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BNT162b2 C4591014 NON- INTERVENTIONAL STUDY PROTOCOL
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PFIZER CONFIDENTIAL
CT24- WI-GL02 -RF02 2.0 Non-Interventional Study Protocol Template For Secondary Data Collection Study
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Page 1 of 42NON -INTER VENTIONAL (NI) STUDY PROT OCOL
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Page 2of 42Study information
Title Pfizer-BioNTech COVID -19 BNT162b2 Vac-
cine Effectiveness Study -Kaiser Perma-
nente Southern California
Protocol number C4591014
Protocol version identifier Version 1.0
Date 22 March 2021
Research question and objectives The primary objective of this study is to esti-
mate vaccine effectiveness (VE) of 2 -doses
of Pfizer’s BNT162b2 (fully vaccinated)
against acute respiratory illness requiring
hospitalization due to SARS -CoV -2 infec-
tion among KPSC members 16 years of
age. Secondary and exploratory objectives
will examine VE for 1 dose vaccination, at
least 1 dose, as well as against ED admis-
sion, specific variants and other populations
of interest.
To assess vaccine effectiveness (VE), we
propose a large retrospective database stud y
using two parallel study designs: a test -neg-
ative case -control design and a retrospective
cohort design. We will conduct additional
analyses of VE estimates by various patient
characteristics and strain ty pe.
Author Sara Y. Tartof, PhD MPH
Kaiser Permanente Southern California De-
partment of Research & Evaluation
[email protected]
(626)564 -3001
Heidi Fischer, PhD MS
Kaiser Permanente Southern California De-
partment of Research & Evaluation
[email protected]
(626)564 -3290
Jeff Slezak, MS
Kaiser Permanente Southern California De-
partment of Research & Evaluation
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Page 3of [email protected]
(626)564 -3477
John M. McLaughlin, PhD
Pfizer Vaccines
Medical Development and Scientific/Clini-
cal Affairs
john.mcla [email protected]
Fred Angulo, DVM PhD
Pfizer Vaccines
Medical Development and Scientific/Clini-
cal Affairs
[email protected]
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Page 4of 421.TABLE OF CONTENTS
1. TABLE OF CONTENTS ................................ ................................ ................................ .......4
2. LIST OF ABBREVIAT IONS ................................ ................................ ................................ 6
3. RESPONSIBLE PARTI ES................................ ................................ ................................ ....8
4. ABSTRACT ................................ ................................ ................................ ........................... 8
5. AMENDMENTS AND UP DATES ................................ ................................ ..................... 10
6. MILESTONES ................................ ................................ ................................ ..................... 10
7. RATIONALE AND BAC KGROUND ................................ ................................ ................ 11
8. RESEARCH QUESTION AND OBJECTI VES ................................ ................................ .12
9. RESEARCH METHODS ................................ ................................ ................................ ....16
9.1. Research Setting ................................ ................................ ................................ ......16
9.2. Study design ................................ ................................ ................................ ............ 18
9.2.1. I nclusion criteria ................................ ................................ ......................... 20
9.2.2. E xclusion criteria ................................ ................................ ........................ 20
9.3. Variables ................................ ................................ ................................ .................. 21
9.3.1. Test Negative Design Outcomes and Exposures ................................ ........ 21
9.3.2. Full Cohort Design Outcome and Exposures ................................ ............. 22
9.3.3. Test -Negative and Full Cohort Designs –Outside Vaccinations ............... 23
9.3.4. Test -Negative and Full Cohort Designs -Covariates ................................ .24
9.4. Data sources ................................ ................................ ................................ ............ 24
9.5. Study size ................................ ................................ ................................ ................ 25
9.6. Data management ................................ ................................ ................................ ....29
9.6.1. Electronic data records ................................ ................................ ............... 29
9.6.2. Record retention ................................ ................................ .......................... 29
9.7. Data analy sis................................ ................................ ................................ ........... 30
9.7.1. Test Negative Design Analy ses................................ ................................ ..30
9.7.1.1. Descriptive Analyses ................................ ................................ .30
9.7.1.2. Estimated Crude (Unadjusted) VE ................................ ............ 30
9.7.1.3. Estimating Adjusted VE ................................ ............................ 31
9.7.1.4. Sensitivity Analyses ................................ ................................ ..31
9.7.1.5. Exploratory analy ses estimating VE for health care
workers and other high risk populations ................................ ........... 31
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Page 5of 429.7.2. Full Cohort Design Analy ses................................ ................................ ......33
9.7.2.1. Descriptive Analyses ................................ ................................ .33
9.7.2.2. Estimated Crude (Unadjusted) VE ................................ ............ 33
9.7.2.3. Estimating Adjusted VE ................................ ............................ 33
9.7.2.4. Sensitivity Analyses ................................ ................................ ..33
9.7.2.5. Exploratory analy ses estimating VE for health care
workers and other high risk populations ................................ ........... 34
9.7.3. Additional Analy tic Elements for Test Negative and Full Cohort
Design ................................ ................................ ................................ .............. 34
9.8. Quality control ................................ ................................ ................................ ......... 35
9.9. L imitations of the research methods ................................ ................................ .......36
9.10. Other aspects ................................ ................................ ................................ ......... 36
10. PROTECTI ON OF HU MAN SUBJECTS ................................ ................................ ........ 37
10.1. Patient information................................ ................................ ................................ 37
10.2. Patient consent ................................ ................................ ................................ .......37
10.3. I nstitutional Review Board (IRB)/Independent Ethics Committee (I EC)............ 37
10.4. Ethical conduct of the study ................................ ................................ .................. 37
11. MANAGEMENT AND R EPORTI NG OF ADVERSE EVENTS/ADVERSE
REACTI ONS ................................ ................................ ................................ ...................... 38
12. PL ANS FOR DI SSEM INATING AND COMMUNI CATING STUDY RESUL TS........ 38
13. REFERENCES ................................ ................................ ................................ .................. 39
14. LIST OF TABLES ................................ ................................ ................................ ............. 40
15. LIST OF FIGURES ................................ ................................ ................................ ........... 40
16. ANNEX 1. LIST OF STAND ALONE DOCUMEN TS................................ ................... 40
17. ANNEX 2. ADDITIO NAL INFORMATION ................................ ................................ ...40
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Page 6of 422. LIST OF ABBREVIATIONS
Abbreviation Definition
AE adverse event
ARI Acute Respiratory Infection
BMI body mass index
CAIR California Immunization Registry
CHIP Children’s Health Insurance Program
CI confidence interval
CLIA Clinical L aboratory Improvement Amendments of
1988
COPD Chronic Obstructive Pulmonary Disease
COVID -19 coronavirus Disease 2019
CSR Clinical Study Report
ED emergency department
EHR electronic health record
EUA Emergency Use Authorization
GEE generalized estimating equations
HCW health care worker
HR hazard ratio
ICD International Classification of Diseases
ICMJE International Committee of Medical Journal Editors
ICU Intensive Care Unit
IEC Independent Ethics Committee
IRB Institutional Review Board
KPSC Kaiser Permanente Southern California
LOS length of stay
LTCF long term care facility
mRNA modified ribonucleic acid
NIS non-interventional study
NLP Natural Language Processing
OR odds ratio
PCR polymerase chain reaction
PHI protected health information
RSV Respiratory Syncytial Virus
RT-PCR Reverse Transcriptase Pol ymerase Chain Reaction
SAE serious adverse event
SAP Statistical Analy sis Plan
SARS -CoV -2 Severe Acute Respiratory S yndrome Coronavirus 2
SAS Statistical Analy sis Software
SDIR San Diego Immunization Registry
SOC Standard of Care
TND test-negative design
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Page 7of 42Abbreviation Definition
US United States
VE vaccine effectiveness
WGS whole genome sequencing
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Page 8of 423.RESPONSIBLE PARTIES
Principal Investigator(s) of the Protocol
Nam e, degree(s) Job Title Affiliation Address
Sara Y. Tartof, PhD,
MPHResearch Scientist Department of Research
and Evaluation
Kaiser Permanente,
Southern California100 South Los Robles,
2nd Floor
Pasadena, CA 91101
USA
Heidi Fischer, PhD, MS Research Scientist Bio-
statisticianDepartment of Research
and Evaluation
Kaiser Permanente,
Southern California100 South Los Robles,
6th Floor
Pasadena, CA 91101
USA
Jeff Slezak, MS Research Scientist Bio-
statisticianDepartment of Research
and Evaluation
Kaiser Permanente,
Southern Califo rnia100 South Los Robles,
6th Floor
Pasadena, CA 91101
USA
Fred Angulo, DVM PhD Epidemiologist Medical Development
and Scientific/Clinical
Affairs, Pfizer Vaccines500 Arcola Rd, Col-
legeville, PA 19426
USA
John McLaughlin, PhD Epidemiologist Medical Development
and Scientific/Clinical
Affairs, Pfizer Vaccines500 Arcola Rd., Col-
legeville, PA 19426
USA
4.ABSTRACT
BNT162b2 is a modified RNA (mRNA) vaccine administered as 2 doses 21 day s apart that
encodes the full -length, membrane -anchored S gly coprotein of SARS -CoV -2 with two intro-
duced proline mutations to lock it in the prefusion conformation. It was co -developed b y Bi-
oNTech SE and Pfizer, Inc. The vaccine showed an acceptable safet y profile in a Phase 1/2
study1and was tolerable and demonstrated a 95% clinical efficacy >7 day s after the second
dose against COVID -19 in persons without current or prior SARS- CoV -2 infection in a
Phase 3 trial2. Pfizer -BioNTech COVID -19 Vaccine is auth orized for use under an Emer-
gency Use Authorization (EUA) for active immunization to prevent coronavirus disease 2019
(COVID -19) caused by severe acute respiratory syndrome coronavirus 2 (SARS -CoV -2) in
individuals 16 y ears of age and older. D ata confirmin g the effectiveness of the vaccine out-
side of the clinical setting are needed.
The primary objective of this study is to estimate the vaccine effectiveness (VE) of 2 -doses
of Pfizer’s BNT162b2 (fully vaccinated) vaccine against acute respiratory illness r equiring
hospitalization due to SARS -CoV -2 infection among KPSC members 16 years of age. Sec-
ondary and exploratory objectives will examine VE for 1 dose vaccination, at least 1 dose, as
well as against emergency department (ED) admission, specific varian ts and other popula-
tions of interest.
To assess VE, we propose a large retrospective database stud y using two parallel stud y de-
signs: a test -negative case -control design and a retrospective cohort design. The test- nega-
tive design (TND) will assess VE against COVID -19 hospitalization (primary endpoint) and
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Page 9of 42EDadmission. The retrospective cohort anal ysis will assess VE against COVID -19 hospitali-
zation (primary ), ICU admission, death, ED admission, and outpatient disease (with no sub-
sequent hospitalization within 14 day s). We will further conduc t additional analyses of VE
estimates by various patient characteristics and strain ty pe.
This study will be conducted at Kaiser Permanente Southern California (KPSC), an inte-
grated health care organization comprising one of the largest health insurance plans in the
US, a hospital system, and >7,600 phy sicians and 27,000 nurses located througho ut 9 coun-
ties of Southern California. For the TND, the study population will include all KPSC patients
16 years or older who are admitted to the hospital or present to the ED with acute respiratory
infection (ARI) after 14 December 2020 (date of first vacc inations at KPSC), and who re-
ceive a PCR test for SARS -CoV -2. For the Full Cohort Design, the study population will in-
clude all KPSC members as of 14 December 2020 (date of first Pfizer vaccination at KPSC)
aged 16 and older.
Vaccine exposure for both st udy designs include fully vaccinated ,defined as 2 doses of
BNT162b2 received with ≥7 day s between receipt of the 2nddose and the event date (e.g., ad-
mission) ;partially vaccinated ,defined as 1 dose (only ) of BNT162b2 received with ≥14 day s
between the re ceipt of the 1stdose and the event date ; and ever vaccinated ,defined as ≥1
dose of BNT162b2 received with ≥14days between the receipt of the 1stdose and the event
date. The unexposed group will include individuals with no record of COVID -19 vaccinatio n
at the time of the event and will serve as the reference group in all VE analy ses. All data will
be collected from KPSC electronic health records (EHRs) .
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Page 10of 425.AMENDMENTS AND UPDAT ES
None
6.MILESTONES
Milestone Planned date
Start of data collection 01April 2021
Final SAP 15May 2021
Interim Data Anal ysis/Report 1 30June 2021
Final Study Report on Primary Data Collection 30 Jul y 2022
Secondary and exploratory data collection 30July 2023
Final Clinical Study Report (CSR) 01January 2024
Submit Manuscript for Publication 15March2024
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Page 11of 427.RATIONALE AND BACKGR OUND
The outbreak of the 2019 novel coronavirus disease (COVID -19), which is caused b y severe
acute respiratory syndrome -related coronavirus 2 (SARS -CoV -2), is still apandemic threat to
global public health. Although the epicenter of the COVID -19 outbreak in December of 2019
was in Wuhan, China, the disease has spread to more than 200 countries with more than 117
million confirmed cases and 2. 6million confirmed deaths worldwide as of 09 March 2019. In
addition, essentially every one’s lives have been affected as a result of mandatory isolation
and quarantine measures. The ripple effect of the COVID- 19 outbreak has brought major
challenges to health sy stems across the wo rld and has had far -reaching impacts on the global
econom y. So far, public health experts have largely only been able to employ nonpharmaceu-
tical intervention strategies to mitigate and control the spread of the virus. Now that safe and
effective vaccines areavailable, further evaluation of their effectiveness outside of the clini-
cal trial setting are needed following their introduction into the general population.
BNT162b2 is a modified RNA vaccine recommended as 2 doses 21 day s apart that encodes
the ful l-length, membrane -anchored S gl ycoprotein of SARS -CoV -2 with two introduced
proline mutations to lock it in the prefusion conformation. It was co- developed by BioNTech
SE and Pfizer, I nc. The vaccine showed an acceptable safety profile in a Phase 1/2 study1. In
a Phase 3 trial, the vaccine was tolerable and demonstrated 95% efficacy >7 day s after sec-
ond dose against COVID -19 in persons without current or prior SARS- CoV -2 infection2.
The vaccine is currentl y authorized for used u nder an E mergency Use Authorization (EUA)
for active immunization to prevent coronavirus disease 2019 (COVID -19) caused by severe
acute respiratory syndrome coronavirus 2 (SARS -CoV -2) in individuals 16 y ears of age and
older and data confirming the effectiveness of the vaccine o utside of the clinical setting are
needed.
As such, this study will be conducted in Kaiser Permanente Southern California (KPSC) , a
large integrated healthcare organization with over 4.7 million members who comprise a soci-
oeconomicall y dive rse and broadly representative population that reflects of the racial/ethnic
groups living in Southern California. As of 23 February 2021 , KPSC has had over 441,000
COVID -19 cases and approximately 29,000 confirmed patients admitted to the hospital and
has vaccinated more than 311,000 individuals. KPSC has 2Regional Laboratories that pro-
cess COVID -19 and other specimens. The central reference laboratories receive more than
50,000 specimens per day from the local laboratories and perform over 29 million tests annu-
ally. All laboratories undergo routine qualit y checks to meet or surpass accrediting bod y
specifications.
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Page 12of 428.RESEARCH QUESTION AN D OBJECTIVES
The primary objective of the study is to estimate vaccine effectiveness (VE) of 2 doses of
Pfizer’s BNT162b2 vaccine (i.e., fully vaccinated) against acute respiratory illness (ARI) re-
quiring hospitalization due to SARS -CoV -2 infection among KPSC members16 years of age.
VE will be evaluated using a test-negative design (TND), including all KPSC patients 16 years
or older who are admitted to the hospital with acute respiratory infection (ARI) after 14 De-
cember 14 2020 (date of first vaccinations at KPSC), and who receive a PCR test for SARS -
CoV -2. Secondary and exploratory objectives will examine VE for 1 dose vaccination, at least
1 dose, as well as against ED admission, specific variants and other populations of interest.
Additionally , we will estimate VE using a full cohort design, including all KPSC members 16
years or older. Table 1and Table 2outline all primary , secondary and exploratory objectives
for the current study for the TND and full cohort designs, respectivel y. Additional sensitivity
analyses are not described below, but rather are outlined in the subsequent Analy sis section.
To assess VE, we propose a large retrospective database stud y using two parallel stud y de-
signs: a test -negative case -control design and a retrospective cohort design. The test- nega-
tive design (TND) will assess VE against COVID- 19 hospitalization (primary endpoint) and
EDadmission. The retrospective cohort anal ysis will assess VE against COVID -19 hospitali-
zation (primary ), ICU admission, death, ED admission, and outpatient disease (with no sub-
sequent hospitalization within 14 day s). We will further conduct additional analyses of VE
estimates by various patient characteristics and strain ty pe.
Table 1.TND Study Design Proposed Objectives
Test- Negative Design
Objectives Endpoints
Primary: Primary:
1.To estimate the effectiveness of 2 doses of
BNT162b2 (i.e., fully vaccinated) against
hospitalization for ARI due to SARS -CoV- 2
infection.VE calculated as 1 minus the odds ratio ( OR)com-
paring the odds of being fully vaccin ated (2 doses)
with BNT162b2 for hospitalized cases and controls,
multiplied by 100%.
Secondary: Secondary:
1.To estimate the effectiveness of 2 doses of
BNT162b2 (i.e., fully vaccinated) against
ED admission (without subsequent hospital-
ization) for ARI due to SARS -CoV- 2 infec-
tion.VE calculated as 1 minus the OR comparing the odds
of being fully vaccinated (2 doses) w ith BNT162b2
for ED cases and controls, multiplied by 100%.
2.To describe the effectiveness of only 1 dose
of BNT162b2 (i.e., partially vacc inated)
against hospitalization for ARI due to
SARS -CoV -2 infection.VE calculated as 1 minus the OR comparing the odds
of being partially vaccinated with BNT162b2 (only 1
dose) for hospitalized cases and controls, multiplied
by 100%.
3.To describe the effe ctiveness of only 1 dose
of BNT162b2 (i.e., partially vaccinated)
against ED admission (without subsequent VE calculated as 1 minus the OR comparing the odds
of being partially vaccinated with BNT162b2 (only 1
dose) for ED cases and controls, multiplied by 100%.
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Page 13of 42Table 1.TND Study Design Proposed Objectives
Test- Negative Design
hospitalization) for ARI due to SARS -CoV -
2 infection.
4.To describe the effectiveness of ≥1 dose of
BNT162b2 (i.e., ever vaccinated) against
hospitalization for ARI due to SARS -CoV- 2
infection.VE calculated as 1 minus the OR comparing the odds
of ever being vaccinated ( ≥1 dose) w ith BNT162b2
for hospitalized cases and controls, multiplied by
100%.
5.To describe the effectiveness of ≥1 dose of
BNT162b2 (i.e., ever vaccinated) against
ED admission (without subsequent hospital-
ization) for ARI due to SARS -CoV- 2 infec-
tion.VE calculated as 1 minus the OR comparing the odds
of ever being vaccinated ( ≥1 dose) w ith BNT162b2
for ED cases and controls, multiplied by 100%.
6.To further describe the effectiveness of
BNT162b2 against hospitalization and ED
admission stratified by prevalent or im-
portant viral strainsBNT162b2 VE estimates stratified by virus variant
(as determined by genome sequencing) and select de-
scriptive ana lyses described above
7.To evaluate the effectiveness of BNT162b2
against severe hospitalization -related out-
comes (e.g., ICU admission, mechanical
ventilation, and death)BNT162b2 VE estimates against severe outcomes in-
cluding ICU admission, mechanical vent ilation, and
death.
Tertiary/Exploratory: Tertiary/Exploratory:
1. Com pare VE of models stratified by rele-
vant vaccination phase time periods to un-
derstand how VE may change as vaccinated
patient risk profiles change over time.BNT162b2 VE estimates by vaccination phase
2.To estimate the effectiveness of 1, ≥1, or 2
doses of BNT162b2 (i.e., fully vaccinated)
against hospitalization or ED for ARI due to
SARS -CoV -2 infection.VE calculated as 1 minus the OR comparing the odds
of have 2, 1, or ≥1 doses of BN T162b2 for hospital-
ized and ED cases and controls, multiplied by 100%.
3.To further describe the effectiveness of
BNT162b2 against hospitalization and ED
admission stratified by various patient char-
acteristics ( e.g., age, sex , race/ethnicity ,
chronic medical conditions , history of SARS -
CoV -2 infection, long -term care facility resi-
dence, pregnancy status, and receipt of influ-
enza vaccine ).BNT162b2 VE estimates by age group
BNT162b2 VE estimates by sex
BNT162b2 VE estimates by presence of chronic medi-
cal conditions , history of SARS -CoV -2 infection, preg-
nancy status
BNT162b2 VE estimates by race/ethnicity
BNT162b2 VE estimates by receipt of influenza vac-
cine in the last year
BNT162b2 VE estimates among long -term care fa-
cility residents (hospital out come only)
BNT162b2 VE estimates by time since vaccination
BNT162b2 VE estimates by time between first and
second dose among those who received 2 doses
4.To describe the proportion of hospitalized
and ED patients with ARI where SARS -
CoV -2 was identified.Proportion of ARI hospitalizations where SARS -
CoV- 2 is identified.
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Page 14of 42Table 1.TND Study Design Proposed Objectives
Test- Negative Design
5.To summarize the proportion of patients
who receive 0, 1, or 2 doses of BNT162b2
among hospitalized and ED patients.
6. To summarize the time between admin-
istration of the first and second dose of
BNT162b2 among patients who received 2
doses
7.To summarize the time since vaccination
with BNT162b2 (most -recent dose) since
vaccinations at KPSC beganProportion of patients who receive 0, 1, and 2
doses of BNT162b2
Average and median time between receipt of the
first and second dose BNT162b2 among patients
who received tw o doses
Average and median time between 14 December
2020 and receipt of last dose among patients re-
ceiving BNT162b2
8. To describe demographic , clinical , and la-
boratory characteristics (i.e., viral strain)
and disease severity of any BNT162b2 vac-
cine failuresDescribe age, gender, race/ethnicity, clinical
characteristics, and severity (ICU admission,
ventilator, death) of any patients who received
BNT162b2 and test posit ive for SARS -CoV -2
9. To describe COVID -19 disease severity for
vaccinated and unvaccinated cases in the
TND designDescribe disease severity for vaccinated and un-
vaccinated cases (e.g., average hospital length of
stay ( LOS ), 30-day readm ission, the proport ion
requiring ICU admission or mechanical ventila-
tion, death)
Table 2.Full Cohort Study Design Proposed Objectives
Cohort Design
Objectives Endpoints
Primary: Primary:
1.To estimate the effectiveness of 2 doses of
BNT162b2 (i.e., fully vaccinated) against
hospitalization due to SARS -CoV- 2 infec-
tion.VE calculated as 1 minus the hazard ratio ( HR)
comparing the incidence of being fully vac-
cinated (2 doses) w ith BNT162b2 for hospitaliza-
tion due to SARS -CoV -2 infection and not, mul-
tiplied by 100%.
Secondary: Secondary:
1. To estimate the effectiveness of 2 doses of
BNT162b2 (i.e., fully vaccinated) against
ED admission (without subsequent hospital-
ization) ED admission due to SARS -CoV- 2
infection.VE calculated as 1 minus the HR comparing the inci-
dence of being fully vaccinated (2 doses) w ith
BNT162b2 for ED admission due to SARS -CoV- 2
infection and not, multiplied by 100%.
2.To estimate the effectiveness of 2 doses of
BNT162b2 (i.e., fully vaccinated) against
ICU admission due to SARS -CoV- 2 infec-
tionVE calculated as 1 minus the HR comparing the inci-
dence of being fully vaccinated (2 doses) w ith
BNT162b2 for ICU admission due to SARS -CoV -2
infection and not, multiplied by 100%.
3.To estimate the effectiveness of 2 doses of
BNT162b2 (i.e., fully vaccinated) against
death due to SARS -CoV -2 infectionVE calculated as 1 minus the HR comparing the inci-
dence of being fully vaccinated (2 doses) w ith
BNT162b2 for death due to SARS -CoV -2 infection
and not, multiplied by 100%.
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Page 15of 42Table 2.Full Cohort Study Design Proposed Objectives
Cohort Design
4.To estimate the effectiveness of 2 doses of
BNT162b2 (i.e., fully vaccinated) against
COVID -19 outpatient visits (without subse-
quent hospitalization within 14 days) due to
SARS -CoV -2 infectionVE calculated as 1 minus the HR comparing the inci-
dence of being fully vacc inated (2 doses) w ith
BNT162b2 for COVID- 19 outpatient visits (without
subsequent hospitalization within 14 days) due to
SARS -CoV -2 infection and not, multiplied by 100%.
5.To describe the effectiveness of only 1 dose
of BNT162b2 (i.e., partially vaccinated )
against hospitalization, ED admission , ICU
admission , death, and outpatient visits
(without subsequent hospitalization within
14 days) due to SARS -CoV -2 infection.VE calculated as 1 minus the HR comparing the inci-
dence of only 1 dose of BNT162b2 (i.e., partially
vaccinated) for hospitalization, ED visit, death, and
COVID -19 outpatient visits (without subsequent hos-
pitalization within 14 days) due to SARS -CoV -2 in-
fection and not, multiplied by 100%.
6.To describe the effectiveness of ≥1 dose of
BNT162b2 ( i.e., ever vaccinated) against
hospitalization, ICU admission , ED admis-
sion, death, and outpatient visits (without
subsequent hospitalization within 14 days)
due to SARS -CoV -2 infection.VE calculated as 1 minus the HR comparing the inci-
dence ≥1 dose of BN T162b2 (i.e., ever vaccinated)
for hospitalization, ED visit, death, and COVID -19
outpatient visits (without subsequent hospitalization
within 14 days) due to SARS -CoV- 2 infection and
not, multiplied by 100%.
Tertiary/Exploratory: Tertiary/Exploratory:
1. Com pare VE of models stratified by rele-
vant vaccination phase time periods to un-
derstand how VE may change as vaccinated
patient risk profiles change over time.BNT162b2 VE estimates by vaccination phase
2.To further describe the effectiveness of
BNT162b2 by durability of vaccine effec-
tiveness after receipt of 2 doses.VE calculated as 1 minus the HR comparing the inci-
dence of being fully vaccinated (2 doses) at various
timepoints from vaccination for all outcomes, multi-
plied by 100%.
3.To further d escribe the effectiveness of
BNT162b2 stratified by various patient
characteristics (e.g., age, sex, race/ethnicity ,
chronic medical conditions, history of SARS -
CoV -2 infection, long -term care facility resi-
dence, pregnancy status, and receipt of influ-
enza vaccine).BNT162b2 VE estimates by age group
BNT162b2 VE estimates by sex
BNT162b2 VE estimates by presence of chronic medi-
cal conditions, history of SARS -CoV -2 infection, preg-
nancy status
BNT162b2 VE estimates by race/ethnicity
BNT162b2 VE estimates by receipt of influenza vac-
cine in the last year
BNT162b2 VE estimates among long -term care fa-
cility residents (hospital outcome only)
BNT162b2 VE estimates by time since vaccination
BNT162b2 VE estimates by time between first and
second dose among those who received 2 doses
4.To summarize the proportion of patients who
receive 0, 1, or 2 doses of BNT162b2
5.To summarize the time betw een adm inistra-
tion of the first and second dose of
BNT162b2 among patients who received 2
doses
6.To summarize the time since vaccination
with BNT162b2 (most -recent dose) from
study enrollment Proportion of patients who receive 0, 1, and 2 doses
of BNT162b2
Average and median time between receipt of the first
and second dose BNT162b2 among patients wh o re-
ceived tw o doses
Average and median time between study enrollment
and receipt of last dose among patients receiving
BNT162b2
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Page 16of 42Table 2.Full Cohort Study Design Proposed Objectives
Cohort Design
7.Estimate overall incidence rates by vaccina-
tion status and by important demographic
and clinical characteristics Incidence by vaccination status, age, gender,
race/ethnicity, clinical characteristics outlined further
below .
8.To further describe the effectiveness of
BNT162b2 stratified by prevalent or im-
portant viral strainsBNT162b2 VE estimates stratified by virus variant
(as d etermined by genome sequencing) and all de-
scriptive analyses described above
9.To estimate the effectiveness of 2 doses of
BNT162b2 (i.e., fully vaccinated) against
death during hospitalization due to ARI due
to SARS -CoV -2 infectionVE calculated as 1 minus the HR comparing the inci-
dence of being fully vaccinated (2 doses) w ith
BNT162b2 for death during hospitalization due to
SARS -CoV -2 infection and not, multiplied by 100%.
9. RESEARCH METHODS
9.1.Research Setting
Kaiser Permanente Southern California (KPSC) is a large integrated healthcare delivery sys-
tem that covers more than 4.7 million members. KPSC comprises one of the largest health
insurance plans in the United States ( US), a hospital system, and >7,600 phy sicians and
27,000 nurses located throughout 9 co unties of Southern California. 15 medical centers and
234 medical offices comprise the KPSC clinical care setting. Kaiser Permanente Southern
California’s member population is socioeconomically diverse and broadl y representative of
the racial/ethnic groups living in Southern California . Our population represents > 260 eth-
nicities and > 150 languages spoken. As of December 2018, the majorit y of current members
are Hispanic or Latino (43%), followed b y White (35%), Asian/Pacific Islander (12%), Black
or Afric an American (9%), and Other (1%). Member retention is very high, with nearl y 90%
staying after 1 y ear, 78% remaining after 3 y ears, and 71% remaining after 5 y ears. Members
enroll through the Kaiser Foundation Health Plan for prepaid health care insurance, including
pharmaceutical benefits, through group plans, individual plans, Medicare, Medicaid, and
other low -income programs. As of December 2018, 22% of patients were enrolled through
Medicare or Medi -Cal and Children’s Health Insurance Program (CHIP ).
Our pre -paid s ystem is a strong incentive to receive care within KPSC and members rarel y
seek outside care. KPSC provides care across the entire spectrum of healthcare needs, from
outpatient, inpatient, ED, urgent care, specialty care, pharmacy , imaging, laboratory , virtual
care, health education classes, and other services for our members. When clinical services
sought outside of our s ystem are captured through claims reimbursement requests.
Each Kaiser Permanente Southern California member is assigned a unique medical record
number upon joining the health plan. This number is retained for life, irrespective of leaving
and rejoining the health plan. This unique number allows for the linkage of different com-
puter files containing clinical and administrative information. Kaiser Permanente HealthCon-
nect®, our comprehensive electronic health record, is one of the largest private electronic
health record s ystems in the world. Kaiser Permanente HealthConnect and our integrated
model securel y connect medical off ices and hospitals across the region, providing members,
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Page 17of 42physicians, and other authorized health care providers with online access to clinical infor-
mation. Kaiser Permanente HealthConnect is a customized version of the EPI C electronic
health record.
The sy stem integrates all aspects of care, including pharmacy and lab services, as well as ap-
pointments, registration, and billing. This information can be used for research purposes.
Trained research staff have access to Kaiser Permanente HealthConnect through the Kaiser
Permanente Regional Application Portal.
Regional Laboratories
The Sherman Way Regional Reference Laboratories is a clinical laboratory management s ys-
tem that interfaces with Kaiser Permanente’s medical centers and medical office buildings.
The central reference laboratory occupies more than 150,000 square feet of lab oratory space
and employ s more than 600 employ ees. Services include comprehensive chemistry , microbi-
ology , cellular pathology, cy togenetic testing, and anatomic pathology services based on
state-of-the-art instrumentation and methodologies.
The Chino Hills reference laboratory occupies more than 120,000 square feet of laboratory
space and employ s approximately 230 employ ees. Services cover specimen processing, in-
cluding send -outs, auto- chemistry , endocrinology , limited special chemistry , immunology ,
bacteriology , molecular microbiology , and histology .
The clinical laboratories located in the local medical centers and medical offices each rou-
tinely conduct 2,000 to 3,000 laboratory tests per day . The central reference laboratory re-
ceives more than 50,00 0 specimens per day from the local laboratories and performs over 29
million tests annually . All laboratories undergo routine quality checks to meet or surpass ac-
crediting bod y specifications.
The Regional Reference Laboratories are fully accredited by theCollege of American
Pathologists. They are licensed by the Department of Health and Human Services Centers
for Medicare and Medicaid Services under the Clinical Laboratory Improvement Amend-
ments (CLIA) of 1988, by the State of California Department of Pub lic Health to perform
clinical assay s, and b y the U.S. Food and Drug Administration Bureau of Biologics. They
are inspected b y the American Association of Blood Banks for handling of blood compo-
nents.
There is a dedicated Regional Laboratory Operations te am including management and Re-
search Associates that supports research and serves as the liaison between Research & Evalu-
ation and the Regional Laboratory .
COVID -19 at KPSC
As of 23February 2021 KPSC has had over 441,000 COVID- 19 cases and approximately
29,000 confirmed patients admitted to the hospital. We have vaccinated more than 311,000
individuals as of 23 February 2021 .
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Page 18of 42At KPSC, diagnostic testing for SARS -CoV -2 is offered free of charge with an order from a
KPSC phy sician. Prioritization for testing has evolved during the pandemic, with an empha-
sis on individuals with sy mptoms (particularl y high -risk groups) and prior to hospital admis-
sions or certain outpatient procedures. Testing is primarily conducted by reverse transcript ase
polymerase chain rea ction ( RT-PCR) of nasopharyngeal/oropharyngeal swabs on the Roche
cobas® 6800 and 8800 analy zers or nasal/orophary ngeal swabs on Hologic Panther® anal yz-
ers. A smaller number of Abbott I DNOW® point -of-care tests are conducted in limited set-
tings (e.g., obst etrics, pulmonary medicine, and infectious disease departments). Testing of
asymptomatic individuals is also available, leveraging e -visits to place tests orders. Imple-
mentation in November 2020 of saliva testing and a new COVID -19 laboratory with Thermo
Fisher Scientific Amplitude Solution instruments has increased testing capacity to approxi-
mately 46,000 tests per day .
9.2.Study design
This is a database onl y study of existing healthcare data, no patients will be activel y enrolled.
Vaccine exposure for both study designs include fully vaccinated, defined as 2 doses of
BNT162b2 received with ≥7 day s between receipt of the 2nddose and the event date (e.g., ad-
mission);partially vaccinated, defined as 1 dose (only ) of BNT162b2 received with ≥14 day s
between the receipt of the 1stdose and the event date; and ever vaccinated, defined as ≥1
dose of BNT162b2 received with ≥14days between the receipt of the 1stdose and the event
date. The unexposed group will include individuals with no record of COVID -19 vaccina tion
at the time of the event and will serve as the reference group in all VE analy ses. All data will
be collected from KPSC electronic health records (EHRs).
Study Design(s)
Test Negative Case -Control Design
A TND study design will be used to evaluate the primary objective of this study , to assess ef-
fectiveness of 2 doses of Pfizer COVI D vaccine > 7 day s after second dose against hospitali-
zation for ARI due to SARS -CoV -2 infection. I t will include all KPSC pati ents 16 years or
older who are admitted to the hospital with acute respiratory infection (ARI) after 14 Decem-
ber 2020 (date of first vaccinations at KPSC), and who receive a PCR test for SARS -CoV -2.
For secondary objectives estimating VE against ED admissi on, the TND will include KPSC
patients 16 y ears or older who present to the ED with acute respiratory infection (ARI) after
14 December 2020 andwho receive a PCR test for SARS -CoV -2. These populations will be
used to evaluate additional secondary and expl oratory objectives outlined in Table 1 and
Table 2above, including VE of 1 dos e or ≥1 dose and VE for important virus variants.
The index date will be defined as the date of hospitalization or ED admission. Patients can
contribute more than one ARI event to the study if a subsequent ARI event for the same pa-
tient occurred >30 day s after the previous event.
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Page 19of 42Per KPSC clinical protocol, we expect that ED patients with ARI will be tested for COVID -
19, and in the inpatient setting, all patients with or without ARI will get tested for COVID-19
(to be confirmed with preliminary data). VE wi ll be estimated separatel y for prevention of
hospitalization (primary outcome) and for prevention of emergency department presentation
without hospitalization (secondary outcome).
Full Cohort Design
A full cohort design will be used for secondary objective s to further explore BNT162b2 VE
in the KPSC population. The cohort stud y will include all KPSC members as of 14 December
2020 (date of first Pfizer vaccination at KPSC) who are age 16 and older. The exposure will
be receipt of Pfizer’s COVID- 19 vaccine, w ith separate relative VEs estimated for those with
2 doses, 1 dose, or ≥1 dose as in the TND design above. In this full cohort design, a patient’s
vaccination status, and thus exposure, will change over time, with all patients entering the co-
hort as unvac cinated. The outcomes of interest will be COVID -19 associated hospitalization,
ED admission, I CU admission, death, and outpatient COVI D-19 diagnoses (without subse-
quent hospitalization within 14 day s). As with the TND, the main outcome of interest will
be hospitalization, and the VE of focus will be 2 doses of BNT162b2. The full cohort anal y-
sis will serve as a secondary anal ysis and will allow for comparability with TND study meth-
odology . Cohort members will be censored if they disenroll from KPSC, die for reasons not
related to COVID -19 (death not within the 30 days following a positive COVID -19 labora-
tory test), receive an y other newl y licensed or investigational COVID -19 vaccine or prophy -
lactic agent other than Pfizer’s COVID-19 vaccine, receive >2 Pf izer COVID -19 vaccine
doses, experience an outcome <14 day s after receipt of the 1stPfizer COVID -19 dose, or ex-
perience an outcome <7 day s after receipt of the 2ndPfizer COVI D-19 dose.
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Page 20of 429.2.1. Inclusion criteria
Patients must meet all of the following inclus ion criteria to be eligible for inclusion in the
study :
Test Negative Design
1.KPSC patients 16 y ears or older who are admitted to the hospital (primary objective) with
acute respiratory infection (ARI ; ICD codes listed in Appendix Table 1 ) after 14 Decem-
ber 2020 (date of first vaccinations at KPSC), and who receive a PCR test for SARS -
CoV -2.
2.For secondary objectives estimating VE against ED admission, the TND will include
KPSC patients 16 y ears or older who present to the ED with ARI after 14 December
2020 ,and who receive a PCR test for SARS -CoV -2.
3. We will include membership requirement of 6 months prior to index date, which is de-
fined as the date of hospitalization or ED admission (allowing 31 -day administrative
gap), to facilitate accurate capture of comorbid conditions.
Cohort Design
1.All KPSC members as of 14 December 2020 (date of first Pfizer vaccination at KPSC)
who are age 16 and older.
2.For the cohort study , patients must have at least 6 months of membership (allowing 31 -
day administrative gap) prior to 14 December 2020 (index date, date vaccinations first
began at KPSC) to facilitate accurate capture of comorbid conditions.
9.2.2. Exclusion cri teria
Patient s meeting any of the following criteria will not be included in the study :
Test Negative Design
Patients who receive an y other newl y licensed or investigational SARS -CoV -2 vaccine or
COVID -19 proph ylactic agent other than Pfizer’s COVID -19 va ccine prior to hospitalization
(or ED, for secondary objective) will be excluded from the anal ysis. Patients will also be ex-
cluded if the index date is within certain time windows from vaccination date, outlined fur-
ther in the exposure section below.
Cohort Design
There will be no exclusion criteria for the cohort design, however patients will be censored
for receiving any other newly licensed or investigational SARS -CoV -2 vaccine or COVID -
19 prophy lactic agent other than Pfizer’s COVID- 19 vaccine . Patien ts will also be censored
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Page 21of 42if the event (hospitalization, ED encounter, etc.) occurs within certain time windows from
vaccination date, outlined further in the exposure section below.
9.3.Variables
9.3.1. Test Negative Design Outcomes and Exposures
Cases : Cases will be defined as those with an y positive KPSC laboratory -confirmed PCR test
from a sample collected within 14 days prior to hospital admission through 3 day s after a
hospital admission (primary objective) or ED encounter (secondary objective) with an ARI
code ( Appendix Table 1 ).
Controls: Controls will be defined as those with laboratory confirmed negative COVID-19
(negative COVID -19 test during first 3 day s of hospitalization for primary objective or ED
admission for secondar y objective and no positive COVID- 19 tests within 30 day s prior to
encounter).
Exposure Definition: The exposure of interest is history of vaccination with BNT162b2. For
the primary objective, patients will be considered vaccinated if they have documented evi-
dence of receiving the second dose of BNT162b2 ≥7 day s before index date (i.e., defined as
the date of hospitalization or ED admission). When evaluating the effectiveness of 1dose of
BNT162b2, patients will be considered vaccinated if they have documented evidence of re-
ceiving the first dose of BNT162b2 ≥14 day s before index date. Four levels of exposure vari-
able will be assessed:
1.Fully vaccinated defined as 2 doses of BNT162b 2 received with ≥7 day s between re-
ceipt of the 2nddose and the index date. This group will serve as the ‘exposed’ group
evaluated in the primary objective. Patients who received onl y 1 dose or 2 doses of
BNT162b2 with <7 day s between receipt of the 2nddose and the index date will be ex-
cluded from anal ysis.In sensitivity anal yses, VE will also be calculated for 2 doses of
BNT162b2 received with ≥14 day s between receipt of the 2nddose and the index date .
2.Partially vaccinated defined as 1 dose (onl y) of BNT162b2 received with ≥14 day s be-
tween receipt of the 1stdose and the index date . This group will serve as the ‘exposed’
group as a secondary endpoint. Patients who received 2 doses or 1 dose of BNT162b2
with <14 day s between receipt of the 1stdose and th e index date will be excluded from
analysis.
3.Ever vaccinated defined as ≥1 dose of BNT162b2 received with ≥14days between in-
dex date and receipt of the 1st dose. Patients who received 1 dose of BNT162b2 received
with <14 days between receipt of the 1stdose and the index date will be excluded from
analysis
4.Never vaccinated defined as never received BNT162b2. This group will serve as the ref-
erence exposure group (i.e., ‘unexposed’ group) in all VE anal yses.
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Page 22of 42The fully vaccinated (2 dose) exposure group will be considered for the primary objective,
while the partiall y (1 dose) and ever vaccinated ( ≥1 dose) groups will be considered in sec-
ondary objectives.
9.3.2. Full Cohort Design Outcome and Exposures
Main outcome
The main outcome of interest will be COVID -19 hospitalization, which will be defined as a
hospitalization with a positive PCR SARS -CoV -2 test within 14 day s prior and 3 day s after
admission date.
Other outcomes of interest
COVID -19 ICU will be defined as time spent in an intensive care/critical care unit during a
hospital stay with COVID -19 admit as defined above.
COVID -19 ED encounter, which will be defined as an ED encounter with a positive PCR
SARS -CoV -2 test within 14 day s prior and 3 day s after encounter.
COVID -19 death will be defined as death wi thin the 30 day s following a positive COVI D-19
laboratory test. Due to lags in compiling cause of death data in our databases, we will not
have cause of death data in time for the study .
Death during hospitalization will also be assessed.
Laboratory -confirmed SARS -CoV -2 infection identified in the outpatient setting, without a
hospitalization in the subsequent 14 days.
Exposures of interest: The exposure will be receipt of Pfizer’s COVID- 19 vaccine, with sep-
arate relative VEs estimated for those full y (2 dose), partiall y (1 dose), or ever vaccinated ( ≥1
dose) as in the TND design above. In this full cohort design, a patient’s vaccination status,
and thus exposure, will change over time, so VE will be estimated using time -varying expo-
sures, explained in further detail below.
Partially and Fully Vaccinated: Partial (1 dose) and full (2 dose) vaccination VE will be esti-
mated using time -varying exposures, with patients initially entering the cohort as unvac-
cinated, then contributing person time to the partia l and fully vaccinated exposure groups as
they are receiv ing the vaccine over time in the real- world setting. Specifically , a patient will
move to the 1 -dose exposure group once 14 -days have passed following the first dose, and
then to the 2 -dose exposure group once 7- days have passed following the second dose. If a
patient experiences an event within 14 day s of the first dose, or 7 day s within the second
dose, he or she will be censored at that time. No requirements on the timing between doses
will be applied.
To explore VE durability after 2 doses, secondary models will further refine the exposure
categories to include time since receipt of dose 2. As in the main anal ysis, patients will still
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Page 23of 42enter the cohort as unvaccinated on 14 December 2020 (date offirst vaccinations at KPSC)
and will move from unexposed to the partial and full vaccinated exposure groups as they are
vaccinated over time. Once the second dose is received, we will then code exposure catego-
ries as, for example, 1- 29 day s, 30 -89 day s, 90- 180 day s, 180 -364, and ≥365 day s since re-
ceipt of dose 2. Each patient will contribute person time to these groups as the allotted
amount of time passes since their second dose. This will allow us to analy ze the relative VE
during those different time pe riods and explore VE durability . If sample size allows, we will
conduct a similar analy sis looking at only 1dose, where patients will be censored from the
analyses when they receive their second dose. To inform our decisions in choice of cut
points for both dose models, we will also estimate changes in relative VE continuously over
time by modeling time since vaccination using restricted cubic splines.
Ever Vaccinated: Relative VE for the Ever Vaccinated ( ≥1 dose) group will be estimated in a
separate a nalysis also using time vary ing exposures. Patients will again enter the cohort as
unvaccinated, then contributing person time to the ever-vaccinated group after receiving dose
1. They will remain in this exposure group regardless of receipt of the 2nddose of the Pfizer
COVID -19 vaccine.
Unexposed: I ndividuals with no record of BNT162b2 COVID -19 vaccination.
9.3.3. Test-Negative and Full Cohort Designs – Outside Vaccinations
To obtain information about vaccination that occurs outside of the KPSC healthca re sy stem,
we will also take advantage of the recent partnership KPSC established with 7 national phar-
macy chains as well as data exchange with the California I mmunization Registry (CAIR).
This partnership allows for KPSC members to receive influenza and o ther vaccines outside
of KPSC pharmacies. Starting 30 December 2020, a bidirectional data exchange was estab-
lished with CAI R, thereby allowing us to capture vaccinations received outside of KPSC.
CAIR bidirectionality brings together a partnership between electronic medical records, the
public health department, and pharmacies. Doses administered outside of KPSC are cur-
rently being recorded in the electronic health record as, for example, “Covid -19 vaccine,
Pfizer, external administration.”
One exception to this is that immunization data for San Diego patients is reported into the
San Diego Immunization Registry (SDIR), not CAI R. Because SDI R does not currentl y pro-
vide data to CAI R, complete immunization information for San Diego patients is not y et
availa ble via KP HealthConnect. However, providers can do a manual query in SDIR to up-
date member immunization records.
In California, COVID -19 vaccination providers are required to report COVID -19 doses ad-
ministered within 24 hours of administration to their lo cal immunization registry .
To verify our exposure data, we propose a validation study nested in the larger cohort study
to survey a random sample of patients in the ‘non- vaccinated’ population to confirm data
capture in the KPSC EHR (separate protocol).
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Page 24of 429.3.4. T est-Negative and Full Cohort Designs - Covariates
We will consider individual- level and neighborhood-level factors listed in the Table 3 below.
These are factors that w e have either found to be important covariates in previous work, have
been identified in other risk factor literature, or are variables that may be associated with the
exposure as well as outcome (i.e. prior positive SARS -CoV -2 PCR test, etc.)3-8. We will also
include calendar week as a covariate in our models to adjust for phase in vaccine rollout, test-
ing practice changes, social distancing impacts, surges, and potential changes in clinical
treatments.
Table 3. Factors to be considered in models
Dem ographics Com orbidities Care utiliza-
tion prior to
testNeighborhood
characteristicsCOVID -his-
toryIndividual risk
indicators
Age Cardiac disease Outpatient en-
countersPopulation den-
sityPrior negative
PCR testsHealth care
worker ( HCW )
/ occupation
Sex Organ trans-
plantInpatient en-
countersMedian income Prior positive
PCR testsLong -term care
resident
Race/ethnicity Diabetes with
A1CED encounters Neighborhood
deprivation in-
dexPrior negative
serology testsMedical Center
Chronic Ob-
structive Pul-
monary Disease
(COPD )Influenza vac-
cinationEducation Prior positive
serology tests
Renal disease Pneumococcal
vaccination
Body mass in-
dex ( BMI )
Malignancy
Hypertension
Charlson Index
Sedentary vs.
Active
9.4.Data sources
All data will be collected from KPSC electronic health records. This is a database analy sis
study of existing healthcare data; no patients will be activel y enrolled. We will collect data
including vaccination status and dates of vaccination, COVID- 19 testing and outcomes,
comorbidities, prior healthcare utilization, other vaccinations, demographic data, and other
data from the EH R.
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Page 25of 42All data for research are subjected to a number of quality checks. The programming teams
perform range and consistency checks for all data to be evaluated. These might include event
dates after death, procedures coded at facilities that don’t perform them, outly ing laboratory
values, and other evaluations. All study data are presented in team meetings on at least a
weekl y basis and further examinations for potential errors are made b y the scientists and bio-
statisticians. I n addition, at both sites ther e are a number of standard algorithms in place that
will be used to further subject the data to qualit y control procedures. Aberrant data will be
examined to determine if they are due to programming errors, and efforts to resolve s ystem-
atic problems that l ead to errors will occur as soon as possible after they are discovered and
will continue until resolution. These quality control procedures will be documented, provid-
ing an auditable trail.
Once all necessary data from KPSC have been pulled and have under gone robust quality con-
trol measures, the databases will be frozen and archival copies of each separate dataset will
be made. Continuous data quality assurance and improvement are a top priority . The team
will be prompt in responding to an y data quality in quiries from Pfizer if and when an y issues
are discovered.
All programming and analy ses will be conducted using SAS statistical software, version 9·4
(Cary , NC), and R (R Core Team 2019, version 3.6.0).
9.5.Study size
The TND anal ysis will be event -driven bas ed on the number of cases identified. Study sam-
ple size is based on the primary endpoint (BNT162b2 VE against ARI requiring hospitaliza-
tion where SARS -CoV -2 is identified in the TND study ). The required sample size will de-
pend primaril y on i) the proportion of all -cause ARI requiring hospitalization caused b y
SARS -CoV -2 (which determines the number of cases identified and the ratio of cases to con-
trols in the primary anal ysis), ii) the average uptake of BNT162b2 in the study population
over the duration of the study , and iii) the assumed VE of the specific COVID- 19 vaccine
against ARI requiring hospitalization where SARS- CoV -2 is identified. Sample size calcula-
tions were based on the following fixed assumptions:
Two-sided, t ype-I error of 5%
1.90% power
2.Log(OR) following approximated normal distribution
3.Assumed true BNT162b2 VE vary ing from 70‒90% to prevent ARI requiring hospi-
talization was modeled
4.5% of all -cause ARI episodes requiring hospitalization will test positive for SARS -
CoV -2. A range of 5–30 % was a lso modeled given the attack rate of COVID -19 may
vary based on social distancing and shelter -in-place measures, underly ing levels of
population immunity , and other factors.
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Page 26of 42Average BNT162b2 vaccine uptake in controls over the study period was allowed to vary in
sample size calculations (range: 10 –90%) and will depend on potential future vaccination up-
take scenarios and timing of the conduct of the study . Final study enrollment size will also
depend on the proportion of enrolled patients excluded from t he Per Protocol Population be-
cause i) vaccination records could not be obtained, ii) they received a newly -licensed or in-
vestigational SARS -CoV -2 vaccine other than BNT162b2 vaccine, or iii) they received
BNT162b2 vaccine, but did not receive the full 2-do se schedule.
Table 4 presents sample size calculations for various scenarios of BNT162b2 uptake and the
proportion of all -cause ARI where SARS -CoV -2 isidentified. Depending on the uptake of
BNT162b2 and the proportion of ARI hospitalizations where SARS -CoV -2 is identified at
the time of the study , approximately 3,000 to 12,000 persons ≥16 y ears of age will be needed
in the TND anal ysis. Our study team w ill monitor BNT162b2 uptake among controls and the
proportion of all -cause ARI where SARS -CoV -2 is identified to inform decisions on the sam-
ple size required to reach an effectiveness endpoint.
For the cohort design, analy sis will be performed at fixed ti me points after a specified dura-
tion of follow -up. Power to detect a given hazard ratio in a Cox model depends primarily on
the number of events observed during follow -up, but also varies with the degree of correla-
tion between the exposure of interest (va ccination) and the other covariates in the model.
Given that exposure at any given time may be highly correlated with age or comorbidities,
we allowed the correlation (r2) to vary from 0.1 to 0.5, while estimating a VE (1- HR) ranging
from 30% to 90%. The power table below shows the total number of events which would
need to be observed in the cohort to have 90% power at alpha level 0.05 to detect a given VE
at a given correlation between vaccine exposure and other covariates.
Table 4. Total number of events needed to provide 90% power to detect a given VE
Correlation of vaccine exposure with other covariates
VE (1 -HR) 0.1 0.3 0.5
90% 4 5 7
70% 13 17 23
50% 38 49 69
30% 144 185 259
Requirements for the final anal ysis population to detect BNT162b2 VE >20% assuming true
VE=70 ‒90% with 90% power and t ype-I error of 5% (2 -sided) under various BNT162b2 up-
take scenarios ( 5to 30% of ARI events requiring hospitalization due to SARS -CoV -2)
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Page 27of 42Table 5.COVID VE Sample Size
5% of ARI is SARS -CoV -2 positive 15% of ARI is SARS -CoV -2 positive 25% of ARI is SARS -CoV -2 positive 30% of ARI is SARS -CoV -2 positive
Assume true VE=70%
BNT162
UptakeCon-
trolscase
sTot
EvalTot En-
roll*Con-
trolscase
sTot
EvalTot En-
roll*Con-
trolscase
sTot
EvalTot En-
roll*Con-
trolscase
sTot
EvalTot En-
roll*
10 6769 356 7125 1187
52104 371 2475 4125 1171 390 1561 2602 938 402 1340 2233
20 3266 172 3438 5730 1022 180 1202 2003 573 191 764 1273 461 198 659 1098
30 2108 111 2219 3698 665 117 782 1303 377 126 503 838 304 130 434 723
40 1540 81 1621 2702 491 87 578 963 281 94 375 625 229 98 327 545
50 1213 64 1277 2128 392 69 461 768 228 76 304 507 187 80 267 445
60 1015 53 1068 1780 335 59 394 657 199 66 265 442 165 71 236 393
70 909 48 957 1595 308 54 362 603 187 62 249 415 157 67 224 373
80 905 48 953 1588 318 56 374 623 200 67 267 445 171 73 244 407
90 1174 62 1236 2060 435 77 512 853 287 96 383 638 251 108 359 598
Assume true VE=80%
BNT162
UptakeCon-
trolscase
sTot
EvalTot En-
roll*Con-
trolscase
sTot
EvalTot En-
roll*Con-
trolscase
sTot
EvalTot En-
roll*Con-
trolscase
sTot
EvalTot En-
roll*
10 4945 260 5205 8675 1518 268 1786 2977 832 277 1109 1848 661 283 944 1573
20 2325 122 2447 4078 717 127 844 1407 396 132 528 880 315 135 450 750
30 1455 77 1532 2553 452 80 532 887 252 84 336 560 201 86 287 478
40 1024 54 1078 1797 321 57 378 630 181 60 241 402 146 63 209 348
50 770 41 811 1352 245 43 288 480 140 47 187 312 114 49 163 272
60 608 32 640 1067 197 35 232 387 115 38 153 255 95 41 136 227
70 505 27 532 887 169 30 199 332 102 34 136 227 85 36 121 202
80 455 24 479 798 160 28 188 313 101 34 135 225 86 37 123 205
90 513 27 540 900 196 35 231 385 132 44 176 293 116 50 166 277
Assume true VE=90%
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Page 28of 42Table 5.COVID VE Sample Size
5% of ARI is SARS -CoV -2 positive 15% of ARI is SARS -CoV -2 positive 25% of ARI is SARS -CoV -2 positive 30% of ARI is SARS -CoV -2 positive
BNT162
UptakeCon-
trolscase
sTot
EvalTot En-
roll*Con-
trolscase
sTot
EvalTot En-
roll*Con-
trolscase
sTot
EvalTot En-
roll*Con-
trolscase
sTot
EvalTot En-
roll*
10 4275 225 4500 7500 1294 228 1522 2537 698 233 931 1552 549 235 784 1307
20 1955 103 2058 3430 594 105 699 1165 322 107 429 715 253 108 361 602
30 1183 62 1245 2075 361 64 425 708 197 66 263 438 155 66 221 368
40 798 42 840 1400 245 43 288 480 135 45 180 300 107 46 153 255
50 568 30 598 997 176 31 207 345 98 33 131 218 78 33 111 185
60 417 22 439 732 132 23 155 258 74 25 99 165 60 26 86 143
70 313 16 329 548 101 18 119 198 59 20 79 132 49 21 70 117
80 241 13 254 423 83 15 98 163 51 17 68 113 43 18 61 102
90 212 11 223 372 82 14 96 160 56 19 75 125 50 21 71 118
*Assumes 40% of enrolled participants will be unevaluable (i.e., excluded from the Per Protocol Population because i) vaccina tion records could not be ob-
tained, ii) they received a newly -licensed or investigational SARS -CoV- 2 vaccine othe r than COVID -19 vaccine , or iii) they received COVID -19 vaccine , but
did not receive the full 2 -dose schedule.
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Page 29of 429.6.Data management
Data management activities include sy stem operation and maintenance, security , data specifi-
cation, programming, systems and data validation, sequencing of operational steps and
events, quality assurance / quality control, and data backup.
Thestudy team will hold weekl y internal meetings with a primary goal surrounding quality
assurance. The meetings will be a platform for the programmers and anal ysts to report their
work in progress to the scientist team and to discuss any potential issues. K PSC will maintain
internal data management logs to track data management activities and important communi-
cation with internal personnel or Pfizer.
In general, we will rel y on our internal team meetings to manage tasks. Internal review pro-
cesses and team m eetings will be used to monitor performance. Meeting minutes, meeting
agendas, progress reports, meetings, e -mail, and calendar tools will be used to manage and
ensure qualit y of the project. We will use internal team meetings, e -mail, conference calls,
the website, and progress reports to communicate. We will develop a document in coordina-
tion with the sponsor that will list all deliverables and expected timelines for deliverables.
Tracking of project deliverables will be a standing item on meeting agendas .
Any problems or risks will be brought up at our regular internal team meetings and escalated
to Pfizer as needed. The leadership team will discuss solutions to problems and way s to miti-
gate risks. We will use e-mail and our progress reports to communica te proactively with
Pfizer regarding an y anticipated risks or barriers to the project.
Once the stud y has begun, if Pfizer changes timelines or increases the scope of the objec-
tives, we will examine all possible means to accommodate the changes within the existing
budget. If not, we will work closel y with Pfizer to adjust the budget, scope of work, and/or
timelines.
9.6.1. Electronic data records
All data will be collected from KPSC electronic health records. This is a database analy sis
study of existing healthcar e data; no patients will be activel y enrolled. Therefore, no case re-
port forms or data collection tools will be created and submitted to Pfizer. The investigator
shall ensure that the electronic data records are securely stored at the study site and will have
limited access. Patient- specific data will not be transferred or reported out to Pfizer. Aggre-
gate descriptive anal yses will be presented.
9.6.2. Record retention
The final database will be archived and retained in a password -protected location. To enable
evaluations and/or inspections/audits from regulatory authorities or Pfizer, records, including
the identity of all participating patients (sufficient information to link records, e.g., hospital
records), source documents, detailed records of treatment dis position, and adequate docu-
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Page 30of 42mentation of relevant correspondence (e.g., letters, meeting minutes, and telephone call re-
ports) will be maintained. The records will be retained by the investigator according to site
guidelines. The records will be stored secur ely for so long as they are retained.
If the investigator becomes unable for an y reason to continue to retain study records for the
required period (e.g., retirement, relocation), Pfizer will be prospectivel y notified. The study
records must be transferred to a designee acceptable to Pfizer, such as another investigator,
another institution, or to an independent third party arranged by Pfizer.
Study records will be kept for a minimum of 15 y ears after completion or discontinuation of
the study . The invest igator will obtain Pfizer's written permission before disposing of an y
records, even if retention requirements have been met.
9.7.Data analysis
Detailed methodology for summary and statistical anal yses of data collected in this study will
be documented in a Statistical Analysis Plan (SAP), which will be dated, filed and main-
tained by the sponsor. The SAP may modify the plans outlined in the protocol; any major
modifications of primary endpoint definitions or their anal yses would be reflected in a proto-
col ame ndment.
9.7.1. Test Negative Design Analyses
The anal yses below will be done separatel y for the primary population of hospitalized pa-
tients as well as the secondary population of patients with ED encounters. Patients will be in-
cluded in the anal yses regardless of prior COVID -19 infection status.
9.7.1.1. Descriptive Analyses
We will give the proportion of hospitalized and ED patients with ARI where SARS -CoV -2
was identified, as well as the proportion of patients who receive 0, 1, and 2 doses of
BNT162b2. We will provide the average and median time between receipt of the first and
second dose of BNT162b2 among patients who received 2 doses, well as between 14 Decem-
ber 2020 (beginning of vaccinations at KPSC) and receipt of last dose of BNT162b2. Finally ,
we will describe a ge, gender, race/ethnicit y, clinical characteristics, and severity (ICU admis-
sion, ventilator, death), and other characteristics described in Table 3above of an y patie nts
who received BNT162b2 and test positive for SARS- CoV -2.
9.7.1.2. Estimated Crude (Unadjusted) VE
Odds of having received BNT162b2 (fully, ever, and partiall y vaccinated) for cases and test-
negative controls will be constructed and compared using ORs and 95% confidence intervals
(CIs). VE will be calculated as 1−OR multiplied by 100%. Corresponding 95% CIs will be
calculated using the Wald method.
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Page 31of 429.7.1.3. Estimating Adjusted VE
In addition to constructing crude OR and VE estimates, logistic regression modeling to assess
BNT162b2 VE after adjustment for potentially confounding factors will be performed. With
the exception of variables determined to be of clinical importance, which will be included in
models regardless, variables described in 8.4.4 will be entered in the logistic regression model
in backward stepwise manner. Onl y variables that change the estimated OR for BNT162b2 b y
≥10% (i.e., confounder) will remain in the final VE model. A 2-sided alpha of .05 will be used
for logistic regression modelling. Corresponding 95% CIs will be calculated using the Wald
method. A generalized estimating equations ( GEE )estimator will be used with a robust sand-
wich variance estimator to account for clustering introduced by variables measured at the
neighborhood level. In addition to results from the final model, univariate VE results will be
presented for each independent variable that is assessed for potential confounding, as the re-
sults f rom a fully -adjusted model.
9.7.1.4. Sensitivity Analyses
1.It is possible that patients that present with a COVID -19-like illness or a COVID -19
diagnosis are not tested for SARS- CoV -2 within 3 day s of hospital admission but are
rather tested later in their hospital stay. If this were the case, we would want to ex-
pand the requirement of a COVID -19 diagnostic test bey ond 3 day s following admis-
sion. To investigate the possibility of late testing, we will present data on the distribu-
tion of COVID -19 tests at time since admission for those admitted for respiratory in-
fections. If we find that a meaningful number of patients are tested >3 day s after hos-
pital admission, we may include a sensitivity analy sis to examine VE without time re-
strictions on testing following admissi on.
2.Use and develop Natural Language Processing (NLP )algorithm to estimate actual
date of s ymptom onset of COVID -19 s ymptoms. Sy mptom onset will then be consid-
ered to define exposure status at the time of a qualify ing event (or to censor a patient
if the y experience an event before 14 -days after the first dose of 7 -days after the sec-
ond).
9.7.1.5. Exploratory analyses estimating VE for health care workers and other high risk
populations
We know that the vaccine roll- out is following a tiered strategy , for example , with healthcare
workers with direct patient contact being vaccinated first. The logic supporting tiered vaccine
eligibility is based on COVID -19 risk, with highest risk populations prioritized first. To ac-
count for differing risk profiles of vaccinated i ndividuals over time, we will account for cal-
endar week in our model. To explore whether controlling for calendar week is sufficient to
address possible biases in VE,we will explore three options:
1.Flag healthcare worker, or other sub -population status (gold standard).
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Page 32of 42This will require complete and reliable identification of healthcare worker or other sub -popu-
lation status, for example, long term care facility (LTCF )-resident , in the EHR. This is the
preferred approach.
Analy ses will then be stratified so that both cases and controls will come from the same sub -
population.
2.Explore and compare VE of models stratified by time periods.
KPSC documentation of the dates of transit ions between tiers will be used to create catego-
ries of vaccine distribution by time ( Healthcare works/L TCF residents onl y, 65+, etc .),
Using these categories, we will perform stratified analy ses for each phase in the vaccine
rollout and examine any diffe rences in relative VE between time strata.
3.If, through our anal yses in part 2 or as the result of additional clinical input, we
determine our inability to identify patients eligible for vaccination during certain
vaccination tiers will result in unobserve d confounding that will materiall y affect
the reliability of our VE estimates, we will limit VE anal yses to certain time peri-
ods of interest for which we know vaccinations were restricted to a particular tier
–in particular we may drop anal yses focused on the time period only healthcare
workers were vaccinated and focus on time periods were vaccination is more
widespread.
Other Additional Anal yses:
We will also perform the following analy ses:
Determine VE against hospitalization and ED admission (combine d).
Provide descriptive statistics and determine VE stratified by viral strains determined
to be important or prevalent based on sequencing anal yses.
Determine VE of BNT162b2 against hospitalization stratified by various patient char-
acteristics (e.g., age , sex, race/ethnicity , chronic medical conditions, pregnancy status,
receipt of influenza vaccine). See Table 1for full list of stratified anal yses.
Evaluate the effectiveness of BNT162b2 against severe hospitalization- related out-
comes (e.g., ICU admission, mechanical ventilation, and death).
Compare COVID -19 disease severit y between vaccinated and unvaccinated cases.
We may also consider the impact of co- infection s on anal yses. It is possible that agents other
than SARS -CoV -2 are the primary drivers causing ARI symptoms, while SARS -CoV -2 play s
a less acute role. We may explore this possibility with descriptive anal yses of the distribution
of COVID -19 cases with dia gnostic tests for other pathogens, and a sub -analy sis excluding
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Page 33of 42all patients with co -infecting respiratory (influenza or Respiratory Syncytial Virus [RSV ])
pathogens.
9.7.2. Full Cohort Design Analyses
As in the TND, we will include those with and without prior C OVID -19 diagnoses.
9.7.2.1. Descriptive Analyses
We will give the proportion of patients who receive 0, 1, and 2 doses of BNT162b2 across all
of KPSC during the study period. We will provide the average and median time between re-
ceipt of the first and second dose of BNT162b2 among patients who received 2 doses, as well
as between 14 December 2020 (index date for cohort study , beginning of vaccinations at
KPSC) and receipt of last dose of BNT162b2. Overall incidence of the outcomes of interest
will be calculated b y dividing the number of outcome cases by the total number of person -
years. We will also provide incidence estimates by age, gender, race/ethnicity , clinical char-
acteristics, and other characteristics described in Table 2and Table 3above. We will addi-
tionally explore changes in the clinical and demographic composition of the vaccinate d and
non-vaccinated population over time, as this will also change with vaccine phase integration.
Characteristics of those who test positive for COVID- 19 and those without COVI D-19 will
be presented.
9.7.2.2. Estimated Crude (Unadjusted) VE
VE will be estimated as 1 –[(incidence of outcome among vaccine recipients)/(incidence of
outcome among unvaccinated)]. The incidence rate ratio will be estimated using the hazard
ratio from the adjusted the Cox model, resulting in estimated VE = (1 –adjusted HR) *
100%. Co rresponding 95% CI s will be calculated. Vaccination status will be time -varying as
described previously in the Exposures section.
9.7.2.3. Estimating Adjusted VE
Adjusted hazard ratios (HRs) and 95% CIs will be estimated b y including age, sex, race, and
other cova riates listed in Table 3 in Cox proportional hazards regression models. Covariates
of clinical importance will be selected for the adjusted anal yses. To determine whether the
remaining covariates should be included in the final model, only variables that change the es-
timated HR fo r BNT162b2 by ≥10% (i.e., confounder) will remain in the final VE model.
We will control for calendar week in all models. Robust variance will be computed to ac-
count for clustering introduced b y neighborhood level variables. Vaccine effectiveness (VE)
willbe estimated as 1 –[(incidence of outcome among vaccine recipients)/(incidence of out-
come among unvaccinated)]. The incidence rate ratio will be estimated using the hazard ra-
tio from the adjusted the Cox model, resulting in estimated VE = (1 –adjusted HR) * 100%.
9.7.2.4. Sensitivity Analyses
Use and develop NL P algorithm to estimate actual date of s ymptom onset of COVID -19
symptoms. Sy mptom onset will then be considered to define exposure status at the time of a
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Page 34of 42qualify ing event (or to censor a patient if the y experience an event before 14 -days after the
first dose of 7 -days after the second).
9.7.2.5. Exploratory analyses estimating VE for health care workers and other high risk
populations
We know that the vaccine roll- out is following a tiered strategy , for example, with healthcare
workers with direct patient contact being vaccinated first. The logic supporting tiered vaccine
eligibility is based on COVID -19 risk, with highest risk populati ons prioritized first. To ac-
count for differing risk profiles of vaccinated individuals over time, we will account for cal-
endar week in our model. To explore whether controlling for calendar week is sufficient to
address possible biases in VE, we will exp lore three options:
Flag healthcare worker, or other sub -population status (gold standard).
oThis will require complete and reliable identification of healthcare worker or
other sub- population status, for example, L TCF resident, in the EHR. This is the
preferred approach.
oWe will then include an interaction term with healthcare worker and HRs used to
estimate VE, to determine if VE is meaningfull y different b y these categories.
Explore and compare VE of models by time periods.
oKPSC documentation of the d ates of transitions between tiers will be used to cre-
ate categories of vaccine distribution by time ( Healthcare works/L TCF residents
only, 65+, etc.),
oUsing these categories, we will perform stratified analy ses for each phase in the
vaccine rollout and ex amine an y differences in relative VE between time strata.
If, through our anal yses in part 2 or as the result of additional clinical input, we determine
our inability to identify patients eligible for vaccination during certain vaccination tiers
will resu lt in unobserved confounding that will materially affect the reliability of our VE
estimates, we will limit VE anal yses to certain time periods of interest for which we
know vaccinations were restricted to a particular tier –in particular we may drop anal yses
focused on the time period only healthcare workers were vaccinated and focus on time
periods were vaccination is more widespread.
9.7.3. Additional Analytic Elements for Test Negative and Full Cohort Design
Other Anal yses for Both Designs:
For cohort desi gn, p rovide descriptive statistics and determine VE stratified by viral
strains determined to be important or prevalent based on sequencing anal yses.
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Page 35of 42Determine VE of BNT162b2 stratified by various patient characteristics (e.g., age,
sex, chronic medical co nditions, receipt of influenza vaccine). Table 2has the full
list of proposed stratified anal yses.
Laboratory Identification of Viral Strains
Residual nasophary ngeal or other respiratory specimens tested for COVID- 19 as part of
standard of care (SOC) ,will be collected daily from the two regional laboratories that serve
the KPSC population. Specimens will be saved prior to being discarded for destruction.
Swabs will be retained at the study site frozen until such time as they are selected and sent
forvariant determination which may include PCR and/or whole genome sequencing (WGS).
WGS will occur for variants of interest, to identify circulating variants, and to assess VE
against specific viral strains.
Missing or Incomplete Data:
Based on extensive prior experience, we expect negligible or no missing data for de-
mographics, comorbidities, utilization, neighborhood characteristics (assessed through resi-
dential address data), COVID history , or societal- level factors. It is possible, however, that
we wi ll have missing data for occupation and LTCF variables. Regardless of missingness, we
will present counts and percentages of missing data for all variables. If we find that data for
variables included in the final models are highl y complete, we will procee d with complete
case anal yses. If there is a substantial amount of missing data (>10%) for any variables
deemed necessary to include in our final analy ses, sensitivity anal ysis will be performed us-
ing multiple imputation for missing covariates (under the a ssumption of missing at random)
to understand the impact of excluding patients with missing information in adjusted models.
Analysis Timings :
Prior to a final anal ysis, periodic interim anal yses may be undertaken to understand attributes
of emerging varian ts, to assess preliminary VE to respond to public health needs or to gauge
sample size. Due to the observational nature of the study , no alpha adjustment will be ap-
plied. Any interim anal yses will be described in the SAP.
9.8. Quality control
Data Quality Chec ks
Range checks and general frequency tables will be produced such that missing values, outli-
ers, and inappropriate or abnormal values will be identified. Comparisons between date of
birth, date of death, event dates and vaccination dates will be made. A ll data will be checked
for duplicate records.
A record of data quality problems and resolutions will be kept through documented meeting
minutes. All inconsistencies and/or data quality issues will be documented. Revisions will
be noted in order to capture the change made, the change date, identification of the individual
making the change, as well as noting an y further actions to be taken to identify and/or resolve
additional data quality problems of this ty pe.
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Page 36of 42Select programming will be reviewed b y a se cond programmer. A report will be created, list-
ing discrepancies, their causes, and an y action taken to resolve them. If there are discrepan-
cies due to a difference in the date on which the original and validation programs are run,
both programs may be ru n again on the same date as a means to eliminate this potential cause
of discrepancies.
Confidentiality of Data
Any research data containing subject protected health information (PHI) is confidential.
KPSC staff will not discuss research data with anyone other than KPSC personnel. Pfizer
will only have access to aggregate data; no PHI will be shared with Pfizer.
9.9. L imitations of the research methods
If essentiall y all vaccine recipients receive two doses, we would be limited to study ing the
effect of 1 dose onl y during the time between doses, which could result in insufficient power
to analy ze the effectiveness of 1dose. The ability to do certain stratified analy ses listed
above will also be limited by sample size and outcome rates in each of these groups.
Given the vaccine rollout to high-risk groups first and lower- risk groups later, the group who
receives the vacc ine initially may be significantly different from the comparison population.
In particular, HCW vaccinated during this period would primarily be compared to non- HCW.
While the rate of infection in HCW is largely driven by the rate of infection in the com mu-
nity 1, this discrepancy could result in a biased estimate. Any bias caused by HCW being
higher risk than the general population will tend to bias the estimate toward lower VE. We
will report E -values to quantify the impact of unmeasured confounding fa ctors. The E -value
is defined as the minimum strength of association on the risk ratio scale that an unmeasured
confounder would need to have with both the exposure and the outcome, conditional on the
measured covariates, to fully explain away a specific exposure -outcome association. We will
compare the E -value with covariate –outcome associations measured in concurrent literature
(if available) that may have had data on HCW, employ ment status, or other unmeasured con-
founders and additionally compare the E -value with covariate –outcome associations among
our measured covariates to determine if an y association is likely to reach its magnitude. If
we find it is not possible to overcome bias in earl y vaccine recipients using the TND or full
cohort approach, we will exclude the earl y time period from anal ysis and begin the cohort at
the time that a greater portion of the general public is able to receive the vaccine, resulting in
a cohort start date when later batches of Pfizer vaccine are available.
9.10. Other aspe cts
Not applicable.
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Page 37of 4210.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. S uch
measures will include omitting patient names or other directl y identifiable data (PHI) in an y
reports, publications, or other disclosures, except where required b y applicable laws.
The personal data will be stored at the study site in encry pted electr onic form and will be
password protected to ensure that only authorized study staff have access. The study site will
implement appropriate technical and organizational measures to ensure that the personal data
can be recovered in the event of disaster. In the event of a potential personal data breach, t he
study site shall be responsible for determining whether a personal data breach has in fact oc-
curred and, if so, providing breach notifications as required b y site and or/law.
To protect the rights and freedoms of natural persons with regard to the proce ssing of per-
sonal data, , when stud y data are compiled for transfer to Pfizer and other authorized parties,
patient names will be removed and will be replaced by a single, specific, numerical code,
based on a numbering s ystem defined b y Pfizer . All other identifiable data transferred to
Pfizer or other authorized parties will be identified by this single, patient -specific code. The
investigator site will maintain a confidential list of patients who participated in the study ,
linking each patient’s numeric al code to his or her actual identity . In case of data transfer,
Pfizer will maintain high standards of confidentiality and protection of patients’ personal data
consistent with the clinical study agreement and applicable privacy laws.
10.2. Patient consent
This is a nobservational database anal ysis study of existing healthcare data; no patients will
be activel y enrolled. As this study does not involve data subject to privacy laws according to
applicable legal requirements, obtaining informed consent from patie nts by Pfizer is not re-
quired. T he site will obtain a waiver for obtaining informed consent from the KPSC I RB.
10.3. Institutional R eview Board (IRB)/Independent Ethics Committee (IEC)
There must be prospective approval of the study protocol, protocol amendments, and other
relevant documents (e.g., informed consent forms if applicable or appropriate waiver for con-
sent) from the relevant IRBs/IECs. All correspondence with the IRB/IEC mus t be retained.
Copies of I RB/IEC approvals must be forwarded to Pfizer.
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.
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Page 38of 4211.MANAGEMENT AND REPOR TING OF ADVERSE EVEN TS/ADVERSE REAC-
TIONS
This study involves electronic health record data that exist as structured data by the time of
study start or a combination of existing structured data and unstruc tured data, which will be
converted to structured form during the implementation of the protocol solely b y 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 pos-
sible to link (i.e., identify a potential association 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, identifia ble reporter, a suspect product, and event) cannot be met .
12.PLANS FOR DISSEMINAT ING AND COMMUNICATING STUDY RESULTS
The Investigator will have primary responsibility for the expedient preparation, review and
submission of any manuscripts, abstracts, press r eleases or other publications detailing the
study ’s procedures or findings. The study team will follow the I nternational Committee of
Medical Journal Editors (ICMJE) criteria to determine authors, and all authors who meet
these criteria will be offered authorship. We anticipate that as a collaborative project, mem-
bers of each of the study organizations (KPSC and Pfizer) will participate. Each organization
will determine members that meet authorship criteria. An y publication will include a list of
investiga tors, with authors being determined in line with the I CMJE guidelines, as well as an
acknowledgement of roles of the study Sponsor and Funder(s).
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 infor-
mation which might influence the evaluation of the benefits and risks of a Pfizer product,
Pfizer should be informed immediately .
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Page 39of 4213.REFERENCES
1. Walsh EE, Frenck RW, Jr., Falsey AR, et al. Safety and I mmunogenicity of Two
RNA -Based Covid-19 Vaccine Candidates. N Engl J Med. 2020;383(25):2439-2450.
2. Polack FP, Thomas SJ, Kitchin N, et al. Safet y and Efficacy of the BNT162b2 mRNA
Covid -19 Vaccine. N Engl J Med. 2020;383(27) :2603 -2615.
3. Tartof SY, Qian L, Hong V, et al. Obesit y and Mortality Among Patients Diagnosed
With COVID -19: Results From an Integrated Health Care Organization. Ann Intern
Med. 2020;173(10):773 -781.
4. Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpa-
tients with COVI D-19 in Wuhan, China: a retrospective cohort study . Lancet.
2020;395(10229):1054- 1062.
5. Webb Hooper M, Napoles AM, Perez -Stable EJ. COVID -19 and Racial/Ethnic Dis-
parities. JAMA. 2020;323(24):2466-2467.
6. Petrilli CM, Jones SA, Yang J, et al. Factors associated with hospital admission and
critical illness among 5279 people with coronavirus disease 2019 in New York City :
prospective cohort study . BMJ. 2020;369:m1966.
7. Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Corona-
virus Disease 2019 (COVID -19) Outbreak in China: Summary of a Report of 72314
Cases From the Chinese Center for Disease Control and Prevention. JAMA.
2020;323(13):1239 -1242.
8. Centers for Disease Control and Prevention. COVID -19 and People with Certain
Medical Conditions. 2021; https://www.cdc.gov/coronavirus/2019 -ncov/need -extra -
precautions/people -with-medical -conditions.html . Accessed March 2, 2021.
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Page 40of 4214.LIST OF TABLES
Table 1. TND Study Design Proposed Objectives ................................ ................. 12
Table 2. Full Cohort Study Design Proposed Objectives ................................ .......14
Table 3. Factors to be considered in models ................................ ........................... 24
Table 4. Total number of events needed to provide 90% power to detect a
given VE ................................ ................................ ................................ ...26
Table 5. COVID VE Sample Size ................................ ................................ .......... 27
15.LIST OF FIGURES
None
16.ANNEX 1. LIST OF STAND ALONE DOCUMENTS
None
17.ANNEX 2. ADDITIONAL INFORMATION
Appendix Table 1: Acute Respiratory Infection Diagnosis codes (International Classification
of Diseases [ICD] codes)
ICD-10 code ICD-10 definition
J12.0 Adenoviral pneumonia
J12.1 Respiratory syncytial virus pneumonia
J12.2 Parainfluenza virus pneumonia
J12.81 Pneumonia due to SARS -associated coronavirus
J12.3 Human metapneumovirus pneumonia
J12.89 Other viral pneumonia
J12.9 Viral pneumonia, unspecified
J13 Pneumonia due to Streptococcus pneumoniae
J18.1 Lobar pneumonia, unspecified organism
J15.0 Pneumonia due to Klebsiella pneumoniae
J15.1 Pneumonia due to Pseudomonas
J14 Pneumonia due to Hemophilus influenzae
J15.4 Pneumonia due to other streptococci
J15.4 Pneumonia due to other streptococci
J15.3 Pneumonia due to streptococcus, group B
J15.4 Pneumonia due to other streptococci
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Page 41of 42ICD-10 code ICD-10 definition
J15.20 Pneumonia due to staphylococcus, unspecified
J15.211 Pneumonia due to Methicillin susceptible Staphylococcus aureus
J15.212 Pneumonia due to Methicillin resistant Staphylococcus aureus
J15.29 Pneumonia due to other staphylococcus
J15.8 Pneumonia due to other specified bacteria
J15.5 Pneumonia due to Escherichia coli
J15.6 Pneumonia due to other Gram -negative bacteria
A48.1 Legionnaires' disease
J15.8 Pneumonia due to other specified bacteria
J15.9 Unspecified bacterial pneumonia
J15.7 Pneumonia due to Mycoplasma pneumoniae
J16.0 Chlamydial pneumonia
J16.8 Pneumonia due to other specified infectious organisms
B25.0 Cytomegaloviral pneumonitis
A37.01 Whooping cough due to Bordetella pertussis with pneumonia
A37.11 Whooping cough due to Bordetella parapertussis with pneumonia
A37.81 Whooping cough due to other Bordetella species with pneumonia
A37. 91 Whooping cough, unspecified species with pneumonia
A22.1 Pulmonary anthrax
B44.0 Invasive pulmonary aspergillosis
J17 Pneumonia in diseases classified elsewhere
B77.81 Ascariasis pneumonia
J17 Pneumonia in diseases classified elsewhere
J18.0 Bronchopneumonia, unspecified organism
J18.8 Other pneumonia, unspecified organism
J18.9 Pneumonia, unspecified organism
J10.00 Influenza due to other identified influenza virus with unspecified type of pneu-
monia
J10.01 Influenza due to other identified influenza virus with the same other identified
influenza virus pneumonia
J10.08 Influenza due to other identified influenza virus with other specified pneumonia
J11.00 Influenza due to unidentified influenza virus with unspecified type of pneu monia
J11.08 Influenza due to unidentified influenza virus with specified pneumonia
J12.9 Viral pneumonia, unspecified
J10.1 Influenza due to other identified influenza virus with other respiratory manifes-
tations
J11.1 Influenza due to unidentified influenza virus with other respiratory manifesta-
tions
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Page 42of 42ICD-10 code ICD-10 definition
J10.2 Influenza due to other identified influenza virus with gastrointestinal manifesta-
tions
J10.81 Influenza due to other identified influenza virus with encephalopathy
J10.82 Influenza due to other identified influenza virus with myocarditis
J10.83 Influenza due to other identified influenza virus with otitis media
J10.89 Influenza due to other identified influenza virus with other manifestations
J11.2 Influenza due to unidentified influenza virus with gastrointestinal manifestations
J11.81 Influenza due to unidentified influenza virus with encephalopathy
J11.82 Influenza due to unidentified influenza virus with myocarditis
J11.83 Influenza due to unidentified influenza virus with otitis media
J11.89 Influenza due to unidentified influenza virus with other manifestations
J09.X1 Influenza due to identified novel influenza A virus with pneumonia
J09.X2 Influenza due to identified novel influenza A virus with other respiratory mani-
festations
J09.X3 Influenza due to identified novel influenza A virus with gastrointestinal manifes-
tations
J09.X9 Influenza due to identified novel influenza A virus with other manifestations
J10.08 Influenza due to other identified influenza virus with other specified pneumonia
J10.1 Influenza due to other identified influenza virus with other respiratory manifes-
tations
J09.X9 Influenza due to identified novel influenza A virus with other manifestations
J09.X1 Influenza due to identified novel influenza A virus with pneumonia
J09.X2 Influenza due to identified novel influenza A virus with other respiratory mani-
festations
J09.X3 Influenza due to identified novel influenza A virus with gastrointestinal manifes-
tations
J09.X9 Influenza due to ide ntified novel influenza A virus with other manifestations
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