Personalized screening for lung cancer: the importance of co-existing chronic conditions to clinical practice and policy

Abstract / summary
Lung cancer is the leading cause of cancer death in the US and worldwide, largely because most
patients have advanced, incurable disease at the time of diagnosis. However, lung cancer
screening (LCS) with low-dose computed tomography (LDCT) has the potential to revolutionize
lung cancer outcomes through early detection. As LCS is disseminated into real-world settings
and populations, a key outstanding question is whether the benefits/harms ratio found in clinical
trials will apply to an older and sicker population. The basic conundrum facing LCS candidates is
that the single risk factor most strongly linked to lung cancer -- smoking history -- is also strongly
linked to morbidity and death from non-lung cancer causes (e.g. chronic obstructive pulmonary
disease emphysema), which limit life expectancy and increase risk of complications from
diagnostic or therapeutic procedures. The overarching goal of our proposed study is to precisely
characterize this vulnerable subpopulation with high comorbidity burden, quantifying for them the
benefits and harms of LCS to enable more informed decision-making by patients contemplating
LCS. Our study will help close this knowledge gap by leveraging real-world data to more fully
characterize this subpopulation of “marginal” LCS candidates, reducing the uncertainty currently
facing patients and providers. More specifically, we propose to leverage electronic health records
and claims data for patients ages 55-80 (n~34,039) undergoing annual screening with LDCT in
geographically diverse real-world settings from 2016-2022. We will then use these observational
data with validated models in the Cancer Intervention Simulation Network to simulate LCS
outcomes in the real-world US population. By generating previously unavailable real-world data
for use in validated simulation models, this proposal responds directly to calls to improve patient-
centered decision-making in LCS candidates for whom the net benefits of screening are currently
highly uncertain.

Grant Number: 5R01CA249506-05
NIH Institute/Center: NIH
Principal Investigator: Dejana Braithwaite