Frailty status determined by an electronic health record embedded frailty index and hospitalization risk among older adults following the initiation of cancer chemotherapy.
Authors: Klepin Heidi D. , Isom Scott , Callahan Kathryn E. , Pajewski Nicholas , Topaloglu Umit , Wagner Lynne I. , Gabbard Jennifer , Justice Jamie N , Parala-Metz Armida , Tooze Janet A. 
Published: June 2023

12010

Background: Novel strategies are needed to efficiently identify older adults at high risk for hospitalization before and after chemotherapy initiation. An electronic frailty index (eFI) holds promise as a passive digital marker for frailty available to estimate risk at the point of care. The objective of this study was to evaluate the association of pre-treatment eFI with risk of hospitalization after receipt of cancer chemotherapy among older adults. Methods: Consecutive patients (N = 509 aged 65+ with newly diagnosed lung, colorectal or breast cancer treated with chemotherapy) were identified from our cancer registry between 2017 and 2020. Calculation of the eFI is automated in the EMR. It requires at least two ambulatory visits over a 2-year period and utilizes demographic information, vital signs, smoking status, ICD-10 diagnosis codes, select outpatient laboratory measurements, and functional information (if available from Medicare Annual Wellness Visits) during the 2 years prior to diagnosis. Frailty status is categorized as fit (eFI ≤0.10), pre-frail (0.10 < eFI≤0.21), and frail (eFI > 0.21) based on the proportion of deficits present over the total number evaluated (score range 0-1). Non-calculable scores indicate insufficient historical primary care data within two year prior to cancer diagnosis. Outcomes were hospitalization at 3 and 6 months post chemotherapy initiation. Time to first hospitalization was estimated by eFI category, using Cox regression models to estimate the adjusted association between frailty status and hospitalization. Results: The cohort included 509 adults (median age 72.2 yrs, 55% female, 83% white, 13% black, 45.8% stage 4) with lung (N = 312), colorectal (N = 111), and breast (N = 86) cancers. Distribution of eFI categories at diagnosis were fit (26.3%), pre-frail (42.4%), frail (16.3%) and not calculable (14.9%). Hospitalization rates at 3 and 6 months post chemotherapy were 12.0% (fit), 29.9% (pre-frail), 46.3% (frail), 45.9% (not-calculable) and 24.4% (fit), 41.3% (pre-frail), 59.8% (frail) and 49.8% (non-calculable), respectively (p < 0.0001). Adjusting for age, gender, race, stage, and cancer type, the incidence of hospitalization was higher for frail (Hazard Ratio (HR) 2.96, 95% Confidence Interval (CI) 2.05, 4.27), pre-frail (HR 1.41, 95% CI 1.03, 1.94), and not calculable eFI categories (HR 2.01, 95% CI 1.33, 3.03) compared to fit patients. Conclusions: Over forty percent of frail older adults with lung, colorectal, or breast cancer identified by eFI were hospitalized within the first 3 months of chemotherapy initiation. The eFI can inform real-time shared treatment decision-making and identify a sub-set of patients who may benefit from care delivery interventions to decrease unplanned hospitalization and improve quality of care.