Predictive value of an electronic frailty index (FI) in U.S. Veterans with newly diagnosed non-small cell lung cancer (NSCLC).

Abstract

11545 Background: Frailty is a well-established predictor of survival, but assessing it in a real-world healthcare setting is often time-consuming and impractical. We sought to determine if a quantitative measure of frailty, computed automatically from electronic health records using the cumulative deficit model, also predicts overall survival in patients with NSCLC. Methods: We conducted a retrospective cohort study of Veterans identified to have NSCLC in the VA Precision Oncology Data Repository. Frailty was assessed using a previously validated FI, the Frailty Index for Veterans Affairs (VA-FI), consisting of 31 deficits. We categorized non-frail patients into non-frail (0-0.1) and pre-frail (0.1-0.2) groups, and frail patients into mild (0.2-0.3), moderate (0.3-0.4) and severe ( > 0.4) groups. Associations of frailty and survival were assessed using Kaplan-Meier estimates and Cox models. The added value of frailty status for predictive performance was quantified using the continuous net-reclassification index (NRI). Results: The cohort included 359 patients with NSCLC. The mean age was 66 years, and 96.1% were male, including 76.3% Caucasian and 16.2% African-American. The majority had an advanced stage cancer (15.9% and 44.3% with stages III and IV respectively) with minority falling into the early stage category (15.3% and 6.1% with stages I and II respectively). A substantial proportion of patients were identified to be frail (30%). The frailty categories differentiated survival profiles of patients with 2-year survival ranging from 0.41 for non-frail patients to 0.08 for the severely frail patients (log-rank p < 0.001). Frail patients exhibited significantly shorter survival than non-frail group even after adjusting for age, gender, and stage in a multivariate Cox model (hazard ratio 1.7, p < 0.001). Inclusion of frailty status in the Cox model significantly improved 2-year risk estimates of survival (NRI 0.35; 95% CI 0.27–0.47). Conclusions: Frailty as determined by VA-FI is a significant predictor of survival independent of stage and demographic factors among NSCLC patients in this VA cohort. VA-FI is an automated and a practically feasible tool to better estimate life expectancy and help individualize patient care.