What question did this study set out to answer?

To assess the effectiveness of various smoking metrics in predicting survival outcomes in non-small cell lung cancer.

March 23, 2026Cancer Epidemiology0 citationsOpen Access

Evaluating eight smoking metrics for modelling survival in non-small cell lung cancer

ALAndrew CL Lam YLYao Ting Li MBM.Catherine Brown

Key Points

To assess the effectiveness of various smoking metrics in predicting survival outcomes in non-small cell lung cancer.
Analyzed different smoking metrics for their relationship with overall survival (OS) and lung cancer-specific survival (LCSS).
Evaluated clinicodemographic subgroups to check consistency in associations.
Utilized logcig-years as a key measurement for smoking exposure.
Logcig-years was the most effective at modeling OS and LCSS.
Consistent associations were observed across various clinicodemographic subgroups.
Findings support the inclusion of logcig-years in clinical assessments of lung cancer patients.

Abstract

Logcig-years best modelled the relationship between smoking exposure and OS as well as LCSS, and had consistent associations across clinicodemographic subgroups. Logcig-years should be considered in clinical and research applications for quantifying smoking exposure in lung cancer.

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Cite This Study

Lam et al. (Fri,) studied this question.

synapsesocial.com/papers/69c0ddb8fddb9876e79c1195 https://doi.org/https://doi.org/10.1016/j.canep.2026.103052

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