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What does the National Lung Cancer Screening Trial imply for the effectiveness of computerized tomography screening in the US population?

Principal Investigator
Name
Issa Dahabreh
Degrees
MD, ScD
Institution
Harvard University
Position Title
Associate Professor
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-983
Initial CDAS Request Approval
Nov 2, 2022
Title
What does the National Lung Cancer Screening Trial imply for the effectiveness of computerized tomography screening in the US population?
Summary
Compared to the general United States target population eligible for screening, participants in the National Lung Cancer Screening Trial (NLST) are younger, healthier, more educated, and more adherent to screening recommendations. The NLST on its own is insufficient to answer questions about the effectiveness of lung cancer screening in diverse clinical settings. Therefore, combining the NLST with other complementary sources of data, such as survey sampling studies (e.g., NHIS), along with methods we have developed for transporting and generalizing results to new target populations is necessary to critically evaluate screening strategies to reduce cancer mortality.

The overall aim of this project is to answer the question of: What does the NLST imply for effectiveness of computerized tomography screening in a nationally representative US population? We will first explore this by generalizing results from the NLST to nationally representative populations by leveraging survey data.
Aims

Estimate the effect of lung cancer screening in representative US target populations. This requires individual-level baseline data and mortality information from the NLST, along with baseline data from representative US target populations, which is available from survey data. We will estimate the absolute and relative rates, rate differences, and ratios for lung-cancer and all-cause mortality at a median follow-up of 6.5 years using methods we have developing for transporting effects from a trial to a target population.

Collaborators

Sarah Robertson, Harvard University

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