Incidental Finding of Coronary Calcium (CAC) in National Lung Screening Trial participants: Its Distribution and Potential Implication
Principal Investigator
Name
Ilana Gareen
Degrees
Ph.D.
Institution
School of Public Health, Brown University
Position Title
Associated Professor
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-1129
Initial CDAS Request Approval
Sep 28, 2023
Title
Incidental Finding of Coronary Calcium (CAC) in National Lung Screening Trial participants: Its Distribution and Potential Implication
Summary
Study Design: This retrospective analysis will utilize the data set from LDCT arm of NLST, which includes a large cohort of individuals aged 55-74 years with a significant smoking history. The dataset provides baseline and follow-up data, including demographics, medical history (disease history and personal cancer history) smoking history, lung cancer status, patient’s survival status. Data on Coronary Calcium (CAC) status (binary categorical variable, present or absent) will be obtained from Professor Ilana Gareen at Brown University. Professor Gareen's data set with CAC will be merged with NLST data set based on patient ID.
b) Data Analysis: Descriptive statistics will be used to determine the incidence of CAC in the study population. Logistic regression models will be employed to assess the association between demographic characteristics and CAC incidence, while adjusting for other known risk factors such as smoking history, and comorbidities. Subgroup analyses will explore interactions between demographic characteristics and other risk factors.
To assess the association between CAC and Coronary Mortality: Cox proportional hazards regression models will be employed to assess the association between CAC and coronary mortality. Survival analysis will be conducted using the follow-up data. The primary outcome will be the occurrence of coronary mortality during the follow-up period. Hazard ratios (HRs) with corresponding 95% confidence intervals (CIs) will be calculated to estimate the strength of the association. The regression models will include covariates that are established contrary artery disease risk, including age, gender, smoking history, comorbidities (such as hypertension, diabetes, and hyperlipidemia), and other cardiovascular risk factors.
b) Data Analysis: Descriptive statistics will be used to determine the incidence of CAC in the study population. Logistic regression models will be employed to assess the association between demographic characteristics and CAC incidence, while adjusting for other known risk factors such as smoking history, and comorbidities. Subgroup analyses will explore interactions between demographic characteristics and other risk factors.
To assess the association between CAC and Coronary Mortality: Cox proportional hazards regression models will be employed to assess the association between CAC and coronary mortality. Survival analysis will be conducted using the follow-up data. The primary outcome will be the occurrence of coronary mortality during the follow-up period. Hazard ratios (HRs) with corresponding 95% confidence intervals (CIs) will be calculated to estimate the strength of the association. The regression models will include covariates that are established contrary artery disease risk, including age, gender, smoking history, comorbidities (such as hypertension, diabetes, and hyperlipidemia), and other cardiovascular risk factors.
Aims
Aim 1, We will investigate the risk factors associated with CAC detection at lung cancer screening. Covariates will be demographics, medical history, smoking and alcohol use.
Aim 2, We will determine if CAC is associated with cardiac mortality.
Collaborators
Fenghai Duan, School of Public Health, Brown University