Alison Rustagi

M.D., Ph.D

University of California, San Francisco

Assistant Professor

NLST (Learn more about this study)

NLST-972

Oct 18, 2022

Time Lag to Benefit: A Systematic Review and Meta-Analysis of Lung Cancer Screening Trials

Lung cancer is by and large the prevailing cause of cancer deaths in the United States. The American Cancer Society estimates that almost 25% of cancer deaths within the US stem from lung cancer. In a 2019 estimate based on data from the Institute for Health Metrics and Evaluation, tracheal, bronchus, and lung cancer were found to not only be the leading cause of cancer deaths worldwide, 2.04 million, but that deaths by lung cancer outnumber the second most common cause of cancer death, colon and rectum cancer, by nearly twice as many deaths. The World Cancer Research Fund estimates that in 2020 about 12.2% of all new cancer cases in the world were lung cancers, only superseded by breast cancer by 0.03%. Lung cancer death can be prevented by lung cancer screening (LCS) via annual low dose CT of the chest, based on the results of randomized controlled trials. However, as with many other screening measures there are risks that must be considered and weighed along with any potential benefits. LCS, like any screening test, must balance short-term harms (radiation, anxiety, false positive/negative tests, procedures to follow abnormal scan, procedural complications, overdiagnosis) against the potential to avert death years in the future. Further, the features that define eligibility for LCS – older age and heavy smoking history – also increase the risk of dying for reasons other than lung cancer (e.g., coronary artery disease). There is an urgent need to better define who is “healthy enough” to justify the short-term risks of LCS. Defining a lag time to benefit for the screening intervention will provide key information to quantify the life expectancy an individual would reasonably need to have, in order to justify these short-term harms. Similar meta-analyses of randomized trial data to estimate the time-lag-to-benefit for other preventive interventions (e.g., statin prescription) provide invaluable and unique information to inform clinical decision-making for older adults. Therefore, we propose to collect and analyze data in a systematic review and meta-analysis of LCS randomized trials from around the world to comprehensively estimate the lag time to benefit from lung cancer screening. Completion of this proposed study will have an impact on determining when it may be better for a patient to screen and when it may be more beneficial to focus on pre-existing health issues, given an estimate of when they would be able to benefit from the screening.

The studies found within the NIH’s Cancer Data Access System, particularly the PLCO, MLP, NLST, and LSS studies will prove to be a great resource in analysis of this issue. We have identified that these studies fit within the framework we will pool and quantitatively estimate an accurate lag time to benefit statistic which may be utilized in further refining of the lung cancer screening process and the decision making therein.