clarification on the self-
controlled risk interval ( SCRI)design, 
including a description of the 
measurements when there is a gap 
between risk intervals for the first and 
second dose and an illustration (new 
Figure 2B) .To respond to a request from C enter 
for Biologics Evaluation and 
Research (CBER) to demonstrate 
how the period after the risk interval 
for dose 1 and prior dose 2 will be 
handled in the anal ysis if there is no 
overlap between the risk intervals 
for the two doses.
1 31 August 
20219.1.1 Added that a dditional doses of the 
Pfizer-BioNTech COVID- 19 vaccine 
may be included in the analy sis.To address the potentia l approval of 
additional doses. Details for this 
analysis will be further described in 
the statistical analy sis plan.
1 31 August 
20219.1.1, 9.3.3, 
9.7.3, 9.7.5, 9.9Removed SCRI  design with pre -
vaccination control interval and added 
SCRI design with post -vaccination 
control interval for 2 safety  events of 
interest (severe COVID -19, 
multisystem inflammatory  syndrome To address CBER request to 
remove the pre -vaccination control 
interval as its comparison to the risk 
interval may  introduce bias and 
reduce the probabilit y of subsequent 
vaccination. Note additional and 
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Page 24of 194Amendment number Date Protocol 
section(s) 
changedSummary of amendment(s) Reason
in adults[MIS-A]) that could not be 
evaluated with the seasonal influenza 
vaccinated comparators. 
Revised Figures 1 -5 to remove pre-
vaccination control interval and 
provide examples for post -vaccination 
interval. more robust anal yses were added to 
signal evaluation phase (see new 
sections under 9.7.3.2.5 and 
9.7.3.2.6). SCRI  with post -
vaccination control intervals was 
included in the signal detection 
phase to evaluate severe COVID -19 
and MIS-A as they require COVID -
19 diagnosis, which would not be 
observed in a seasonal influenza 
comparator.
1 31 August 
20219.2.3, 9.4 Added clarification for the 
identification of subgroups who are 
immunocompromised sand 
individuals with specific
comorbidities .
Added one additional subgroup of 
interest (individuals with Medicare 
coverage for whom Veterans Health 
Administration [VH A] records can be 
linked to their Medicare claims).To provide additional detail 
regarding how subgroups who are 
immunocompromised and 
individuals with specific
comorbidities will be defined and 
operationalized.
To respond to a query  from CBER 
regarding the potential for 
incomplete data for healthcare 
encounters not received at VHA, an 
additional subgroup of individuals 
with linked Medicare data has been 
added.
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Page 25of 194Amendment number Date Protocol 
section(s) 
changedSummary of amendment(s) Reason
1 31 August 
20219.3.1 All measurement details concerning 
how Pfizer -BioNTech COVID-19 
vaccine and seasonal influenza 
vaccine will be identified in the data 
to an Appendix Table 3 in Section 18. 
Appendix Table 3 includes all specific 
CPT/HCPCS/NDC codes previously  
listed in Section 9.3.1 as well as 
additional codes identified at the time 
of the data anal ysis. To update the protocol with all 
relevant CPT/HCPCS/NDC codes, 
while maintaining concise language 
in the main text.
1 31 August 
20219.3.1, 18 Added Appendix Table 4 in Section 
18 regarding the LOINC codes used to 
identify COVID-19 RT-PCR Test 
among the stud y population and 
corresponding reference.To provide additional details on 
how individuals with prior SARS -
CoV-2 infection will be identified 
in the data.
1 31 August 
20219.3.2, 18 Added fra ilty index as a baseline 
characteristic of interest.To describe the identification of 
frailty in the Pfizer -BioNTech 
COVID-19 and seasonal influenza 
cohorts during the 1- year baseline 
period prior to vaccination as frailt y 
may be a prognostic factor for 
safety events of interest.
1 31 August 
20219.3.3, 18 Added fouradditional safety events of 
interest: thrombosis with 
thrombocy topenia sy ndrome, 
convulsions/seizures in individuals To consider new safety  events 
based on emerging research and 
align with codes from the FDA 
CBER COVID-19 Vaccine Safet y 
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Page 26of 194Amendment number Date Protocol 
section(s) 
changedSummary of amendment(s) Reason
with controlled epileps y, Steven-
Johnson sy ndrome/Toxic epidermal 
necrolysis, and hemol ytic anemia 
(increasing the number of safet y 
events of interest from 42 to 46).
Reclassified COVID -19-related safet y 
events of interest to be measured 
independentl y of the patient ’s
COVID-19 infection status ; this 
change had no impact on the number 
of safety events of interest (reflected 
both in the revised text and revised 
Table 1).
Added that the clean window may  be 
extended (e.g., 2 years).Surveillance : Active Monitoring 
Master Protocol.20,21,22
The COVID -19-related safet y 
events were reclassified to more 
closely align with the FDA CBER 
COVID-19 Vaccine Safety  
Surveillance : Active Monitoring 
Master Protocol. COVID-19-related 
safety events that were previously 
listed may  not necessarily  be related 
to COVID-19 infection (e.g., 
coronary artery disease), a nd 
therefore are defined independent of 
a COVID -19 diagnosis, with the 
exception of “severe COVID -19 
disease” and “MIS -A” which 
requires a concurrent COVID -19 
diagnosis. 
Extending the clean window will 
address the reduction in healthcare 
resource utilizat ion during the 
pandemic to more accurately  
identify incident events. 
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Page 27of 194Amendment number Date Protocol 
section(s) 
changedSummary of amendment(s) Reason
1 31 August 
20219.7.3.2 Clarified in the Signal Evaluation 
section that thesignal evaluation 
analyses will beconducted every  six 
months.To provide additional detail on the 
timing of the signal evaluation 
analyses.
1 31 August 
20219.1.3, 9.7.3.2.5 Added self-controlled case series 
(SCCS)design with fullpost-
vaccination period as an additional
analysis in the Si gnal Evaluation 
analysis. Added that Signal 
Evaluation anal yses may also be 
conducted based on signa ls detected 
in external sources or based on 
regulatory  request(e.g., 
myocarditis/pericarditis) .   To further align with the CBER 
Master Protocol: Assessment of 
Risk of Safety  Outcomes Following 
COVID-19 Vaccination ( March 23, 
2021).23SCCS analy sis has 
increased power compared to SCRI  
design using post -vaccination 
control interval and has been added 
to complement the SCRI  design. In 
addition, clarified that Signal 
Evaluation anal yses may al so be 
conducted based on signals detected 
in external sources or based on 
regulatory  request even if such 
analyses were not first identified in 
the Signal Detection phase of this 
study.
1 31 August 
20219.7.3.2.6 Added a comparison group of 
contemporary  unvaccinated controls 
in the Signal Evaluation analysis.To address the recommendation 
from CBER to include a 
contemporary  control group of 
unvaccinated individuals due to 
potential period effects of an active 
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Page 28of 194Amendment number Date Protocol 
section(s) 
changedSummary of amendment(s) Reason
comparator design that uses 
historical control s of influenza 
vaccinated individuals. 
1 31 August 
20219.7.8 Added new section on 
myocarditis/pericarditis safet y 
analysis and risk factor analysis. To include a separate analy sis 
focused on m yocarditis/pericarditis 
based on emerging evidence 
regarding this event in association 
with mRNA COVI D-19 vaccines.17
1 31 August 
20219.9 Added strengths and limitations 
associated with the addition of the 
SCCS design, contemporaneous 
unvaccinated controls, and subgroup 
analysis of individuals with linkage to 
Medicare claims data.To further describe the rationale for 
these additional anal yses.
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Page 29of 1946.MILESTONES
Milestone Planned date
VHA CRADA execution, Determination of IRB & 
Research Safet y and Security  exemptions, 
Approval by Designated Member Review[1-3]January -February 2021
Registration in the EU PAS register 5 March 2021 
Start of data collection 11 May2021[4]
Interim reports 30June 2021
31December 2021 
30June 2022 
31 December 2022 
End of data collection 30June 2023[5]
Final study  report 31December 2023 
Abbreviations: ACOS, Associate Chief of Staff; COVID -19, Coronavirus disease 2019; CRADA , 
Cooperative Research and Data Agreement; IRB, Institutional Revie w Board; EUA, Emergency Use 
Authorization; FDA, Food and Drug Administration; NNERC VAMC, Northern New England Research 
Consortium VA Medical Centers; R&D, Research and Development; SRSS, S ubcommittee on Research 
Safety and Security; VA, Veterans Affairs; VAIRRS, VA Innovation and Research Review System; VINNE, 
Veteran’s IRB of Northern New England; VHA, Veterans Health Administration; US, United States. 
Notes:
[1] IRB exemption determinati on was granted in accordance w ith 38 CFR 16 by the Veteran’s IRB of 
Northern New England (VINNE), White River Junction VA Medical Center, White River Junction, VT for 
the signal detection and signal evaluation phases. Prior to progressing to the signal ver ification phase for 
chart review, a second IRB review application will be submitted for an expedited or full review. The tw o-
stage IRB application process is to expedite the initiation of the project.
[2] Research Safety and Security exemption determinatio n was granted by the Subcommittee on Research 
Safety and Security (SRSS), VA Innovation and Research Revie w System (VAIRRS).
[3] Approved by Associate Chief of Staff for Research and Development (ACOS/R&D) and R&D 
Committee of the Northern New England Rese arch Consortium VA Medical Centers (NNERC VAMC). 
[4] Start of data collection is the date for starting data extraction for the purposes of the study analysis. The 
initial data analysis includes Pfizer -BioNTech COVID -19 vaccine exposures from December 11, 2020 (the 
EUA approval date by the US FDA) to March 12, 2021 (the data cutoff date).
[5] End of data collection is after the Pfizer -BioNTech COVID -19 vaccine exposure data reached 30 months 
post-EUA approval and the last day of the month that the study wil l be completed.
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Page 30of 1947.RATIONALE AND BACKGR OUND
In March 2020, the World Health Organization (WHO) declared a global pandemic for the 
coronavirus disease 2019 (COVID -19) due to the severe acute respiratory  syndrome 
coronavirus 2 (SARS -CoV-2), which was first i dentified by  public health officials in China 
in December 2019.1The COVID -19 pandemic presents an unprecedented public health 
crisis. As of January 7, 2021, over 21.4million COVID -19 cases and 364,000 deaths have 
been reported in the United States (US) alone.2To date, the incidence of COVID -19 has 
continued to rise, large ly affecting the elderl y and middle -aged individuals, with worsening 
clinical sequelae linked to increasing age and comorbid conditions ( e.g., cardiovascular 
disease, active cancer, obesity , diabetes and chronic lung disease).24,25SARS-CoV-2 is a 
well-adapted highl y infectious human pathogen with a case fatality rate that ranges between 
0.5% and 20%, based on the individual’s age, gender, race, and comorbidites.26
Pfizer and BioNTech have partnered to develop a novel messenger RiboNucleic Acid 
(mRNA)vaccine against SARS -CoV-2for the prevention of COVID -19 (Candidate 
BNT162b2). To this end, Pfizer is conducting a Phase 1/2/3, randomized, placebo -controlled, 
observer-blind, dose -finding, vaccine candidate- selection, and efficacy  study among healthy  
individuals (NCT04368728). In their Phase 1 trial evaluating safety  and immunogenicit y of 
two mRNA vaccine candidates ( i.e., BNT162b1, BNT162b2) at various dose leve ls, 
candidate BNT162b2 was selected for advancement to a pivotal Phase 2/3 safet y and efficacy 
evaluation due to its milder systemic reactogenicity  profile, especially  in older adults.27The 
study was initiated in July  2020 with a target enrollment of 43,998 individuals.28
The US Food and Drug Administration (FDA) announced that regulatory  emergency  use 
authorization (EUA) as well as full approval of any  COVID-19 vaccine will require 
demonstrating prevention of the disease or decrease in its severity  in at least 50% of the 
individuals who receive it. I n addition, data from Phase 3 studies are required to include a 
median follow -up duration of at least 2 months after completion of the full vaccination 
regimen to assess the vaccine’s benefit -risk profile, especiall y adverse events and cases of 
severe COVID -19 in vaccinated study  subjects.29The FDA reviewed the available safet y 
data of the Phase 1/2/3 trial from 37,586 participants 16 y ears of age and older and did not 
identify any specific safety  concerns. In addition, the anal ysis of available efficacy  data from 
36,523 participants 12 years of age and older without evidence o f prior SARS -CoV-2 
infection at least 7 day s after receiving the second dose demonstrated  95% efficacy  of the 
vaccine in the prevention of COVID -19 (as confirmed by  8 vs. 162 COVID -19 cases in the 
vaccine and placebo groups, respectivel y).3,4Based on these safety  and efficacy  data, as well 
as a review of manufacturing information regarding product quality  and consistency , the 
FDA determined that the known and potential benefits of the vacci ne outweighed the known 
and potential risks for the prevention of COVID -19 in individuals 16 y ears of age and older.4
Therefore on December 11, 2020, the Pfizer -BioNTech COVID-19 vaccine was granted an 
EUA by the FDA to preve nt COVID -19 in individuals 16 y ears of age and older.5
With respect to geographic regions other than the US, on December 2, 2020, the United 
Kingdom (UK) was the first country  in the world to grant temporary  authorization for 
emergency  use of the Pfizer -BioNTech COVID -19 vaccine.6On December 21, 2020, the 
European Medicines Agency  (EMA) granted the Pfizer -BioNTech COVID- 19 vaccine a 
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Page 31of 194conditional marketing authorization (CMA) for use among individuals 16 years of age and 
older throughout all of the European Union’s (EU) 27 member states.7
As required b y the EUA, post-authorization observational studies using real -world data are 
needed in order to assess the association between Pfizer -BioNTech COVID- 19 vaccine and 
pre-determined safet y events of interest (including deaths , hospitalizations, and severe 
COVID-19) among individuals administered the v accine in both the population at large and 
in populations of interest ( e.g., immunocompromised individuals, elderl y, and those with 
specific comorbidities) .4Post-authorization safety evaluations are important for identify ing 
rare, serious safet y events of interest in larger populations that may  not have been detected 
during clinical trials (either due to sample size or selected study  populations), and ensure a 
favorable benefit -risk ratio post -trial.Pfizer in collaboration with the US Veterans Health 
Administration ( VHA)of the Department of Veterans Affairs (VA) and Analy sis Group 
herein propose post -EUA active safet y surveillance of safety  events of interest based 
primarily on the Priorit y List of Adverse Events of Specia l Interest from the Brighton 
Collaboration’s Safet y Platform for Emergency vACcines (SPEAC) Project and from the 
preliminary  list of safet y events of interest presented at the September 22, 2020, meeting of 
Centers for Disease Control and Prevention’s (CDC ’s) Advisory  Committee on 
Immunization Practices (ACI P)on the enhanced safet y monitoring of COVID -19 vaccines.8,9
This safet y surveillance study  willidentify and evaluate rapid, near real-time potential safet y 
signals associated with the Pfizer- BioNTech COVID -19 vaccine in the large -scale VHA 
electronic medical record (EMR) database. The observed rates of safet y event of interest will 
be compared to expected rates derived from self -controls and active comparators. Part of the 
methodologies used in this study  are constructed based on approachespreviously  used by the 
Post-Licensure Rapid Immunization Safety  Monitoring (PRISM) program for the H1N1 
vaccine.10This non-interventional study  is designated as a Post -Authorization Safety Study 
(PASS) commitment to the US FDA andisa Category  3 commitment in the EU Risk 
Management Plan.
8.RESEARCH QUESTION AND OBJECTIVES
Research question: what are the incidence rates of safety events of interest (based on adverse 
events of special interest [AESI ]) among individuals vaccinated with the Pfizer-BioNTech 
COVID-19 vaccine within the US VHA system overall and in sub -cohorts of interest a s 
compared to expected rates of those events?
Primary study objectives:
To assess whether individuals in the VHA s ystem experience increased risk of safet y 
events of interest following receipt of the Pfizer- BioNTech COVID -19 vaccine;
To assess whether sub-cohorts of interest ( i.e., immunocompromised, elderly , with 
specific comorbidities, individuals receiving onl y one dose of the Pfizer -BioNTech 
COVID-19 vaccine, and individuals with prior SARS -CoV-2 infection) in the VHA 
system experience increased risk of safety events of interest following receipt of the 
Pfizer-BioNTech COVID- 19 vaccine. 
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Page 32of 194Secondary study objective s:
To characterize utilization patterns of the Pfizer -BioNTech COVID -19 vaccine 
among individuals within the VHA including estimating the proportion of individuals
receiving vaccine, 2-dose vaccine completion rate,and distribution of time gaps 
between the first and second dose , demographics and health histories of recipients, 
overall and among the sub-cohorts of interest. 
9.RESEARCH METHODS
9.1.Study Design 
This post-EUAactive safety  surveillance program will employ  a rapid-cycle, longitudinal, 
observational cohort study design to provide earl y real-world safet y information . The self-
controlled risk interval (SCRI) design will be used to sequentially  monitor occurrence of 
safety events of interest while controlling for time- invariant confounders (such as sex, race, 
chronic illness, and state). I n addition, safety events of interest associated with Pfizer-
BioNTech COVID -19 vaccinations will be sequentially  monitored and compar ed to 
recipients of influenza vaccine in the VHA between 2014/2015 to 2018/2019 .10,30
9.1.1.Self-Controlled Risk Interval (SCRI) Design with Post -Vaccination Control 
Interval
The SCRI design uses data from cases ( i.e., individuals who experience safety events of 
interest following vaccination) to compare the risk interval following vaccination to 
post-vaccination non -risk intervals ( “post-vaccination control interval”) in the same 
individual.31A length of 42 day s has been used to define the risk interval in SCRI  design 
studies for signal detection to ascertain the safet y profile of the H1N1 vaccine.10,30The same 
length of risk interval is proposed here, subject to further modification based on clinical 
input, clinical trial data, biologic plausibility , and published literature. The day  of vaccination 
will only be included in the risk period for thos e safety eventsof interest for which a same -
day occurrence is biologically  plausible ( e.g.,anaphylaxis).
Apost-vaccination control interval will be used for certain safet y events of interest for the 
following reasons: (1) a recent prior safet y event of interest might preclude vaccination 
(i.e.,anaphylaxis), (2) individuals might have an underly ing condition that is also a 
contraindication for vaccination ( i.e., seizure disorder), or (3) safet y event of interest and 
vaccination may  be seasonal in nature.32Thetime between the risk and control intervals will 
be determined based on the biological mechanism of action for each safety eventsof interest 
assessed, and may  be subject to change based on further clinical input . Examples of the SCRI  
design with a post -vaccination control interval (in an individual who only receives the first 
dose of vaccine) is presented in Figure 1below.
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Page 33of 194Figure 1.Example of SCRI Design for Assessment of a Safety Event of Interest with a 
42-day Risk Interval in an Individual who Receives Only One Vaccine Dose, 
with Post -vaccination Control Intervals*
*The risk interv al may include day 0, date of Pfizer -BioNTech COVID -19 vaccination, for some of the safety 
eventsof interest assessed ( e.g., anaphylaxis). The length of the risk interval will vary across each safety event 
of interest and may be subject to change based on clinical input. Note that some individuals may not receive the 
complete course of vaccination, and thus may only receive the first dose of vaccine. This is represented in 
Figure 1while Figure 2represents an example where the complete course with 2 doses are receive d.
Two doses of the Pfizer -BioNTech COVID -19 vaccine are recommended 3 weeks apart.  
This study  program will monitor safety  events of interest that occur after dose 1 before dose 
2 (i.e., during risk interval 1), after dose 2 ( i.e., during risk interval 2), and aggregate for 
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Page 34of 194doses 1 and 2 ( i.e., risk interval 1 + risk interval 2), respectively , for individuals receiving 
both doses. Additional doses of the Pfizer -BioNTech COVID -19 vaccine may be included in 
the analysis should they  be approved , and those details will be described in the statistical 
analysis plan(SAP).
Given the risk intervals for specific safety events of interest range from 1 day  to 90 day s 
(please see Table 1in Section 9.3.3), the time between the first and second dose may  be 
longer or shorter than the recommended risk interval for a given safety eventafter the first 
dose.  See Figure 2below for SCRI design exampleswhere asafety event with a 42 risk 
interval window (e.g., Bell’s palsy ; Table 1 in Section 9.3.3 ) is assessed in hypothetical
individual swho receive two doses of P fizer-BioNTech COVID -19 vaccine: Figure 2Ashows 
the SCRI design with the second dose received 21 day s after the first (i.e., the risk interval 
for dose 1 overlaps with the risk interval for dose 2) , while Figure 2B shows the SCRI  design 
with the second dose received 60days after the first(i.e., there is a gap between the end of 
the risk interval for dose 1 and dose 2 initiation) . For the first scenario ( Figure 2A), t he risk 
interval for dose 1 will be censored at the time of dose 2; further, s afety events of interest that 
occur during the overlapping period of risk interval 1 and risk interval 2 (shown in gray  
shading in Figure 2A) may be flagged for separate anal yses to discern the additive effect of 
Pfizer-BioNTech COVID- 19 vaccine dose 1 and dose 2. For the second scenario ( Figure 2B), 
eventswill only be measured during the risk intervals, ignoring the gap between the end of 
the risk interval for dose 1 and dose 2 initiation. 
For each anal ysis, control intervals corresponding to the risk intervals will be defined either 
at end of the risk interval for dose 1 (for individuals with only  one dose observed) or after the 
risk interval for dose 2 (for individuals with two doses observed), regardless of whether of 
the analyses focus on safety  events after dose 1, after dose 2, or aggregated for doses 1 and 2
(Figure 2A and Figure 2B).
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Page 35of 194Figure 2.Example of SCRI Design for Assessment of a Safety Event of Interest with a
42-day Risk Interval in an Individual who Receives TwoVaccine Dose
s, with 
Post-vaccination Control Intervals
9.1.2.Active Comparator Design
In the active comparator design, the frequency  of safety events of interest among individuals 
who received Pfizer -BioNTech COVID- 19 vaccine from December 11, 2020 onward will be 
compared wit h the event frequency  among recipients of the seasonal influenza vaccination in 
five prior seasons, between 2014/2015 t hrough 2018/2019. Data in peri -COVID time periods 
from January  2020 to present are excluded because of pandemic -associated under -utilization 
of health resources and under -reporting of medical events. The same risk interval length 
(e.g.,42 days)will be used to evaluate safety eventsof interest following vaccination with 
Pfizer-BioNTech COVID -19 vaccine and to assess safet y eventsof interest occurring after 
vaccination for seasonal influenza in prior seasons. The observed number of safety eventsof 
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Page 36of 194interest for Pfizer -BioNTech COVID -19 vaccine will be compared to the expected number 
calculated for the influenza vaccine in past seasons.10
9.1.3.Additional Study Designs in the Signal Evaluation Phase
There will be additional study  designs conducted during the signal evaluation phase if a 
signal is detected from the above anal ysesin the signal detection phase . These in clude 
analyses using self-controlled case series (SCCS) and comparison of vaccinated unvaccinated 
contempora rycontrols.Additionally , signal evaluation anal yses may also be conducted for 
signals detected in external sources or based regulatory  request(e.g., 
myocarditis/pericarditis) . These analy ses are further detailed in Section 9.7.3.2 .
9.1.4.Study Period 
The studywill be conducted for a period of 30 months , starting on December 11, 2020 
onward, with data collection concluding on Ju ne 10, 2023. 
9.2. Setting 
The study population will be kept as broad as possible in order to capture safety eventsof 
interest that occur among all vaccinated individuals.
9.2.1. Inclusion Criteria
Record of at least one dose of Pfizer-BioNTech COVID- 19 vaccine in the period of 
December 11, 2020 to present, or
Record of at least one dose of seasonal influenza vaccine during prior flu seasons, 
from 2014/2015 to 2018/2019 (applies to active comparator s only); and
At least 1 y ear of enrollment in and no disenrollment from VHA benefits ( i.e., the 
baseline period) prior to Pfizer -BioNTech COVID- 19 or seasonal influenza 
vaccination date. 
9.2.2.Exclusion criteria
Individuals who receive at least one dose of Pfizer- BioNTech COVID-19 vaccine in 
addition to a COVID -19 vaccine from a manufacturer other than Pfizer -BioNTech 
will be identified and summarized , but they will be excluded from further anal ysis.
9.2.3.Subgroups
Safety surveillance may  be conducted for subgroups of interest , including, but not limited to:
Immunocompr omised individuals , defined as individuals diagnosed with 
symptomatic human immunodeficiency  virus (HIV)/acquired immunodeficiency  
syndrome (AIDS), hematologic malignancy , or other immune conditions; individuals 
diagnosed with solid malignancy , organ transplant, or rheumatologic/inflammatory  
conditions, all of whom were administered chemotherap y or immune modulators;
individuals diagnosed with rheumatologic/inflammatory  conditions and administered 
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Page 37of 194systemic corticosteroids; orindividuals who were administered chemotherapy , 
immune modulators, or systematic steroids for at least 14 day s;13
Different age groups, with a focus on the elderl y(e.g., <35, 35 - <45, 45 - <55, 55 -
<65, 65 -<75, > 75);
Individuals with specific comorbidities identified as high risk for COVID -19 by the 
CDC (i.e., cancer, chronic kidney disease, chronic obstruction pulmonary disease 
[COPD], Down Sy ndrome, cardiovascular conditions [e.g., heart failure, coronary 
artery disease, or cardiomy opathies], immunocompromised state from solid organ 
transplant, obesity  [body mass index (BMI) of 30 kg/m2 or higher but < 40 kg/m2], 
severe obesity  [BMI of 40 kg/m2or higher], sickle cell disease, smoking, type 1 and 2 
diabetes mellitus);12
Individuals receiving only  one dose of Pfizer-BioNTech COVID-19 vaccine;
Individuals with prior SARS -CoV-2 infection based on medical history  or 
pre-vaccination serology (Appendix Table 4 );
Individuals with regular use of VHA medical care, defined as at least two outpatient 
(excluding emergency  department [ED], as ED visits may  not be considered regular) 
or inpatient enco unters in the one y ear prior to vaccination .The encounters must be 
separated b y >30days (for inpatient, by  admission date), and at least one must be 
within sixmonths prior to the date of vaccination .This will ensure that individuals
have ongoing healt h care encounters, particularl y near the vaccination date, and 
regularly receive their healthcare from VHA facilities, rather than outside facilities
that would not be captured in the VHA’sCorporate Data Warehouse ( CDW);
Individuals who are in the VApriority group 1Veteran. These individuals have either 
the highest levels of service connected disability (≥50% disabling), are considered 
unemploy able, or have received the medal of honor.33Individuals categorized as 
priority group 1 are the highest priorit y for VHA care. This will ensure that the 
individual is more likely  to receive all of their care from a VA facility .
Individuals enrolled in the VHA with dual coverage who are also identified in the 
Centers for Medicare & Med icaid Services (CMS) Medicare administrative claims 
data, which will be linked to the CDW, in order to supplement CDW data for a more 
complete evaluation of healthcare encounters . 
Additional subgroups of interest will be assessed as additional information becomes 
available from ongoing clinical trials, Vaccine Adverse Event Reporting Sy stem (VAERS), 
and other sources that will inform the Pfizer -BioNTech COVID -19 vaccine safet y profile.
Giventhat VA population has a median age of over 46 y ears for females and is comprised of 
approximately  90% males , the evaluation of the Pfizer-BioNTech COVID -19 vaccine safet y 
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Page 38of 194during pregnancy , including fetal death and infant outcomes, may  have poor feasibility and 
will therefore not be conducted. 
9.3.Variables
9.3.1.Exposure of In terest
Administration of Pfizer -BioNTech COVID -19 vaccine post-EUA approval will be identified 
based on the following (seeAppendix Table3for additional details) :
Current Procedural Terminology  (CPT) code sand associated vaccine administration 
HCPCS codes; OR
10 and 11- digit National Drug Codes (NDCs); OR
Immunization records that contain data on vaccine code descriptor, vaccine 
manufacturer ( i.e., Pfizer), lot number, injection site, and date(s) of immunization.11
Relevant codes will be continuously  reviewed and amended if new codes are added.
Person-time at-risk exposure to the first dose onl y, overlapping first and second doses, and 
second dose onl y will be anal yzed separatel y.
Administration of the seasonal influenza vaccine during 2014/2015 through 2018/2019 flu 
seasons wil l be identified based on the following (seeAppendix Table3for additional 
details):
CPT codes; OR
10 and 11- digit NDCs; OR
Immunization records that contain data on vaccine code descriptor, vaccine 
manufacturer, lot number, injection site, and date(s) of immunization. 
9.3.1.1.Pfizer-BioNTech COVID -19 Vaccine Groups of Interest
While the primary  vaccination group of interest is all in dividuals receiving Pfizer- BioNTech 
COVID-19 vaccine (irrespective of receipt of seasonal influenza vaccination), additional 
subsets of the study population will be studied, similar to the PRI SM safety  surveillance 
program of H1N1 vaccine safet y:10
Cohort A: Individuals vaccinated with Pfizer -BioNTech COVID- 19 vaccine who did not 
receive the influenza vaccine during the flu season in which COVID -19 vaccination 
occurred;
Cohort B: Individuals vaccinated with Pfizer -BioNTech COVID-19 vaccine who received 
the seasonal influenza vaccine at least 42 day s prior to COVID -19 vaccination during the 
same flu season in which COVID -19 vaccination occurred;
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Page 39of 194Cohort C: Individuals vaccinated with Pfizer -BioNTech COVID-19 vaccine who received 
the seasonal influenza vaccine within 42 day s before or any  time after COVID -19 
vaccination during the same flu season in which COVID- 19 vaccination occurred;
Cohort D: Individuals vaccinated with both Pfizer -BioNTech COVID -19 vaccine and the 
seasonal influe nza vaccine on the same day .
The following sub -cohorts will be assessed for each of the Cohorts A -D:
Individuals vaccinated with only  1 dose (i.e., incomplete course) of Pfizer -BioNTech 
COVID-19 vaccine;
Individuals vaccinated with 2 doses ( i.e., complete course) of Pfizer- BioNTech 
COVID-19 vaccine.
9.3.2.Baseline Characteristics
The following data elements regarding baseline demographic and clinical characteristics will 
be assessed based on a 1-year baseline period prior to the date of vaccination with Pfizer -
BioNTech COVID -19 vaccine and date of seasonal influenza vaccination for active 
comparator s.Depending on the attrition rate, the length of the baseline period may  be 
modified to 6 months. All diagnoses, procedures, and medications will be identified by the 
International Classification of Diseases, Tenth Revision, Clinical Modification ( ICD-10-CM)
diagnosis codes, ICD -10-PCS (procedure coding system) codes, CPT, orHealthcare 
Common Procedure Coding S ystem (HCPCS) procedure codes, and generic drug names, as 
appropriate (AppendixTable1). The following demographic and clinical characteristics will 
be assessed:
Demographic s:
Age 
Sex
Race/ethnicit y
VHA service area
Clinical characteristics:
Smoking status
BMI
History of anaphylaxis/allergic reactions
Previous anaph ylaxisof vaccine component 
History of hospitalizations
Frailty index
Charlson c omorbidity  index (CCI)
Selected c omorbidities
oAutoimmune disease
oAsthma
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Page 40of 194oBleeding diathesis or condition associated with prolonged bleeding
oCancer
oCardiovascular conditions
oChronic kidney  disease/dialy sis
oCOPD/interstitial lung disease
oDiabetes mellitus
oDown syndrome
oSickle cell disease
oHepatitis B virus ( HBV)
oHepatitis C virus ( HCV)
oHIV
oHyperlipidemia
oHypertension
oLiver disease
oNeurological disease
oOther immune deficiencies
oSolid organ transplant
oVenous thromboembolism (VTE)
Concurrent immunizations
oSeasonal influenza vaccine
oTetanus diphtheria and pertussis (Tdap or Td)
oChickenpox (varicella)
oShingles (herpes zoster recombinant and/or live)
oHuman papillomavirus (HPV)
oPneumococcal conjugate
oPneumococcal pol ysaccharide
oHepatitis A
oHepatitis B
oMeningococcal conjugate (MenACWY) and serogroup B meningococcal 
(MenB)
oHaemophilus influ enza type b
Specific covariates of interest for the prioritized analy sis of myocarditis/pericarditis are 
described in Section 9.7.8 .
9.3.3.Outcomes
The safety events of interest for active surveillance wereidentified based on the Priority List 
of Adverse Events of Special Interest from the Brighton Collaboration’s SPEAC Project, the 
FDA and CDC enhanced safet y monitoring recommendations.8,9Endpoints of special interest 
in signal detection, as noted by  the FDA and CDC’s ACI P are denoted in italics.9If 
unanticipated potential safety eventsof interest are identified during the course of
surveillance, they  will be added to the list and included in the anal yses.See
Appendix Table2for the operational definitions of the outcome variables based on ICD -10-
CM diagnosis codes, which may be refined as the study  progresses based on additional 
available information and the published literature ( e.g., frequency  of ICD-10-CMcodes).
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Page 41of 194Outpatient ,ED,and/orinpatient setting s will be used to identify  safety events of interest, 
depending on the t ype of event. The specific encounter setting considered for each safet y 
event of interest is summarized in Table 1.Any record of death will be captured, regardless 
of whether the individual died in a healthcare or non -healthcare setting. The following safet y 
events of interest will be assessed:
Neurologic :
Aseptic meningitis
Bell’s pals y
Cerebrovascular non -hemorrhagi c stroke
Convulsions/seizures in individuals with controlled epilepsy
Encephalitis/encephalomyelitis
Guillain-Barré Syndrome (GBS) 
Generalized convulsion/seizures
Multiple sclerosis (MS)
Optic neuritis (ON) 
Other acute dem yelinating diseases
Transverse myelitis (TM)
Immunologic :
Anaphylaxis
Arthritis and arthralgia/joint pain
Autoimmune thy roiditis
Fibromyalgia
Kawasaki disease (KD)
Multisystem inflammatory syndrome in adults (MIS-A)
Vasculitides
Cardiac:
Acute myocardial infarction (AMI)
Arrhythmia
Coronary  artery disease (CAD)
Heart failure and cardiogenic shock
Microangiopath y
Myocarditis
Pericarditis
Stress cardiom yopathy
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Page 42of 194Hematologic :
Cerebrovascular hemorrhagic stroke
Chilblain-like lesions
Disseminated intravascular coagulation (DIC)
Deep vein thrombosis (DVT)
Hemolytic anemia
Hemorrhagic disease
Limb ischemia
Pulmonary  embolus (PE)
Single organ cutaneous vasculitis
Thrombocytopenia
Thrombosis with thrombocy topenia sy ndrome (TTS)
Other:
Acute kidney  injury
Appendicitis
Death
Erythema multiforme
Liver injury
Narcolepsy and cataplexy 
Non-anaphylactic allergic reactions
Severe COVID -19 disease
Stevens-Johnson sy ndrome (SJS)/Toxic epidermal necrol ysis (TEN)
The risk intervals selected for each safety event of interest are based on biological 
plausibility  and precedents in the published literature ( Table 1). A safety event of interest 
will only be counted if it can be assigned to 1) the risk interval following Pfizer- BioNTech 
COVID-19 vaccination (all designs) , 2) the post -vaccination control interval (self-controlled 
designs), or 3) the risk interval for the active comparators receiving seasonal influenza 
vaccine(active comparator desig n). Events outside the intervals will not be counted. Onl y the 
individual’s first instance of a safety  event of interest following a specified clean window 
(i.e., the occurrence -free baseline period used to define incident outcomes during which 
individuals enter the study cohort only if the safety event of interest did not occur during this 
period) will be included ; this means that if a safet y event of interest is identified but 
diagnosis codes (or laboratory  values in the case of select safet y events of interest) 
corresponding to the safety  event of interest are also observed during the clean window, it 
will not be counted. The duration of the pre -specified window will differ by safet y events of 
interest in order to rule out pre -existing events. This approa ch is consistent with the FDA’s 
COVID-19 Vaccine Safety  Surveillance Project.16Additionally , the length of the clean 
window may  be extended (e.g., 2 y ears) given the reduction in healthcare resource utilization 
since the start of the pandemic. By way of example, a safety  events of interest for the SCRI 
design can be considered in the following ways:
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Page 43of 194If a safety event of interest occurs in the individual’s risk interval and there are no 
other diagnosis codes for the same saf ety event of interest in the clean window (e.g., 
1-year prior to vaccination date ), the safet y event of interest should be assigned to the 
risk interval.
oHowever, if an outpatient safety event of interest occurs in the clean window 
and an inpatient occurrence for the same t ype of safety event of interest occurs 
in the riskinterval, the inpatient occurrence will be counted in order to capture 
event exacerbation. 
oIf a safety event of interest occurs in the risk interval and another diagnosis 
code for the sa me safety event of interest is identified during the post -
vaccination control interval, then the safety  event of interest will only  be 
assigned to the risk interval 
oIf a safety event of interest occurs in the post -vaccination control interval and 
there are no other diagnoses for the same safety  event of interest in the risk 
intervaland clean window, then the safety  event of interest will be assigned to 
the post-vaccination controlinterval
The risk intervals for outcome evaluation for the active comparato rs who received 
seasonal influenza vaccination will be the same as for the individuals who received 
Pfizer-BioNTech COVID-19 vaccine. 
However, it is possible that some safety eventsof interest do not have a precise time 
interval from which to evaluate risk, for example if biological plausibility  is unknown 
or the diagnostic time window is more delay ed than anticipated. In these cases, 
misspecification of the risk (and control) intervals could re sult in misclassification 
and introduce bias, often toward the null. For instance, the assumption of a longer risk 
interval than is true may result in “washing out” the signal, and an erroneously  short 
risk interval may  similarly  result in underestimation of effect when using post -
vaccination time intervals for self -control. To address this, sensitivity  analyses may 
be conducted with vary ing risk intervals (longer as well as shorter) in order to 
increase the likelihood that the safet y risk is detected accur ately. Additionally , if 
further refinement and evaluation is necessary , temporal scan statistics may  be used 
to empirically  identify the at-risk time interval b y evaluating clusters of safety events 
of interest. This will be further described in the SAP. 
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Page 44of 194Table 1.Outcome algorithms for SCRI analysis, with risk and control intervals
Safety Event of Interest Setting
(Inpatient [IP], Outpatient 
[OP], Emergency 
Department [ED])Clean window Risk interval 
(days)Post-vaccination 
control interval 
(days)
Neurologic
Aseptic meningitis IP only166 months161-423443-8434
Bell’s pals y16IP or OP 6 months 1-42 43-84
Cerebrovascular non -hemorrhagic 
stroke16IP only 1 year 1-28 29-56
Convulsions/seizures in individuals with 
controlled epileps y35IP or OP-ED 1 year 1-90 91-180
Encephalitis/encephalomyelitis16IP only 6 months 1-42 43-84
Guillain-Barré Syndrome (GBS)16IP, primary  position on 1 year 1-42 43-84
Generalized convulsion/seizures10IP or OP-ED 6 months 0-14 15-29
Multiple sclerosis (MS)10,30IP or OP 1 year 1-42 43-84
Optic neuritis (ON)10,30IP or OP 1 year 1-42 43-84
Other acute dem yelinating diseases10,30IP or OP 1 year 1-42 43-84
Transverse m yelitis (TM)16IP or OP-ED 1 year 1-42 43-84
Immunologic
Anaphylaxis IP or OP-ED161 month160-1167-810,30
Arthritis and arthralgia/joint painaIP or OP 1 year 1-42 43-84
Autoimmune thy roiditisaIP or OP 1 year 1-42 43-84
FibromyalgiaaIP or OP 1 year 1-42 43-84
Kawasaki disease (KD)36IP only 1 year 1-28 29-56
Multisystem inflammatory  syndrome in 
adults (MI S-A)16IP or OP-ED 1 year 1-42 43-84
VasculitidesbIP only 1 year 1-28 29-56
Cardiac
Acute myocardial infarction (AMI)16IP only 1 year 1-28 29-56
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Page 45of 194Table 1.Outcome algorithms for SCRI analysis, with risk and control intervals
Safety Event of Interest Setting
(Inpatient [IP], Outpatient 
[OP], Emergency 
Department [ED])Clean window Risk interval 
(days)Post-vaccination 
control interval 
(days)
ArrhythmiacIP only 1 year 1-42 43-84
Coronary  artery disease (CAD)cIP only 1 year 1-42 43-84
Heart failure and cardiogenic shockcIP only 1 year 1-42 43-84
Microangiopath ybIP only 1 year 1-28 29-56
Myocarditis16IP or OP 1 year 1-42d43-84
Pericarditis16IP or OP 1 year 1-42d43-84
Stress cardiom yopathycIP only 1 year 1-42 43-84
Hematologic
Cerebrovascular hemorrhagic stroke16IP only 1 year 1-28 29-56
Chillblain -like lesionsbIP or OP 1 year 1-28 29-56
Disseminated intravascular coagulation 
(DIC)16IP or OP-ED 1 year 1-28 29-56
Deep vein thrombosis (DVT)16IP or OP 1 year 1-28 29-56
Hemolytic anemiaeIP or OP 1 year 1-42 43-84
Hemorrhagic diseasebIP only 1 year 1-28 29-56
Limb ischemiabIP only 1 year 1-28 29-56
Pulmonary  embolus (PE)16IP or OP 1 year 1-28 29-56
Single organ cutaneous vasculitisbIP only 1 year 1-28 29-56
Thrombocy topenia16IP or OP 1 year 1-42 43-84
Thrombosis with thrombocytopenia 
syndrome (TTS)eIP or OP 1 year 1-42 43-84
Other
Acute kidney  injuryfIP only 6 months   1-42 43-84
Appendicitis16IP or OP-ED 1 year 1-42 43-84
Death IP or OP 1 year 0-42 43-85
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Page 46of 194Table 1.Outcome algorithms for SCRI analysis, with risk and control intervals
Safety Event of Interest Setting
(Inpatient [IP], Outpatient 
[OP], Emergency 
Department [ED])Clean window Risk interval 
(days)Post-vaccination 
control interval 
(days)
Erythema multiformegIP only 6 months   1-2 8-9
Liver injuryfIP or OP 1 year 1-42 43-84
Narcoleps y and cataplexy IP or OP161 year161-421643-84
Non-anaphylactic allergic reactions10,30IP or OP 6 months   1-2 8-9
Severe COVID -19 diseasehIP only 1 year 1-42 43-84
Stevens-Johnson sy ndrome (SJS)/Toxic 
epidermal necrol ysis (TEN)gIP only 6 months   1 -2 8-9
Notes: 
a.Published setting, clean window, and risk and control intervals for autoimmune disorders were applied to similar autoimmune r heumatic conditions (i.e., 
arthritis and arthralgia/joint pain, fibromyalgia and autoimmune thyroiditis).
b.Published setting, clean window, and risk and control intervals for DVT, pulmonary embolus and DIC were applied to other cardiovascular and 
hematological disorders characterized by damage to the blood vessels and/or arteries and clotting (i.e., microangiopathy, lim b ischemia, hemo rrhagic 
disease, chilblain -like lesions, single organ cutaneous vasculitis and vasculitides ).The published risk and control intervals for KD were applied to 
vasculitides given that KD is a type of medium and small -vessel vasculitis.
c.Published setting, clean window, and risk and control intervals for myocarditis and pericarditis were applied to other cardiovascular conditions (i .e., heart 
failure and cardiogenic shock, stress cardiomyopathy, CAD, arrhythmia). 
d.For the prioritized safety analysis of myocarditis/pericarditis, additional risk intervals (i.e., 1 -7 days and 1 -21 days) will be examined and are described in 
Section 9.7.8.
e.Published setting, clean window and risk and control intervals for thrombocytopenia were applied to hem olytic anemia and TTS.
f.Risk intervals of 42 days were applied for acute kidney injury and liver injury to be consistent with other similar safety ev ents of interest.
g.Published setting, clean window, and risk and control intervals for non -anaphylactic aller gic reactions were applied to hypersensitivity disorders (i.e., 
erythema multiforme and SJS/TEN). 
h.As severe COVID -19 ranges from severe pneumonia, acute respiratory distress syndrome, and multisystem organ failure/MIS -A, a 1-42 day risk interval 
was applied in order to capture the 14 -day incubation period of the disease and 4 -5 day period from exposure to symptom onset.
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Page 47of 1949.4.Data Source 
The VHA is the largest integrated health care s ystem in the US, providing both inpatient and 
outpatient clinical care to over 9 million Veterans enrolled at more than 170 medical centers 
and 1,074 community -based outpatient clinics.14VHA’s health care delivery  system is 
organized regionall y around 18 Veterans Integrated Service Networks (VISNs) across the 
US. Each VISN is responsible for health care planning and resource allocation in a particular 
geographical region. For example, the VA New England Healthcare S ystem (VISN 1) covers 
VHA facilities in Massachusetts, Connecticut, New Hampshire, Maine, and Rhode I sland, 
while the VA Heart of Texas Health Care Network (VI SN 17) oversees the facilities in 
Texas. 
The VHA also maintains i ts own mortality  data where 99% of enrollees’ deaths are reported 
within one month of occurrence .As of January  7, 2021, the VHA has had over 174,000
confirmed COVID -19 cases.37Among active and convalescent cases , approximately  145,000
are Veterans and approximately  15,000are employees (with an estimated 630 as Veteran 
employees).33While African American Veterans make up approximately  12% of the VHA,38
the burden of COVID -19 cases are skewed, with African American Veterans comprising 
approximately 20% of all COVID -19 cases.37Approximately  7,099COVID-19-infected VA 
patientshave died, an estimated 2,738in VHA hospitals.37
The objectives of this study  will be addressed using data from VHA’s CDW, which is an 
integrated EMR system with a centralized data warehouse that is updated on a daily  basis. 
The CDW stor es data in separate databases, one for each t ype of clinical information ( e.g., 
inpatient medication, inpatient admission, outpatient medication, outpatient visit). Individual
demographic information such as date of birth and gender are also available. Immunization 
records include information on manufacturer, lot number, injection site, and concurrent 
immunizations. The CDW does not include information on any  care received outside of a 
VHA facility . 
Each individual is assigned a unique identification numbe r to allow for longitudinal 
follow-up as well as to cross -reference to the various separate databases. For example, in 
each inpatient admission record, there is information on the primary  discharge diagnosis (and 
as many as 15secondary  diagnoses), date of admission, date of discharge, and length of stay . 
This record can then be linked to other information of that inpatient stay  located in other 
files, including procedures that the patient underwent during the hospitalization, medical 
specialty of the provi der, and prescriptions dispensed. Other files are similarly  structured, 
and therefore may  be linked together to provide comprehensive information about the patient 
and his/her medical encounters. 
The VHA database is an appropriate data source to evaluate the safety of the Pfizer -
BioNTech COVID-19 vaccine for the following reasons. First, as the vaccine will be
distributed through government facilities (including VHA) as part of initial distribution , 
analysis of VHA data will provide earl y data on the safet y of the vaccine. Veterans living in 
long-term care facilities and Veteran s who are healthcare workers will be prioritized in the 
first wave of Pfizer -BioNTech COVID -19 vaccinations.39The VA offers eligible Veterans 
long-term care services ranging from nursing homes and assisted- living centers to caregiver 
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Page 48of 194support in the Veterans’ own homes.15Secondly, and relatedl y, VHA data are refreshed dail y 
and would thus enable early  and rapid data anal ysis. Third, the VHA population is on 
average older than the general US population.40Of these, about 30% (roughly 
1,000,000 individuals) use VHA health services almost exclusively  (i.e., those with a priority  
group of 1 or 4; Veterans assigned to Priorit y group 4 are either accepting VA assistance or 
housebound benefits, or have been determined to be “catastrophicall y disabled” b y the 
VA.33), which lends itself to having complete, longitudinal healthcare data for such 
individuals who may be at higher risk of COVID -19 due to older age.41,42These priorit y 
groups include Veterans with the highest levels of service- connected disability  and are 
therefore, the highest priority  for VHA care.33Finally, the VHA population ha s, on average, 
more comorbid conditions than the general population, which also indicates that these 
individuals may be athigher risk of COVID -19.43While the VHA pop ulation is 
predominantly  male (approximately  90%), and thus lacks generalizability  to females, it will 
still provide a useful setting to examine real -world vaccine safet y.
Since it is possible that individuals may  not have all their health encounters within the VHA, 
(especially  older veterans who are also covered by  Medicare ), additional subgroup analyses 
will be conducted in which the CDW data will be supplemented with data from CMS, linking 
Medicare administrative claims data at the patient level to ensure a more comprehensive 
evaluation of the care an individual receives. Medicare data will include eligibility  files and 
claims for services received in the inpatient and outpatien t setting, as well as skilled nursing 
facilities, hospice, and home health agencies, and will cover the US primarily  among those 
aged 65 years or older.
9.5.Study Size 
The sample size achieved will depend on the number of recipients of Pfizer -BioNTech 
COVID-19 vaccine within the VHA database during the study  period, which will increase 
over time with subsequent analy ses. The population size will increase with each bi -weekly 
analysis as the Pfizer -BioNTech COVID-19 vaccine becomes more readily available and a 
greater number of individuals are vaccinated. Specificall y, the data will be refreshed on a 
biweekly basis and a continuous sequential test procedure will be used to reevaluate data 
according to this schedule. As of January  21, 2021, 112,201 doses of Pfizer -BioNTech 
COVID-19 vaccine have been administered within the VHA (based on CPT code 91300) to a 
total of 107,458 patients.
As a result of the ability  to perform near -real-time analysis, the risk interval (and post -
vaccination control interval, for applicab le safety events of interest ) may have only partially 
elapsed in some cases. To account for this, we will use methods adopted in previous 
studies,10,44,45whereby risk in tervals will be scaled (or truncated) in order to ensure an 
equivalent length (or a fixed ratio) of time is assessed between the control and risk intervals.
9.5.1.Power
Power calculations for the rapid cy cle analysis (RCA) approaches proposed for safety event 
ofinterestsignal detection will be conducted according to the methods of Kulldorff et al.46,47
Table2illustrates the estimated power for the RCA approach using the Poisson -based 
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Page 49of 194maximized sequential probability  ratio test (MaxSPRT), and provides an overview of the 
power required to detect vary ing relative risk (RR ) estimates with an alpha level of 0.01. T 
denotes the expected number of safety events of interest to occur during the risk interval of 
interest (Table2and Table 3). Power of ≥80% is ty pically desirable in drug safet y research. 
Usually the FDA views a RR of > 3 as meaningful, so this has been used fo r power 
calculations here.48As an example, as shown in Table2, the surveillance system would have 
sufficient power (80.0%) to detect an increased risk of safet y events of interest associated 
with the Pfizer -BioNTech COVID- 19 vaccine b y 3 fold when the expected number of safety 
events of interest reaches 6 events. 
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Page 50of 194Table2.Estimated S tatistical Power for the Poisson -based MaxSPRT46
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Page 51of 1949.6.Data Management
Data for this stud y will be stored and extracted from the VHA database (p reviously described 
in Section 9.4) that contain information about patient demographics, vaccinations, 
procedures, diagnoses, and death.  
9.6.1.Case report forms (CRFs)/Electronic data record
As used in this protocol, the term CRF should be understood to refer to either a paper form or 
an electronic data record or both, depending on the data collection method used in this study .
A CRF is required and should be completed for each included patient in the signal 
verification phase that requires EMR and chart review ( seeSection9.7.3.3). The completed 
original CRFs should not be made available in an y form to third parties, except for 
authorized representatives of Pfizer or appropriate regulatory  authorities, without written 
permission from Pfizer. The CRF will consist of two parts: (1) a database CRF that will be 
populated based on a direct extraction of data from the VA CDW for review by  the 
adjudicators; (2) an adjudication page that will be completed by  an adjudicator afte r 
reviewing data in the completed CRFs. Analysis Group shall ensure that the CRFs are 
securely stored on VHA servers in an encry pted electronic and/or paper] form and will be 
password protected or secured in a locked room to prevent access b y unauthorized third 
parties.
Analysis Group has ultimate responsibility  for the collection and reporting of all clinical, 
safety, and laboratory data entered on the database CRFs and an y other data collection forms 
(source documents) and ensuring that they  are accurate,authentic/original, attributable, 
complete, consistent, legible, timely  (contemporaneous), enduring, and available when 
required.  The adjudication page must be signed by  the adjudication committee members to 
attest that the data contained on the formsare trueand accurate based on their review of the 
EMR data . Any corrections to entries made in the CRFs or source documents must be dated, 
initialed, and explained (if necessary) and should not obscure the original entry .
The source documents are the hospital or the ph ysician's chart. In these cases, data collected 
on the CRFs must match those charts. 
9.6.2.Record retention
To enable evaluations and/or inspections/audits from regulatory  authorities or Pfizer, 
Analysis Group agrees to keep all study -related record s, which includes study  documents and 
deliverables such as the protocol, SAP, aggregated results tables, SAS Institute (SAS) 
programming files, and study  report. The records should be retained b y Analysis Group 
according to local regulations or as specifie d in the vendor contract, whichever is longer. 
Analysis Group must ensure that the records continue to be stored securel y for so long as 
they are retained.
If Analysis Group becomes unable for any  reason to continue to retain study  records for the 
requiredperiod, Pfizer should be prospectivel y notified. The study records must be 
transferred to a designee acceptable to Pfizer.
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Page 52of 194Study records must be kept for a minimum of 15 years after completion or discontinuation of 
the study, unless Analy sis Group and Pfi zer have expressly  agreed to a different period of 
retention via a separate written agreement. Record must be retained for longer than 15 years 
if required b y applicable local regulations.  
Analysis Group must obtain Pfizer's written permission before dis posing of any  records, even 
if retention requirements have been met.
9.7.Data Analysis
Detailed methodology  for summary  and statistical anal yses of data analyzedin this study  will 
be documented in a SAP, which will be dated, filed, and maintained b y the spons or. The SAP 
may modify the plans outlined in the protocol; any major modifications of primary  endpoint 
definitions or their anal yses would be ref lected in a protocol amendment. The SAP will also 
provide additional detail regarding the evaluation of a thres hold of excess risk for each of the 
safety events of interest. Consistent with the approach of Kulldorff et al., t his will be 
determined based on background incidences for each event ( e.g., based on historical 
influenza vaccinated active comparator cohort data to be evaluated during the study ), in 
addition to pre -specified significance level ( e.g., alpha=0.01 or 0.05) and power.46This 
information, in conjunction with a clinically  meaningful RR ( e.g., 2 or 3) and the expected 
upper limit of events under the null hypothesis will allow for the calculation of critical values 
of each safet y event of interest using the MaxSPRT method. Greater power (e.g. , 80%) is 
also a natural criterion to use when selecting the upper limit on the length of surveillance, 
and in turn, the expected number of events to occur, although there is ultimately  a tradeoff 
between that power and the time allowed to identify  the expected number of events to occur.
Data analy ses will be conducted using SAS Enterprise Guide version 7.1 (SAS I nstitute Inc., 
Cary, NC) or R Version 3.5.3 or its latest version (R Core Team, Vienna, Austria). In 
addition, SaTScan will also be used to conduct specific temporal anal yses.
9.7.1.Baseline Characteristi cs
Baseline demographics and clinical characteristics for individuals receiving Pfizer -BioNTech 
COVID-19 vaccine and individuals who received seasonal influenza vaccination will be 
summarized using descriptive statistics, consisting of the mean and standar d deviation (SD) 
and median (interquartile range [IQR]) values for continuous variables and frequency  
distributions for categorical variables. Incidence rates ( i.e., per-patient per -month) for prior 
hospitalizations may  be calculated as the number of events divided by  person-time of 
observation since the length of the baseline period may vary  between individuals. 
Standardized differences will be calculated between Pfizer BioNTech COVID -19 vaccine 
recipients and active comparators who received seasonal influ enza vaccination to evaluate 
whether there are an y major differences in individuals’ baseline characteristics. Standardized 
differences <10% will indicate that matching has appropriatel y balanced the charac teristics 
between recipients of the Pfizer- BioNTech COVID -19 vaccine and seasonal influenza 
vaccine.
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Page 53of 1949.7.2.Vaccine Utilization Patterns
Descriptive statistics will also be used to summarize vaccine utilization patterns, including 
proportion of individuals receiving vaccine, 2 -dose completion rate ,distribution of time gaps 
between the first and second dose , and care setting where immunization was received ( e.g., 
outpatient clinic, pharmacy , inpatient ward). Counts of individuals who received a COVID -
19 vaccine from a different manufacturer in addition to the Pf izer-BioNTech COVID-19 
vaccine will be summarized .
9.7.3.Safety Signal Analyses
Several analy ses corresponding to the designs discussed previousl y will be conducted to 
detect safet y signals associated with Pfizer -BioNTech COVID -19 vaccine. Analy ses will be 
conducted among all individuals receiving the vaccine, individuals who received 
Pfizer-BioNTech COVID-19 vaccine without seasonal flu vaccine (Cohort A will be used for 
SCRI; Cohort B +Cwill be used for active comparator analyses), and individuals receiving 
Pfizer-BioNTech COVID- 19 vaccine and seasonal flu vaccine on the same day  (Cohort D), 
along with sub- cohorts receiving onl y one dose vs. two doses. 
A stepwise process, illustrated below, will be performed for signal d etection, evaluation, and 
verification ( Figure 3).This approach has been adapted from the Active Monitoring Protocol 
of the FDA’s COVID -19 Vaccine Safet y Surveillance Project.16The statistical approach 
described below may  be modified further based on data availability , additional clinical input, 
and for consistency  or to complement similar studies of Pfizer -BioNTech COVID-19 
vaccine.
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Page 54of 194Figure 3.Steps in Signal Detection, Evaluation , and Verification
Notes: 
[1] List of safety events of interest and corresponding definitions may be refined as the study progresses based 
on additional available information.
[2] The risk and control intervals selected for the SCRI analysis for each safety event of interest are based on 
biological plausibility and precedents in the literature. Only the individual’s first instance during the specified 
clean window  (i.e., the interval used to define incident outcomes) will be included.  Note that only the first 
inpatient or outpatient occurrence of a safety event of interest following the clean window will be used to 
identify incident events ( e.g., if an inpatient saf ety event of interest occurs in the clean window , a repeat 
occurrence will not be counted in the risk interval). However, event worsening will be counted as a safety event 
of interest. For example, if an outpatient safety event of interest occurs in the cl ean window and an inpatient
occurrence for the same type of safety event of interest occurs in the risk interval, the inpatient occurrence will 
be counted as a safety event of interest. 
9.7.3.1.Signal Detection
Signal detection will rely on SCRI  design with comparison to post -vaccination control 
intervals 
for the two safety  events that require COVID -19 diagnosis (i.e., severe COVID -19 
disease, MIS -A) and active comparator design for the remaining safety events. While the 
active comparator design will be the main analysis for signal detection because it can be 
performed the fastest, it cannot be used for safety  events that require COVID -19 diagnosis 
becausehistorical controls would not meet the criteria of having a COVID -19 diagnosis.
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Page 55of 1949.7.3.1.1. Sequential Testing -SCRI Desi gn using the Binomial -based MaxSPRT for 
Comparison to P ost-vaccination Control Intervals
For the Two Safety Events Requiring 
COVID-19 Diagnosis 
The goal is to provide rapid- cycle, near real -time safet y surveillance. In the signal detection 
phase, the SCRI analysis withpost-vaccination control intervals will be used for certain
safety events of interest ( i.e., severe COVID -19 disease , MIS-A). All other safety events of 
interest will be assessed in the signal detection phase using the active comparator design. The 
post-vaccination control period will be assessed once enough post -vaccination time has 
accumulated. 
To account for multiple testing and bi -weekly review of the data, the MaxSPRT using a 
binomial probability  model will be applied. The null hy pothesis (H 0) assumes that the risk of 
a safety event of interest during the risk interval is equivalent to the risk of the same safety 
event of interest developing during the control interval, accounting for differences in interval 
duration as needed ( e.g.,for safety events of interest such as dem yelinating disease), meaning 
a RR of 1 is specified under H 0.30The one-sided composite alternative h ypothesis (H a) 
assumes that the risk of a safet y event of interest during the risk in
terval is greater than the 
risk of the same safety eventof interest developing during the control interval, accounting for 
differences in interval duration ( i.e., RR>1, Hais applicable across a range of RRs).46
Specifically, for the Pfizer- BioNTech COVID -19 vaccine, let xrepresent the total count of 
safety events of interest in the control interval (Figure 
4), let y represent the total count of 
safety events of interest in the risk interval, and let rrepresent the ratio of yto x under the 
null hypothesis. Thus, when the total control interval du ration and total risk interval duration 
are equal, r will be 1. The RR is estimated by  ..
.44The RR and corresponding 99% 
confidence intervals (CIs) will be calculated. 
Figure 4.Example of SCRI Design for 
a Safety Event of Interest with a 42-day Risk 
Interval and a Post -vaccination Control Interval
For the binomial model, the log -likelihood ratio (LLR) is calculated as the log probability  of 
observing this distribution of y under H a, divided by  the probability  of this occurring under 
H0.46This ratio is calculated whenever new data arereceived to account for the continuous 
data stream until the full 42- day risk period is complete.
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Page 56of 194=ln(|)
(|)
Once the LLR test statistic reaches a pre -specified critical value , a signal is detected.  
Specificall y, the null hypothesis will be rejected if the LLR exceeds the critical value. The 
null hypothesis will not be rejected if the LLR does not r each or exceed the critical value, if 
the total number of safety events of interest reaches a pre -specified upper limit, or if 
surveillance ends without reaching this upper limit.44
For each safety event of interest (and specific to each age group, if age -stratified anal yses are 
conducted), the critical value of the LLR will be determined based on the safety event of 
interest specific upper limit of expected safety events of interest and alpha level.44Upper 
limits will be determined based on the expected number of safety events of interest under the 
null hypothesis, assuming the risk after Pfizer -BioNTech COVID- 19 vaccination is no 
greater than the risk of safety events of interest after seasonal influenza vaccination. 
Therefore, upper limits will be chosen such that they  would not usually  be reached. 
9.7.3.1.2. S equential Testing -Poisson-based MaxSPRT for Comparison to Active 
Comparators who Received Seasonal Influenza Vaccination
For comparison with active comparators who received seasonal influenza vaccination, the 
Poisson-based MaxSPRT will be applied, following the same statistical approach as 
described above, but using a Poisson probabilit y distribution. In the Poisson MaxSP RT 
approach, the event frequency  of safety events of interest in the risk interval after Pfizer-
BioNTech COVID -19 vaccination will be compared to a background rate ofsafety events of 
interest in the risk interval after seasonal influenza vaccination in fi ve prior seasons, ranging 
from 2014/15 through2018/19. This approach is particularl y important for extremely  rare 
safety events of interest (i.e., less than 50 anticipated based on historical influenza vaccine 
ratesof safety events of interest ).30Poisson MaxSPRT is used to monitor very  rare safet y 
events of interest as binomial MaxSPRT may  not detect a signal, despite a clinically  
meaningful RR.44This will also allow for more timely anal ysis using historical data, as well 
as improved power and sample size.
GBS is of particular interest relative to the safety profile of Pfizer -BioNTech 
COVID-19vaccine. As GBS is an extremely  rare safety event of interest , the primary  RCA 
proposed will focus on Poisson MaxSPRT and apply  an alpha of 0.05. The Poisson 
MaxSPRT has increased power to detect a signal with fewer occurrences of the safet y event 
of interest. However, this method cannot fully  control for confoundin g by indication. 
9.7.3.1.3. Critical Values and Alpha Spending
Critical values for the LLR test statistic are shown below in Table 3based on calculations 
conducted b y Kulldorff et al 2011.46For example, assuming T =6 (number of expected 
events under the null) and RR =3, which corresponds to a power of 80.0% (See 
Section9.5.1), the critical value would be 5.14 using alpha of 0.01 for the Poisson -based 
MaxSPRT. As noted previously , each safety  event of interest will be evaluated separatel y to 
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Page 57of 194determine a critical value based on background incidence, alpha, power, and clinically  
meaningful RR. These details will be addressed in the SAP.
Table 3. Critical Values for Poisson- based MaxSPRT
Multiple ty pes of alpha spending functions can be employ ed to calculate the cumulative rate 
at which Ty pe 1 error (alpha) probabilit y is spent during sequential testing.49To achieve 
optimal expected time -to-signal, especiall y when historical Poisson data are used with 
surveillance data, a power-typeconvex alpha spending shape will be used based on published 
literature.49Additionally , ρ =1.5 is referenced as a “rule of thumb” as it i s suggested to be 
appropriate in most applications.
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Page 58of 1949.7.3.2.Signal Evaluation
Signals are detected when the event frequency  of asafety eventof interest during the risk 
interval following vaccination with Pfizer -BioNTech COVID -19 vaccine is significantl y 
increased compared to the event frequency  of the same safety events of interest in the control 
comparator (i.e., the critical value is achieved and surpassed). If signals are indeed detected 
for safety  events of interest based on the anal ysis described above, furt her evaluation is 
warranted to refine and confirm such detections. This will consist of the additional analy ses 
describe in the following sections, which will be conducted every  six months. 
9.7.3.2.1. Post-Signal Quality Assurance
Quality assurance will first be con ducted in order to assess the quality  of the data and 
analysis that produced the signal. While quality control measures will be conducted during 
the signal detection phase (seeSection 9.8), post-signal quality assurance will also be 
performed during the signal evaluation phase. This will include a comprehensive quality 
assurance (for example, check for possible duplications of claims or medical record s, 
checking for unusual clustering in claim or medical record accrual b y service date for 
potential coding issues, check for geographical distribution of cases that may be related to lot 
numbers or diagnostic practice) . In addition, for signals detected vi a active comparison, 
additional anal yses comparing to p ost-vaccination control intervals may  be formed to check 
for consistency . Signals will also be confirmed across all of the safety  studies planned to be 
performed (i.e., C4591008, C4591011, C4591012) to confirm that specific data sources are 
not biased. 
9.7.3.2.2. Multivariate Adjustment using Poisson Regression
If signals are detected and persist after conducting quality  assurance, further evaluation via 
statistical measures are warranted. Specifically , to investigate whether potential signals 
identified via Poisson MaxSPRT for the comparison to active comparators with seasonal 
influenza vaccination are not confounded ( i.e., to take into account baseline differences 
between the Pfizer BioNTech COVID -19 vaccina ted and active comparator populations), a 
multivariate Poisson regression anal ysis will be conducted to compare the incidence rates of 
the safety events of interest occurring within the risk intervals. T he predictor would be
whether the individual had received the Pfizer -BioNTech COVID -19 vaccine or had received 
the influenza vaccine during historical seasons. Analyses will be adjusted for relevant 
baseline and/or clinical characteristics ( e.g., age, sex, race, CCI and/or specific comorbidities 
of interest, state, etc.).10
If the signal remains, based on an IRR > 3 with a p- value <0.01 from the adjusted Poisson 
regression, further evaluation may be considered via signal verification. 
9.7.3.2.3. Assessment of Temporal Clusters
Vaccine safet y surveillance must allow for sufficient ty pe I error probability for rapid 
detection ofsafety events of interest , and statistically  significant signals must be studied 
further to ensure that a true association is present.50Therefore, the presence of temporal 
clusters will be assessed using the software SaTScan to calculate temporal scan statistic in 
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Page 59of 194order to further refine safety  signals detected from the signal detection analy ses.30A temporal 
scan statistic accounts for multiple testing present during overlapping risk intervals. The null 
hypothesis assumes that there is no association between the safet y eventsof interest and 
immunization, and safety events of interest are assumed to be distribut ed independentl y and 
uniformly  during a period of time subsequent to Pfizer -BioNTech COVID- 19 vaccination.30
A temporal scan statistic will be generated b y moving a time interval of fixed length across 
the risk interval, comparing the number of observed versus expected safety events of interest
within the time interval under the null hy pothesis.46
9.7.3.2.4. Sequential Testing -SCRI Design using the Binomial MaxSPRT for 
Comparison with Post -Vaccination Control Intervals
Any safety events of interest with signals detected and not alread y analyzed during the signal 
detection phase with the SCRI design using the binomial -based MaxSPRT will be anal yzed 
during the signal evaluation phase using SCRI design using the binomial- based MaxSPRT 
method for post -vaccination control intervals. This will be conducted during the signal 
evaluation phase in order to allow time to accumulate during the post -vaccination control 
period. The same statistical methodology  as described above will be applied.
9.7.3.2.5. SCCS Design using Conditional Poisson Regression for Comparison with 
Post-Vaccination Control Time Period
Similar to the SCRI  design with post-vaccination control intervals, SCCS design with post -
vaccination control time period will include cases (i.e., individuals vaccinated with the 
Pfizer-BioNTech COVID- 19  vaccine who experience safety events of interest following 
vaccination) to compare the incidence of safet y events occurring in the risk interval 
following vaccination with the incidence of safet y events occurring during all other times 
post-vaccination in the same individual until the earliest of 183 day s after the Pfizer-
BioNTech COVID -19 vaccination, disenrollment, death, end of data availability .This 
analysis will be conducted for all safety  events of interest with signals detected in the signal 
detection phase . The SCCS design differs from the SCRI  design in that instead of having 
fixedpost-vaccination control intervals of the same duration as the risk interval, it has a time -
varying post-vaccination control time period that includes all-non risk interval time from 
Pfizer-BioNTech COVID -19 vaccination date until the earliest of 183 days after Pfizer-
BioNTech COVID -19 vaccination , disenrollment, death, end of data availabilit y.23
For individuals who receive two doses of the vaccine, the post-vaccination control time 
period may  include time before and after Pfizer-BioNTech COVID -19 vaccine dose 2 or 
solely include time after Pfizer-BioNTech COVID- 19 vaccine dose 2. See Figure 5below for 
an example ofan individual who receives two doses of Pfizer-BioNTech COVID- 19 vaccine , 
where the safet y event of interest has a 42 -day risk interval window (e.g., Bell’s pals y; Table 
1 in Section 9.3.3). Figure 5A demonstrates the SCCS design with the second dose received 
21 days after the first (i.e., the risk interval for dose 1 overlaps with the risk interval for dose 
2), while Figure 5B demonstrates the SC CS design with the second dose received 60days 
after the first (i.e., 
with gaps between the end of dose 1 risk interval and dose 2). The post -
vaccination control time peri od isdisplayed belowasshading with gray  lines.
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Page 60of 194Figure 5.Example of SC CS Designfor Safety Event of Interest with a 42 -day Risk 
Intervalwith Post -vaccination Control Intervals when Two Doses of Pfizer -
BioNTech COVID -19 Vaccine are Administered
Compared to the SCRI  design, the SCCS design with post -vaccination control time period 
will have increased statistical power, which isespecially useful 
forthe study of raresafety 
events of interest. A conditional Poisson regression model will be used to compare the rates 
of safety events of interest in the risk interval vs post -vaccination control time period. From 
this model we will report rate ratios and 95% CIsthat will be interpretated as the rate ratio 
for the safety event of interest in the risk interval compared to the control interval.
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Page 61of 1949.7.3.2.6. Comparison with Contemporary Unvaccinated Controls
To address period effects that could impact the appropriateness of using the historical 
comparator cohort, a nalyses will also be performed comparing individuals who received the 
Pfizer-BioNTech COVID- 19 vaccine to individuals who were not vaccinated at that point in 
time.The unvaccinated controls will be assigned an index date matched to a corresponding 
Pfizer-BioNTech COVID -19 vaccinee’s vaccination date ; these individuals can later receive 
the Pfizer -BioNTech COVID- 19 vaccine and enter the vaccination group if all inclusion and 
exclusion criteria are met . To address possible selection bias due to health seeking behaviors, 
the unvaccinated controls will be selected from a population of patients who have regular use 
of VHA medical care, defined as at least two outpatient (excluding ED, as ED visits may  not 
be considered regular) or inpatient encounters in the one year prior to vaccination. The 
encounters must be separated b y > 30 days (for inpatient, by admission date), and at least one 
must be within six months prior to index date. This approach is consistent with the Center for 
Biologics Evaluation and Research ( CBER) Surveillance Program, Draft Master Protocol 
Assessment of Risk of Safety  Outcomes Following COVID -19 Vaccination.23
Inverse probability  treatment weighting (I PTW)will be used to ensure comparability  
between the Pfi zer-BioNTech COVID -19 vaccinated cohort and contemporary unvaccinated 
controls. The IPTW approach uses weights to create a “pseudo -population” in which the 
distribution of covariates is on average the same in each cohort.51IPTW is defined as the 
inverse of the individual’s probability  of receiving the first dose of Pfizer-BioNTech
COVID-19 vaccine, conditional on their demographic and clinical characteristics. This 
approach assumes that an individual’s probability  of receiving Pfizer -BioNTech COVID -19 
vaccination is constant for the first and second doses of the vaccine , as the wei ght will be 
applied for both doses .23Initial inverse probability weights will be calculated as 1 / 
propensity  score (PS) for individuals who received the Pfizer -BioNTech COVID- 19 vaccine 
and 1/ (1- PS) for individuals with no record of COVID -19 vaccination. To avoid extreme 
weights, each individual’s weight will be stabilized by  the marginal probability  of being in 
their assigned cohort. Therefore, the stabilized weights will be calculated as Pr (Pfizer -
BioNTech COVID -19 = 1) / PS for individuals who received the Pfizer-BioNTech COVID -
19 vaccineand 1 -Pr (Pfizer-BioNTech COVID -19 = 1) / (1- PS) for the contemporary  
unvaccinated controls. The distribution of weights will be examined to check for extreme 
values, and truncation will be considered if necessary . 
Weighted Cox regression with robust standard errors to account for within -subject 
correlation will be conducted to compare the risk of safet y events of interest between cohorts. 
Hazard ratios and corresponding 95% CIs wi ll be summarized .
9.7.3.3.Signal Verification
9.7.3.3.1. Medical Records Review
As part of the signal evaluation process, diagnostic validation of the detected safet y events of 
interest (i.e.,cases) via a djudication of patient medical records by VHA clinicians for 
outcome verification in a representative sample of cases will be conducted. The total number 
of charts to be reviewed will depend on the number of safety events of interest detected, such 
that all cases may  be reviewed for safety events of interest where a small nu mber of events 
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Page 62of 194result in signal detection and a representative sub -sample may  be reviewed for safety events 
of interest where a larger number of events results in signal detection .52For rare events, 
potentially  all cases ma y be adjudicated. An adjudication charter will be developed to govern 
signal evaluation and medical records review. Specificall y, validation of detected safet y 
events of interest will be performed through patient medical chart review in collaboration 
withan adjudication committee comprised ofthe treating or trained healthcare 
professionals.52
9.7.4.Seasonality- Adjusted Cases -Centered Method
A case-centered anal ysis for specific safety  events of interest for which signals were detected 
may also be conducted in order to account for bias caused b y seasonality of safety events of 
interest and vaccination.30.53
This method will use data on all safety event of interest cases that occur after vaccination 
with Pfizer -BioNTech COVID -19 vaccine. Logistic regression will be used to compare the 
number of safet y event of interest cases that were vaccinated inside versus outside a pre-
specified risk interval , asof the date of the safety  events,where the total number of 
vaccinations given inside versus outside the risk interval (in the population of all vaccinees) 
is used as the offset term.44Specifically , the association of vaccination with risk of safet y 
events of interest will be estimated from a logistic regression model that includes 
summarized data with one record per risk set. The key  independent variable will be the 
proportion of the risk set who were in the risk interval o n the date of the safety event of 
interestoccurrence. In this way , risk sets are anchored to calendar dates, and confounding b y 
seasonality  of the safet y eventsof interest and vaccination is addressed .53Note that other 
confounders may  also be adjusted for b y restricting risk sets to vaccinees similar with respect 
to select characteristics ( i.e., through stratification). 
9.7.5.End-of-Season and End -of-Surveillance Analyses
For any safety event of interest with signals detected, end -of-season anal yses (over the course 
of the 30- month period) and an end -of-surveillance anal ysis (i.e., at 30 months, after the end 
of surveillance) will be conducted. Similar methodology  will be applied for the end -of-
surveillance anal ysis and end-of-s eason anal ysis conducted for seasonal influenza vaccine in 
order to adjust for the seasonality  of both disease and vaccine administration.10This approach 
will be able to define the true risk intervals after each dose and estima te the risk for potential 
safety events of interest after both dose 1 and 2 of the Pfizer -BioNTech COVID- 19 vaccine, 
as well as the abilit y to discern whether or not one or two doses of seasonal influenza vaccine 
were administered during the same period.  
The number of events in the sum of three distinct risk intervals will be compared to the 
control interval, adjusting for potential differences in interval length, to estimate the RR of 
Pfizer-BioNTech COVID-19 vaccine compared to the influenza vaccine . Inorder to monitor 
the safety after the first and full course of the vaccine, the number of potential safety events 
of interest occurring in three separate risk intervals (P 1, P2, P3) will be estimated ( Figure 6). 
P1represents the risk interval after the first dose only , excluding any  overlap in risk intervals 
with the second dose. P 2represents the overlapping risk intervals for first and second dose of 
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Page 63of 194the vaccine. P 3represents the risk interval of the second dose of the vaccine, excluding the 
overlapping risk interval alread y captured in P 2. This design will allow for the assessment of 
risk during the appropriate periods, regardless of the time interval between vaccine doses. As 
multiple endpoints will be assessed, 99% CI swill be calculated around the RR in order to 
ascertain whether the Pfizer -BioNTech COVID -19 vaccine is associated with 
safety events 
of interest. 
Figure 6.Example of Risk (P 1, P2, P3) and Aggregate Post-vaccination Control 
Intervals for the SCRI End -of-surveillance Analyses of 1 or 2 Doses of
Pfizer-BioNTech COVID -19 Vaccine
In Figure 6A, P1+ P2+ P3represent the risk intervals where a safet y event of interest may 
occur. In Figure 6B,there is no overlapping risk interval so that P 1+ P3represent the risk 
intervals where a safety event of interest may occur.The timing of the risk and control 
intervals may be adjusted fo
r in order to control for the effect of seasonalit y across the 
intervals assessed.
9.7.6.Subgroup Analysis
Separate anal yses of baseline characteristics, vaccine utilization patterns, signal detection, 
signal evaluation, and signal verification insubgroups of interest may  be conducted based on 
feasibility , sample size, and data available. 
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Page 64of 1949.7.7.Incidence Rates and Time to Safety Event of Interest Analysis
Incidence rates (and corresponding CIs) will be calculated from safety event of interest signal 
detection anal yses. Kaplan -Meier methods will be used to anal yze time-to-event (i.e., time to 
safety event of interest ). If individuals do not experience thesafet y events of interest , they 
will be censored at the end of the risk interval. Median t ime to safety event of interest and 
corresponding CI swill be summarized .
9.7.8.Prioritized Safety Analysis of Myocarditis/ Pericarditis
Notably, CDC recentl y investigated the occurrence of myocarditis/pericarditis following 
mRNA COVID -19 vaccinations.17Therefore, separate safet y analyses will be prioritized and 
performed to assess the risk of my ocarditis/pericarditis following Pfizer -BioNTech COVID-
19 vaccination, to provide additional context to the CDC investigation and addr ess regulatory  
requestsfor further information on this safety  event. Therefore, separate analy ses will be 
prioritized and conducted to better understand the risk of my ocarditis/pericarditis following 
Pfizer-BioNTech COVID- 19 vaccination in the VHA. This a nalytical approach is intended to 
align with the methodology  used bythe Vaccine Safet y Datalink (VSD)and preliminary  
findings of m yocarditis/pericarditis published by  ACIP on June 23, 2021.17,18The VSD 
protocol defines m yocarditis/pericarditis (ICD-10-CM codes B33.22, B33.23, I 30, I40) 
events as the first event in 60 day s identified through an ED or inpatient encounter, without a 
first diagnosis of COVID -19 (i.e., COVID -19 diagnosis code or positive COVID -19 lab test) 
in the 30 day s prior to or on the day of the event. This analy sis will follow the outcome 
definition used in the VSD and uses three distinct risk intervals following vaccination (i.e., 1 -
7 days, 1-21 days, and 1-42 days). This definition and the statistical approach differ from the 
primary analysisdescribed in this protocol , but will facilitate comparison with the results 
presented by ACIP.16,17
This analy sis will include all individuals in the primary anal ysis who were vaccinated with 
the Pfizer -BioNTech COVID- 19 vaccine. The number of m yocarditis/pericarditis events in 
the risk interval will be identified, and incidence rates per million doses will be summarized . 
Subgroup anal yses will also be performed, stratified by age ( e.g., 12-39 years, 40-49 years, 
50-64 years, 65+ y ears), gender, and race/ethnicity , respectively.
In addition, vaccinated concurrent comparators will be selected among individuals who 
received the Pfizer -BioNTech COVID -19 vaccine, and then events will be compared 
between vaccinees who are in their risk interval and vaccinees who are concurren tly, on the 
same calendar date, in their comparison interval. Poisson regression will then be used to 
calculate incidence rate ratios and 95% CIs to compare the rate of m yocarditis/pericarditis 
events between those individuals who were in a risk interval v ersus those individuals who 
were in a comparison interval on the same calendar day. Data will be analy zed at the stratum 
level for each calendar day  and will include strata for the independent variable of interest 
(i.e., risk vs. comparison interval) and f or adjustment variables (i.e., age group, sex, 
race/ethnicity , and VHA service area). Thus , the number of m yocarditis/pericarditis events in 
a risk or comparison interval on a calendar day  will be modeled as a function of whether the 
stratum’s vaccinees ar e in a risk versus comparison interval on that calendar day , controlling 
for age, sex, race/ethnicity , and VHA service area. The log of the number of individuals 
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Page 65of 194contributing data to each stratum on each calendar day  will be included as an offset term in 
the Poisson model. Additionally , if it is suggested that calendar time may beassociated with 
risk of post -vaccination my ocarditis/pericarditis, to account for changes COVID- 19 and other 
viruses circulating and other ecologic factors, analyses may alsobe stratified by  calendar 
time, for example in 6 months increments.
In addition to analyzing codified data, C ase confirmation for my ocarditis/pericarditis events 
identified in the codified data will be conducted based on medical chart review. 
Myocarditis/peric arditis cases will be confirmed and validated using the Brighton 
Collaboration’s case definitions .19Risk factor analysis will also be conducted via logistic 
regression among confirmed cases of myocarditis/pericarditis to further evaluate variables 
associated with the event ; additional details will be provided in the SAP.
Additional data surrounding risk factors, clinical course, and sequelae of identified 
myocarditis/pericarditis events up to 365 day s following the event will be collected and 
summarized .These will include an examination of other possible etiologies/risk factors (i.e., 
prior COVID -19 infection, prior Coxsackie infection, other prior viral infections, other 
vaccines received, como rbid immunocompromising conditions and s ystemic immune -
mediated diseases, demographics, and medication history); time between Pfizer -BioNTech 
COVID-19 dose (first and second) and onset of my ocarditis/pericarditis; echocardiogram 
information; lab troponin i nformation; sy mptoms (e.g., chest pain, shortness of breath, 
weakness or fatigue, arm or shoulder pain, heart palpitations cough, swelling in abdomen or 
legs, fever); treatments received for my ocarditis/pericarditis (e.g., non-steroidal anti -
inflammatory  drugs (NSAIDs), colchicine, corticosteroids, pericardectomy ); healthcare 
resource utilization following the event, and long- term sequelae for up to one y ear following 
the event (for my ocarditis: recovery , sudden cardiac death, heart failure cardiogenic shoc k, 
fulminant my ocarditis, inflammatory  cardiomy opathy, heart transplant, arrhy thmia; for 
pericarditis: recovery , chronic pericarditis, restrictive pericarditis, recurrent pericarditis).
9.8.Quality Control
Data for the study  will be extracted from electronic d atabases in the CDW of the VHA. Each 
data content area in the CDW is subjected to similar checks, from high level variable 
name/type checks, to detailed trending comparisons. As an example, the diagnostic data is 
subject to the following checks:
Referenced table exists
Diagnosis type is correctly assigned b y codes defining the diagnosis
Percentages, rates, are as expected (check ranges and for missing)
Both inpatient and outpatient diagnosis codes are captured. Referenced variables exist 
and are of appropri ate length and t ype
Data retrieval will be coordinated b y an experienced programmer/anal yst. The anal yst will 
write programming for retrieval of each data element from the electronic databases. Double 
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Page 66of 194programming will be performed for the first iteration o f the analyses; results/datasets will be 
compared, and if an y discrepancies are identified, both programmers will determine a 
resolution, bringing in a third programmer if needed. Subsequent iterations of anal yses (i.e., 
re-runs of the anal yses) will be au dited by a senior programmer. All tables will be reviewed 
by the project manager and the principal investigator to evaluate for internal consistency  of 
counts and totals. All calculated variables will be checked against the component variables 
(cross tabs) to ensure accuracy . For example, categorical age would be compared with 
continuous age to confirm that each category of age contained onl y individuals of the 
expected age ranges within that category .
9.9.Strengths and Limitations of the Research Methods
To identify  individuals who experienced safety events of interest associated with Pfizer-
BioNTech COVID -19 vaccine, the SCRI  method of signal detection offers some key  
advantages. The SCRI  approach inherentl y adjusts for within-individual confounders, such as 
age, sex, and confounding b y indication. While control intervals can be defined both pre -and 
post-vaccination, the current study  will only use a post-vaccination control period because 
individual smay be more vigilant for the reporting of possible safet y events after they  receive 
a vaccine than before vaccination, which may  bias the comparison between a post -vaccine 
risk interval with a pre -vaccine control interval.54Specificall y, safety events of interest may 
be more likel y to be reported or sought care for after vaccination with Pfizer -BioNTech 
COVID-19 vaccine than before ,which may  result in bias against the Pfizer -BioNTech 
COVID-19 vaccine . Lastly, SCRI allows fo r near real -time monitoring of safet y risks 
associated with the Pfizer -BioNTech COVID- 19 vaccine. Similar considerations apply  to the 
SCCS design with post -vaccination control interval that will be used in the signal evaluation 
phase. 
The comparison of vaccinated to contemporary  unvaccinated controls y ieldsa more 
interpretable result than other planned anal yses using SCRI  and active comparators who 
receive seasonal influenza vaccination (i.e., the increased risk of experiencing a specific 
safety event due to Pfizer -BioNTech COVID -19 vaccination). The potential for selection bias 
(i.e., confounding b y indication, health y user bias) will be mitigated b y comparing baseline 
demographic and clinical characteristics among the unvaccinated controls. Unvacci nated 
controls will be required to have similar healthcare -seeking behaviors asPfizer-BioNTech 
COVID-19 vaccinees, including a t least 1 y ear of enrollment in and no disenrollment from 
VHA benefits prior to their match date. This design is also not limited to assumptions 
required b y SCCS and SCRI , and can also be completed rapidly  as it does not require post -
vaccination control intervals. However, it is noted that the mass vaccination campaign in the 
past year has provided various channels to receive vaccin ation, and therefore unvaccinated 
controls may  be misclassified if they  are vaccinated outside of the VHA. 
The VHA CDW provides a range of benefits, including its comprehensive structure, large 
number of variables, and electronic accessibility . The VHA C DW also includes EMR data 
that include structured fields (which will be used for signal detection) and open fields (such 
as physician notes, which will be used for signal verification and case validation, as needed). 
Importantly , the VHA CDW retains electronic immunization records that include 
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Page 67of 194manufacturer name and lot numbers, facilitating the identification of brand -specific vaccines, 
such as the Pfizer -BioNTech COVID -19 vaccine. Moreover, the VHA CDW data are 
updated on a dail y basis, enabling near real -time rapid monitoring of potential safet y signals. 
However, there are several limitations when rely ing on VHA that should be noted. First, 
there could be gaps in the data since individuals may  receive healthcare services outside of 
VHA facilities. As such, if individuals receive the Pfizer-BioNTech COVID- 19 vaccine 
outside of a VHA facility, this information will not be captured in the VHA EMR sy stem. 
Similarly, individuals may  have also received past seasonal influenza vaccinations outside of 
the VHA s ystem, and thus would be misclassified as not having received vaccine in the 
current anal ysis. For example, veterans with secondary  insurance or veterans who are 
65years of age or older who have Medicare may  receive health care services outside of VHA 
facilities. One study  on VHA enrollees in seven different states found that of all individuals 
admitted to VHA hospitals in 2007, one fifth also had a non VHA hospitalization during that 
year.55Another study  reported that about 53% of Veterans 65 years of age and older who 
were dually  eligible for VHA and Medicare services in 2003 2004 used both.56Hence, it is 
important to note that data on vaccination status may  be incomplete. However, this limitat ion 
will be addressed b y examining subgroups of individuals who receive care regularl y at VHA 
facilities, as well as those with Priority  group 1 status, to ensure that their healthcare data are 
complete to the extent possible in the CDW. The results from t hesesubgroup analyses will be 
compared to the overall population results from the VHA CDW to confirm consistent 
findings such that if there are missing data for individuals in the overall population, the 
missing data can be assumed to be missing at random and not biasing the results in any  
direction. This will be evaluated in the context of evaluating the relative risk of safet y events 
of interest in the comparative anal yses. However, if there are discrepancies that suggest data 
are not missing at random a nd could bias results, subgroup anal yses will be conducted for 
individuals with dual coverage in the VHA and Medicare. T he CDW data will be
supplement ed and linked with Medicare administrative claims data at the patient level to 
ensure a more comprehensive evaluation of the care an individual receives. L inking variables 
are available in the data to allow for patient -level linking of the two data sources. Given the 
older age of man y veterans, it is likely  that these individuals have secondary  coverage with 
Medicare. 
Lastly, to the extent that the individuals in the VHA database are different from individuals 
outside of the VHA, the results may  not be generalizable to the broader US population. For 
example, since the VHA includes predominantl y male Veterans (approximately  90% male), 
findings from this study  may not be generalizable to women in the US. 
9.10.Other Aspects
Not applicable.
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Page 68of 19410. PROTECTION OF HUMAN SUBJECTS
10.1.Patient Information
All parties will comply  with all applicable laws, including laws regarding the implementation 
of organizational and technical measures to ensure protection of patient personal data. Such 
measures will include omitting patient names or other directl y identifiable data in an y 
reports, publications, or other disclosures, except where re quired by applicable laws.
To protect the rights and freedoms of natural individuals with regard to the processing of 
personal data, when study  data are compiled for transfer to Pfizer and other authorized 
parties, an y patient names will be removed and wil l be replaced b y a single, specific, 
numerical code. All other identifiable data transferred to Pfizer or other authorized parties 
will be identified by  this single, patient -specific code. In case of data transfer, Pfizer will 
maintain high standards of co nfidentialit y and protection of individuals’ personal data 
consistent with the vendor contract, and applicable privacy  laws. 
No personal data is planned to be transferred off the VA servers. Specifically, the Clinical 
Epidemiology  Program (CEP) at White R iver Junction VA Medical Center will conduct this 
safety surveillance stud y with sponsorship from Pfizer and assistance from Analy sis Group, 
Inc. The project will be led by  the VA, with Dr. Yinong Young -Xu, Director of CEP, serving 
as the Principal Investi gator. Data access will be granted through VA Informatics and 
Computing I nfrastructure (VINCI). VHA data will not be provided to Pfizer or Anal ysis 
Group.Rather, onl y VA employees, including those with research service without 
compensation (WOC) employ ee status, who have completed necessary  VA training and have 
proper clearance will access and anal yze data on secure VA servers and behind necessary  
firewalls, under the direction and supervision of Dr. Young -Xu. Given the sensitive nature of 
healthcare data, comprehensive securit y measures will be implemented to ensure the 
confidentiality , integrity, and protection of Veterans’ privacy and healthcare data.
10.2.Patient Consent
As this study  does not involve data subject to privacy  laws according to applicable lega l 
requirements, obtaining informed consent from individuals by  Pfizer is not required.  
10.3. Institutional Review board (IRB)/Independent Ethics Committee (IEC)
There must be prospective approval of the study  protocol, protocol amendments, and their 
relevant documents from the relevant I RBs/IECs. All correspondence with the I RB/IEC must 
be retained. Copies of IRB/IEC approvals must be forwarded to Pfizer. The study  protocol 
will be reviewed b y the IRB of the VA Medical Center, White River Junction, VT.
10.4.Ethical Conduct of the Study
The study  will be conducted in accordance with legal and regulatory  requirements, as well as 
with scientific purpose, value and rigor and follow generall y accepted research practices
described in Guidelines for Good Pharmacoepidemiolog y Practices (GPP) issued by the 
International Societ y for Pharmacoepidemiology ,57the FDA Guidance for Industry and FDA 
Staff: Best Practices for Conducting and Reporting, Pharmacoepidemiologic Safet y Studies 
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Page 69of 194Using Electronic H ealthcare Data58and Good Epidemiological Practice (GEP) guidelines 
issued by the International Epidemiological Association (IEA).59
11.MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS 
Signal Detection and Signal Evaluation
This study  involves data that exist as structured data by  the time of study  start or a 
combination of existing structured data and unstructured data, which will be converted to 
structured form during the implementatio n of the protocol solely  by a computer using 
automated/algorithmic methods, such as natural language processing. In these data sources, 
individual patient data are not retrieved or validated, and it is not possible to link (i.e., 
identify a potential assoc iation between) a particular product and medical event for an y 
individual.  Thus, the minimum criteria for reporting an adverse event (AE) (i.e., identifiable 
patient, identifiable reporter, a suspect product, and event) cannot be met. 
Signal Verification
This study  protocol requires human review of patient- level unstructured data; unstructured 
data refer to verbatim medical data, including text-based descriptions and visual depictions 
of medical information, such as medical records, images of ph ysician notes, neurological 
scans, X-rays, or narrative fields in a database.  The reviewer is obligated to report adverse 
events (AEs) with explicit attribution to any  Pfizer drug that appear in the reviewed 
information (defined per the patient population and study period specified in the protocol).  
Explicit attribution is not inferred b y a temporal relationship between drug administration 
and an AE, but must be based on a definite statement of causality  by a healthcare provider 
linking drug administration to the A E.
The requirements for reporting safet y events of interest on the non -interventional study  
(NIS) adverse event monitoring (AEM) Report Form to Pfizer Safety  are as follows:
All serious and non- serious AEs with explicit attribution to any  Pfizer drug that 
appear in the reviewed information must be recorded on the data collection tool (e.g., 
chart abstraction form) and reported, within 24 hours of awareness, to Pfizer Safet y 
using the NIS AEM Report Form.
Scenarios involving drug exposure, including exposure during pregnancy , exposure 
during breast feeding, medication error, overdose, misuse, extravasation, lack of 
efficacy, and occupational exposure associated with the use of a Pfizer product must 
be reported, within 24 hours of awareness, to Pfizer Safet y using the NI S AEM 
Report Form.
For these AEs with an explicit attribution or scenarios involving exposure to a Pfizer 
product, the safety  information identified in the unstructured data reviewed is captured in the 
Event Narrative section of the report form, and constitutes all clinical information known 
regarding these AEs.  No follow-up on related AEs will be conducted.
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Page 70of 194All the demographic fields on the NI S AEM Report Form may  not necessarily  be completed, 
as the form designates, since not all elements will be available due to privacy  concerns with 
the use of secondary  data sources. While not all demographic fields will be completed, at the 
very least, at least one patient identifier (e.g., gender, age as captured in the narrative field of 
the form) will be reported on the NI S AEM Report Form, thus allowing the report to be 
considered a valid one in accordance with pharmacovigilance legislation. All identifiers will 
be limited to generalities, such as the statement “A 35- year-old female...” or “An elderl y 
male...”  Other identifiers will have been removed.      
Additionally , the onset/start dates and stop dates for “Illness”, “Study  Drug”, and “Drug 
Name” may  be documented  in month/y ear (mmm/yyyy ) format rather than identify ing the 
actual date of occurrence within the month /y ear of occurrence in the day /month/year 
(DD/MMM/YYYY ) format.
All research staff members must complete the following Pfizer training requirements:   
Your Reporting Responsibilities ( YRR)Training for Vendors Working on Pfizer 
Studies 
These trainings must be completed by  research staff members prior to the start of data 
collection.  All trainings include a “Confirmation of Training Certificate” (for signature b y 
the trainee) as a record of completion of the training, which must be kept in a retrievable 
format.  Copies of all signed training certificates must be provided to Pfizer. 
Re-training must be completed on an annual basis using the most current Your Reporting 
Responsibilities training materials. 
12.PLANS FOR DISSEMINAT ING AND COMMU NICATING STUDY RESUL TS
This protocol will be posted on publicly available registers following its finalization. The 
final study  results will be made publicly  available via the European Union Post Authorisation 
Safety (EU PAS) Register and may  be submitted for publication in a peer reviewed medical 
journal.
In the event of an y prohibition or restriction imposed (e.g., clinical hold) by an applicable 
competent authorit y in any area of the world, or if the investigator is aware of an y new 
information which mig ht influence the evaluation of the benefits and risks of a Pfizer 
product, Pfizer should be informed immediately.  
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Page 76of 19414.LIST OF TABLES
Table 1. Outcome algorithms for SCRI  analysis, with risk and control 
intervals................................ ................................ ................................ .....44
Table2. Estimated S tatistical Power for the Poisson -based MaxSPRT46..............50
Table 3. Critical Values for Poisson -based MaxSPRT ................................ ...........57
AppendixTable1.Demographic and Clinical Characteristics Definitions ............................ 77
Appendix Table2.Operational Definitions of Safet y Events of Interest.............................. 108
Appendix Table3.COVID-19 and Seasonal I nfluenza Vaccine Exposure CPT, 
HCPCS, NDC Codes ................................ ................................ ..............180
Appendix Table 4. COVID-19 RT-PCR Test L OINC................................ .......................... 193
15.LIST OF FIGURES
Figure 1. Example of SCRI  Design for Assessment of a Safety  Event of 
Interest with a 42- day Risk Interval in an Individual who Receives 
Only One Vaccine Dose, with Post -vaccination Control I ntervals* ........33
Figure 2. Example of SCRI Design for Assessment of a Safety  Event of 
Interest with a 42- day Risk Interval in an Individual who Receives 
Two Vaccine Doses, with Post -vaccination Control I ntervals................. 35
Figure 3. Steps in Signal Detection, Evaluation, and Verification .......................... 54
Figure 4. Example of SCRI  Design for a Safety  Event of Interest with a 42 -
day Risk Interval and a Post -vaccination Control Interval ....................... 55
Figure 5. Example of SCCS Design for Safet y Event of Interest with a 42 -day 
Risk Interval with Post -vaccination Control Intervals when Two 
Doses of Pfizer -BioNTech COVID -19 Vaccine are Administered.......... 60
Figure 6. Example of Risk (P1, P2, P3) and Aggregate Post- vaccination 
Control Intervals for the SCRI  End-of-surveillance Anal yses of 1 or 
2 Doses of Pfizer -BioNTech COVID -19 Vaccine ................................ ....63
16.ANNEX 1. LIST OF STAND ALONE DOCUMENTS
None. 
17.ANNEX 2. ENCEPP CHEC KLIST FOR STUDY PROT OCOLS
N/A
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Page 77of 19418.ANNEX 3. ADDITIONAL INFORMATION
AppendixTable1.Demographic and Clinical Characteristics Definitions
Variable Description Operational definition
Demographic Characteristics
Age Continuous variable;
Categorical variable:
<16
16–64
65–74
≥75Age on the date of Pfizer- BioNTech 
COVID-19 vaccination (and/or date of 
seasonal influenza vaccination for active 
comparators)
Sex Categorical variable: 
Male
Female
Unknown
Race/ethnicit yCategorical variable:
White, non -Hispanic
Black
Hispanic ethnicity , any 
race
Asian
Native Hawaiian or 
Pacific Islander
American Indian or 
Alaskan native
Two or more races
Unknown
VHA service 
areaGeographic regions in the US;
Categorical variable:
South
Midwest
West
Northeast
Other
UnknownRegion associated with the most recent 
healthcare encounter prior to index date 
Clinical Characteristics
Smoking Status Dichotomous variable ICD-9-CM codes:
305.1, Tobacco use disorder
V15.82, History  of tobacco use
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Page 78of 194AppendixTable1.Demographic and Clinical Characteristics Definitions
Variable Description Operational definition
ICD-10-CM codes:
F17.200, Nicotine dependence, 
unspecified, uncomplicated
Z7.20, Tobacco use
Z87.891, Personal history of 
nicotine dependence
Body mass 
index (BMI) *Continuous variable; 
Categorical variable:
Underweight (<18.5) 
Normal weight (18.5 –<25) 
Overweight (25– <30)
Obese (30 –<40)
Severe obesit y (≥40)
UnknownCalculated from height and weight data 
(kg/m2) 
History of 
anaphylaxis/
allergic 
reactionsDichotomous variable ICD-9-CM code:
V13.81, Personal history  of 
anaphylaxis
V14.0–V14.6, V14.8, V14.9, 
Personal history  of allergy  to 
drugs, medications and 
biological substances, excluding 
serum and vaccine
V15.0x, Other allergy
525.66, Allergy  to existing dental 
restorative material
995, Other anaph ylactic shock, 
not elsewhere classified
995.1, Angioneurotic edema, not 
elsewhere classified
995.21, Arthus phenomenon
999.27, Other drug allergy
995.3, Allergy , unspecified, not 
elsewhere classified
995.6x, Anaphy lactic shock due 
to food
999.41, Anaph ylactic reaction 
due to administration of blood 
and blood products
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Page 79of 194AppendixTable1.Demographic and Clinical Characteristics Definitions
Variable Description Operational definition
999.49, Anaph ylactic reaction 
due to other serum 
ICD-10-CM code:
Z87.892  Personal history of 
anaphylaxis
Z88.0–Z88.6, Z88.8, Z88.9, 
Allergy status to drugs, 
medications and biological 
substances, excluding serum and 
vaccine
T78.00xx –T78.09xx, 
Anaphylactic reaction due to 
food, initial encounter, 
subsequent encounter and 
sequela
T78.2xxx, Anaphy lactic shock, 
initial encounter, subsequent 
encounter and sequela
T78.3xxx, Angioneurotic edema, 
initial encounter, subsequent 
encounter and sequela
T78.41xx, Arthus phenomenon
T80.51xx, Anaphy lactic reactio n 
due to administration of blood 
and blood products, initial 
encounter, subsequent encounter 
and sequela
T80.59xx, Anaphy lactic reaction 
due to other serum,  initial 
encounter, subsequent encounter 
and sequela
T88.6xxx, Anaphy lactic reaction 
due to adverse effect of correct 
drug or medicament properly  
administered, initial encounter, 
subsequent encounter and 
sequela
Previous 
anaphylaxis of Dichotomous variable ICD-9-CM code:
999.42, Anaph ylactic reaction 
due to vaccination
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Page 80of 194AppendixTable1.Demographic and Clinical Characteristics Definitions
Variable Description Operational definition
vaccine 
componentV14.7, Personal history of 
allergy to serum or vaccine
ICD-10-CM codes:
T80.52xx, Anaphy lactic reaction 
due to vaccination, initial 
encounter, subsequent encounter 
and sequela
Z28.04, Immunization not 
carried out because of patient 
allergy to vaccine or component
Z88.7, Allergy status to serum 
and vaccine
History of 
hospitalizations Dichotomous variable;
Continuous variableDefined b y having any  hospitalizations
(dichotomous) and number of 
hospitalizations (continuous)
Frailty index60Continuous variable ICD-9-CM codes available in Appendix 
Table 1 of Segal et al, 2017. I CD-9-CM 
codes mapped to ICD -10-CM codes.
Charlson 
Comorbidity  
Index (CCI )61Continuous variable ICD-9-CM codes:
410.x, 412.x, Myocardial 
infarction
398.91, 402.01, 402.11, 402.91, 
404.01, 404.03, 404.11, 404.13, 
404.91, 404.93, 425.4 –425.9, 
428.x, Congestive heart failure
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Page 81of 194AppendixTable1.Demographic and Clinical Characteristics Definitions
Variable Description Operational definition
093.0, 437.3, 440.x, 441.x, 
443.1–443.9, 447.1, 557.1, 
557.9, V43.4, Peripheral vascular 
disease
362.34, 430. x–438.x, 
Cerebrovascular disease
290.x, 294.1, 331.2, Dementia
416.8, 416.9, 490.x– 505.x, 
506.4, 508.1, 508.8, Chronic 
pulmonary  disease
446.5, 710.0 –710.4, 714.0 –
714.2, 714.8, 725.x, Rheumatic 
disease
531.x–534.x, Peptic ulcer disease
070.22, 070.23, 070. 32, 070.33, 
070.44, 070.54, 070.6, 070.9, 
570.x, 571.x, 573.3, 573.4, 
573.8, 573.9, V42.7, Mild liver 
disease
250.0–250.3, 250.8, 250.9, 
Diabetes without chronic 
complication
250.4–250.7, Diabetes with 
chronic complication
334.1, 342.x, 343.x, 344.0 –
344.6,344.9, Hemiplegia or 
paraplegia
403.01, 403.11, 403.91, 404.02, 
404.03, 404.12, 404.13, 404.92, 
404.93, 582.x, 583.0–583.7, 
585.x, 586.x, 588.0, V42.0, 
V45.1, V56.x, Renal disease
140.x–172.x, 174.x –195.8, 
200.x–208.x, 238.6, Any  
malignancy , including l ymphoma 
and leukemia, except malignant 
neoplasm of skin
456.0–456.2, 572.2 –572.8, 
Moderate or severe liver disease
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Page 82of 194AppendixTable1.Demographic and Clinical Characteristics Definitions
Variable Description Operational definition
196.x–199.x, Metastatic solid 
tumor
042.x–044.x, Acquired 
immunodeficiency  syndrome 
(AIDS)/Human 
immunodeficiency  virus (HIV)
ICD-10-CM codes:
I21.x, I21.xx, I 22.x, I25.2, 
Myocardial infarction
I09.9, I11.0, I13.0, I13.2, I25.5, 
I42.0, I42.5–I42.9, I43, I43.x, 
I50.x, I50.xx, Congestive heart 
failure
I70.x, I71.x, I 73.1, I73.8, I 73.9, 
I77.1, I79.0, I79.2, K55.1, K55.8, 
K55.9, Z95.8, Z95.9, Periphe ral 
vascular disease
G45, G45.x, G46.x, H34.0, 
I60.x–I63.x, I60.xx–I63.xx, 
I60.xxx–I63.xxx, I65.x–I69.x, 
I65.xx–I69.xx, I65.xxx–I69.xxx, 
Cerebrovascular disease
F00.x–F03.x, F00.xx –F03.xx, 
F05, F05.1, G30.x, G31.1, 
Dementia
I27.8, I27.9, J40.x –J47.x, 
J40.xx–J47.xx, J40.xxx –J47.xxx, 
J60.x–J67.x, J68.4, J70.1, J70.3, 
Chronic pulmonary  disease
M05, M05.x, M05.xx, M05.xxx, 
M06, M06.x, M06.xx, M06.xxx, 
M31.5, M32.x –M34.x, M32.xx –
M34.xx, M35.1, M35.3, M36.0, 
Rheumatic disease
K25.x–K28.x, Peptic ulcer 
disease
B18.x, K70.0– K70.3, K70.9, 
K71.3–K71.5, K71.7, K73.x, 
K74.x, K74.xx, K76.0, K76.2 –
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Page 83of 194AppendixTable1.Demographic and Clinical Characteristics Definitions
Variable Description Operational definition
K76.4, K76.8, K76.9, Z94.4, 
Mild liver disease
E10.0, E10.1x, E10.6x, E10.6xx, 
E10.8, E10.9, E11.0x, E11.1x, 
E11.6x, E11.6xx, E11.8, E11.9, 
E12.0, E12.1, E12.6, E12.8, 
E12.9, E13.0x, E13.1x, E13.6x, 
E13.6xx, E13.8, E13.9, E14.0, 
E14.1, E14.6, E14.8, E14.9, 
Diabetes without chronic 
complication
E10.2x–E10.5x, E10.2xx–
E10.5xx, E10.7, E11.2x –E11.5x, 
E11.2xx–E11.5xx, E11.7, E12.2 –
E12.5, E12.7, E13.2 –E13.5x, 
E13.
…[truncated]