Life expectancy in older adults with advanced cancer: Evaluation of a geriatric assessment-based prognostic model. Issue 2 (March 2022)

• Record Type: Journal Article
• Authors: Lund, Jennifer L.; Duberstein, Paul R.; Loh, Kah Poh; Gilmore, Nikesha; Plumb, Sandy; Lei, Lianlian; Keil, Alexander P.; Islam, Jessica Y.; Hanson, Laura C.; Giguere, Jeffrey K.; Vogel, Victor G.; Burnette, Brian L.; Mohile, Supriya G.
• Is Part Of: Journal of geriatric oncology. Volume 13:Issue 2(2022)
• Page Start: 176
• Page End: 181
• Publication Date: 2022-03
• Subjects: Geriatric assessment -- Advanced cancer -- Prediction modeling; Geriatric oncology -- Periodicals; Neoplasms -- Periodicals; Aged -- Periodicals; Geriatric oncology; Electronic journals; Periodicals; 618.976994005
• DOI: 10.1016/j.jgo.2021.08.009
• Languages: English
• ISSNs: 1879-4068

Abstract

Abstract: Objectives: Oncologists estimate patients' prognosis to guide care. Evidence suggests oncologists tend to overestimate life expectancy, which can lead to care with questionable benefits. Information obtained from geriatric assessment may improve prognostication for older adults. In this study, we created a geriatric assessment-based prognostic model for older adults with advanced cancer and compared its performance to alternative models. Materials and methods: We conducted a secondary analysis of a trial (URCC 13070; PI: Mohile) capturing geriatric assessment and vital status up to one year for adults age ≥ 70 years with advanced cancer. Oncologists estimated life expectancy as 0–6 months, 7–12 months, and > 1 year. Three statistical models were developed: (1) a model including age, sex, cancer type, and stage (basic model), (2) basic model + Karnofsky Performance Status (≤50, 60–70, and 80+) (KPS model), and (3) basic model +16 binary indicators of geriatric assessment impairments (GA model). Cox regression was used to model one-year survival; c-indices and time-dependent c-statistics assessed model discrimination and stratified survival curves assessed model calibration. Results: We included 484 participants; mean age was 75; 48% had gastrointestinal or lung cancer. Overall, 43% of patients died within one year. Oncologists classified prognosis accurately for 55% of patients, overestimated for 35%, and underestimated for 10%. C-indices were 0.61 (basic model), 0.62 (KPS model), and 0.63 (GA model). The GA model was well-calibrated. Conclusions: The GA model showed moderate discrimination for survival, similar to alternative models, but calibration was improved. Further research is needed to optimize geriatric assessment-based prognostic models for use in older adults with advanced cancer.