Frailty status derived from the electronic medical record to predict survival and health care utilization in veterans with lung and gastrointestinal cancers.

Abstract

6582 Background: Frailty is associated with increased vulnerability to stressors. Although frailty is a predictor of survival, traditional frailty assessments are not feasible in clinical practice. Frailty indexes (FI) derived from the electronic medical record (EMR) are an alternate approach. There is limited data for the association between EMR-FI and cancer-related outcomes including survival and health care utilization. Methods: We identified a cohort of patients diagnosed with lung or gastrointestinal cancer from 2016-2020 using VA administrative files. We used the Veterans Affairs-FI (VA-FI), a validated 31-item cumulative deficit FI, to define three groups: robust (≤0.1), prefrail (0.1-0.2), frail ( > 0.2). Cox proportional hazard analyses were conducted to evaluate survival. Logistic regression analyses were performed to examine healthcare utilization. All models were adjusted for age, gender, race, Charlson comorbidity index, and stage. Results: Among 37,439 patients (age: 70±8.6 years), the majority were prefrail (36.8%) or frail (24.1%). Prefrail patients had a 13% increased risk of death compared to robust patients (adjusted hazard ratio [aHR] 1.13; 95% CI 1.10-1.16), while frail patients had a 52% increased risk (aHR 1.52; 95% CI 1.47, 1.57). Pre-frail and frail patients had increased odds of 1-year ED visits (adjusted odds ratio [aOR] 1.33; 95% CI 1.27 - 1.40 and aOR, 1.88, 95% CI 1.77-2.00, respectively). Frailty status was associated with increased odds of 1-year all-cause hospitalization among prefrail (aOR 1.09; 95% CI 1.03-1.15) and frail patients (aOR 1.26; 95%CI: 1.18, 1.34). Conclusions: Frailty measured by EMR data is significantly associated with survival and healthcare utilization among patients with lung and gastrointestinal cancers, independent of stage. Further study is warranted to develop EMR-FI as a risk stratification tool for personalized cancer treatment decisions.