Abstract

The Cancer and Aging Research Group (CARG) prediction model for chemotherapy-related toxic effects has been developed but not yet validated in older Asian adults. In view of differences in drug metabolism and toxic effect reporting in the Asian population, the ability of this tool to guide the cancer treatment decision-making process in older Asian adults needs to be assessed. To examine the validity of the CARG predictive model in a multiethnic Asian cohort of older adults. In this prognostic study, patients of various Asian ethnicities 70 years or older with a solid tumor diagnosis receiving chemotherapy at the National University Cancer Institute, Singapore, were accrued from June 1, 2017, to January 1, 2019. Their risks of chemotherapy-related toxic effects were calculated using the CARG tool. A geriatric assessment was performed, and the treating oncologist (blinded to the CARG scores) was asked to give an estimated likelihood of toxic effects (low, medium, or high). Chemotherapy-related toxic effects were recorded during each clinic visit. Validation of the prediction model was performed by calculating the area under the receiver operating characteristic curve. Multivariate analyses were performed to identify variables in other domains in the geriatric assessment predicting for severe toxic effects. Grade 3 to 5 toxic effects and hospitalization. The study included 200 patients (median age, 74 years [range, 70-89 years]; 110 [55.0%] male; 177 [88.5%] Chinese, 17 [8.5%] Malay, 4 [2.0%] Indian, and 2 [1.0%] other ethnicities [according to Singapore's national system of race classification]). A total of 137 patients (68.5%) experienced grade 3 to 5 toxic effects, and 131 (65.5%) required hospitalization. The area under the receiver operating characteristic curve for the CARG chemotoxicity prediction model was 0.74 (95% CI, 0.67-0.82), retaining good discrimination in the study population. This prognostic study conducted in a multiethnic Asian cohort of older adults supports the validity of the CARG predictive model in this population, predicting which older adults are at risk of chemotherapy-related toxic effects.

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