Methods for Using Race and Ethnicity in Prediction Models for Lung Cancer Screening Eligibility.

ABSTRACT:

Importance

Using race and ethnicity in clinical prediction models can reduce or inadvertently increase racial and ethnic disparities in medical decisions.

Objective

To compare eligibility for lung cancer screening in a contemporary representative US population by refitting the life-years gained from screening-computed tomography (LYFS-CT) model to exclude race and ethnicity vs a counterfactual eligibility approach that recalculates life expectancy for racial and ethnic minority individuals using the same covariates but substitutes White race and uses the higher predicted life expectancy, ensuring that historically underserved groups are not penalized.

Design, setting, and participants

The 2 submodels composing LYFS-CT NoRace were refit and externally validated without

SUBMITTER: Landy R 

PROVIDER: S-EPMC10507484 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature