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Principal Investigator: Donglin Zeng
Organization: UNIVERSITY OF MICHIGAN AT ANN ARBOR
Fiscal Year: 2024
Award: $396,020
Funding agency: National Heart Lung and Blood Institute
PROJECT SUMMARY
In epidemiological cohort studies, the onset of an asymptomatic disease (e.g., diabetes, hypertension, chronic
obstructive pulmonary disease, HIV infection, SARS-CoV-2 infection, cancer, or dementia) cannot be observed
directly but rather is known to occur sometime between two consecutive clinical examinations. The two examina-
tions bookend a time interval, such that the event time is “interval-censored”. It is highly challenging to analyze
interval-censored data because none of the event times is exactly known; therefore, investigators have resorted
to statistical methods that are unreliable or even invalid. The broad, long-term objectives of this research project
are to develop semiparametric regression models, with associated inference procedures and numerical algo-
rithms, for analyzing interval-censored data from current epidemiological investigations. The specific aims of the
project are: (1) to explore semiparametric regression models for assessing the impact of an interval-censored
event (e.g., onset of diabetes) on future outcomes (e.g., stroke, heart attack, methylation level); (2) to build a
system of proportional intensity models with random effects for analyzing interval-censored multi-state processes
that characterize disease progression over time; (3) to provide graphical and numerical techniques for checking
the adequacy of semiparametric regression models with interval-censored data; and (4) to relax the proportional
hazards assumption by allowing time-varying regression coefficients. All of these aims are motivated by the
unmet methodological needs in the cohort studies that the investigators are currently conducting and address
the most timely and important issues in human population health research. The estimation of model parame-
ters is based on nonparametric likelihood (with an arbitrary event-time distribution) and other sound statistical
principles. The large-sample properties of the estimators will be established rigorously through innovative use
of modern empirical process theory, semiparametric efficiency theory, and other advanced mathematical argu-
ments. Computationally efficient and stable algorithms will be created to implement the inference procedures.
The operating characteristics of the numerical algorithms and inference procedures will be evaluated extensively
through simulation studies that mimic real data. The proposed methods will be applied to the Atherosclerosis Risk
in Communities Study and the SubPopulations and InteRmediate Outcome Measures In COPD Study, both of
which are being carried out at the University of North Carolina at Chapel Hill. These studies exemplify the broad
challenges and opportunities arising from modern epidemiological research. The results will be published in both
statistical and medical journals. Efficient, reliable, user-friendly, open-access, and well-documented R packages
will be produced and disseminated to the broad scientific community. This research will create new paradigms
in survival analysis, advance population health research in the United States and elsewhere, and accelerate the
search for effective strategies to prevent and treat many diseases of critical importance to public health, including
cardiovascular disease, lung disease, diabetes, cancer, HIV/AIDS, and dementia.
Terms: <AIDS/HIV><Acceleration><Active Follow-up><Address><Algorithms><Amentia><Apoplexy><Atherosclerosis Risk in Communities><Brain Vascular Accident><COPD><COVID-19><COVID-19 infection><COVID-19 virus infection><COVID19 infection><CV-19><Cancers><Cardiac Diseases><Cardiac Disorders><Cardiac infarction><Cardiovascular Diseases><Cerebral Stroke><Cerebrovascular Apoplexy><Cerebrovascular Stroke><Cessation of life><Characteristics><Chronic Obstruction Pulmonary Disease><Chronic Obstructive Lung Disease><Chronic Obstructive Pulmonary Disease><Cohort Studies><Communities><Computer software><Concurrent Studies><Coronavirus Infectious Disease 2019><Cox Models><Cox Proportional Hazards Models><Data><Data Set><Death><Dementia><Diabetes Mellitus><Disease><Disease Progression><Disorder><Documentation><Epidemiologic Research><Epidemiologic Studies><Epidemiological Studies><Epidemiological data><Epidemiology><Epidemiology Research><Epidemiology data><Equation><Event><Future><Gills><Goals><HIV Infections><HIV/AIDS><HTLV-III Infections><HTLV-III-LAV Infections><Heart Diseases><Human><Human T-Lymphotropic Virus Type III Infections><Hypertension><Infection><Intervention><Intervention Strategies><Investigators><Journals><Life><Likelihood Functions><Link><Lung Diseases><Magazine><Malignant Neoplasms><Malignant Tumor><Math><Mathematics><Maximum Likelihood Estimate><Medical><Methodology><Methods><Methylation><Modeling><Modern Man><Modernization><Monte Carlo Method><Monte Carlo algorithm><Monte Carlo calculation><Monte Carlo procedure><Monte Carlo simulation><Myocardial Infarct><Myocardial Infarction><Normalcy><Normalities><North Carolina><Outcome><Outcome Measure><Participant><Periodicals><Preventative strategy><Prevention strategy><Preventive strategy><Probability><Procedures><Process><Property><Proportional Hazards Models><Public Health><Publishing><Pulmonary Diseases><Pulmonary Disorder><R-Series Research Projects><R01 Mechanism><R01 Program><Regression Analyses><Regression Analysis><Regression Diagnostics><Relaxation><Research><Research Grants><Research Personnel><Research Project Grants><Research Projects><Researchers><Resort><SARS-CoV-2 infection><SARS-CoV2 infection><Sampling><Severe acute respiratory syndrome coronavirus 2 infection><Software><Statistical Methods><Statistical Regression><Stochastic Processes><Stroke><Survival Analyses><Survival Analysis><System><Techniques><Time><United States><Universities><Vascular Hypertensive Disease><Vascular Hypertensive Disorder><Work><absorption><active followup><brain attack><cardiac infarct><cardiovascular disorder><cerebral vascular accident><cerebrovascular accident><chronic obstructive pulmonary disorder><clinical exam><clinical examination><coronary attack><coronary infarct><coronary infarction><coronavirus disease 2019><coronavirus disease 2019 infection><coronavirus disease-19><coronavirus infectious disease-19><diabetes><disease of the lung><disorder of the lung><effective intervention><epidemiologic><epidemiologic data><epidemiologic investigation><epidemiological><epidemiology study><expectation><experience><follow up><follow-up><followed up><followup><hazard><heart attack><heart disorder><heart infarct><heart infarction><high blood pressure><high dimensionality><hyperpiesia><hyperpiesis><hypertensive disease><hypertensive disorder><infected with COVID-19><infected with COVID19><infected with SARS-CoV-2><infected with SARS-CoV2><infected with coronavirus disease 2019><infected with severe acute respiratory syndrome coronavirus 2><innovate><innovation><innovative><interest><interventional strategy><lung disorder><malignancy><measurable outcome><neoplasm/cancer><normality><novel><outcome measurement><periodic><periodical><population health><prevent><preventing><primary outcome><semiparametric><simulation><sound><statistic methods><stochastic method><stroked><strokes><theories><time interval><tool><user-friendly>