Accounting for Delayed Entry in Analyses of Overall Survival in Clinico-Genomic Databases.

ABSTRACT:

Background

Clinico-genomic databases favor inclusion of long-term survivors, leading to potentially biased overall survival (OS) analyses. Risk set adjustments relying on the independent delayed entry assumption may mitigate this bias. We aimed to determine whether this assumption is satisfied in a dataset of patients with advanced non-small cell lung cancer (aNSCLC), and to give guidance for clinico-genomic OS analyses when the assumption is not satisfied.

Methods

We analyzed the association of timing of next-generation sequencing (NGS) testing with real-world OS (rwOS) in patient data from a United States-based nationwide longitudinal deidentified electronic health records-derived database. Estimates of rwOS using risk set adjustment were compared with estimates computed w

SUBMITTER: Backenroth D 

PROVIDER: S-EPMC9377725 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature