Skip to Main Content

An official website of the United States government

The utility of CT-based nodule characteristics and polygenic risk score in the setting of a lung cancer screening trial.

Principal Investigator
Name
Gerard Silvestri
Degrees
M.D., M.S.
Institution
Medical University of South Carolina
Position Title
Professor of Medicine
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-1201
Initial CDAS Request Approval
Mar 11, 2024
Title
The utility of CT-based nodule characteristics and polygenic risk score in the setting of a lung cancer screening trial.
Summary
Lung cancer screening, through annual computed tomography (CT), has been shown to reduce lung cancer mortality in randomised control trials. However, CT-based screening results in a high rate of positive scans (nodules) where the majority are benign. Preliminary analysis from the ACRIN arm of the NLST (Biospecimen arm N=10,054 subjects) has identified and validated a panel of 12 single nucleotide polymorphisms (SNPs) than are associated with lung cancer and 8 SNPs associated with chronic obstructive pulmonary disease (COPD). When the SNP genotypes are combined in a simple composite score (polygenic risk score, PRS), the PRS independently predicts who will get and die from lung cancer in combination with traditional risk factors. The question arises, “Does the PRS perform equally well in those with or without nodules identified during screening?”

Recent interest has turned to better distinguishing who will die from their lung cancer and how this affects their screening outcome after the first baseline scan. This allows the utility of adding nodule data, such as the number and size of lung nodules, during the screening process. We propose to (a) examine the relationship between the PRS and nodule characteristics, and (b) the predictive utility of the PRS in those with and without pulmonary nodules identified during screening.
Aims

Aim: This study aims to extend an existing study where clinical data and SNP data are available for analysis. The objective of this extended study is to examine the utility of adding nodule related data from the ACRIN Biospecimen study (N=10,054), to see if the 12 SNP score performs equally well in predicting who will develop and die from their lung cancer.

Methods: Firstly to compared the nodule data in those with and with lung cancer and those who did or did not die from lung cancer, to assess which nodule-related characteristics were most relevant. Second to then add the 12 SNP score data to assess any changes in (a) AUC characteristic for dying of lung cancer (total cohort), (b) the impact of the score on reclassifying subject by risk tertiles (% who are redistributed across tertiles), and (c) compare the outcomes according to screening arm with respect to absolute reduction in lung cancer deaths.

Summary: This study will examine nodule data from the ACRIN-Biospecimen substudy of the NLST and assess its utility in improving prediction of who develops and dies of lung cancer in the setting of a lung cancer screening trial.

Collaborators

Dr. Gerard Silvestri (Medical University of South Carolina)
Dr. Rob Young (University of Auckland)
Dr. Raewyn Hopkins (University of Auckland)
Dr. Kathryn Long (Medical University of South Carolina)
Dr. Ralph Ward (Medical University of South Carolina)
Dr. Fenghai Duan (Brown University)