Validation of a Prediction Tool for Chemotherapy Toxicity in Older Adults With Cancer.
PURPOSE: Older adults are at increased risk for chemotherapy toxicity, and standard oncology assessment measures cannot identify those at risk. A predictive model for chemotherapy toxicity was developed (N = 500) that consisted of geriatric assessment questions and other clinical variables. This study aims to externally validate this model in an independent cohort (N = 250). PATIENTS AND METHODS: Patients age ≥ 65 years with a solid tumor, fluent in English, and who were scheduled to receive a new chemotherapy regimen were recruited from eight institutions. Risk of chemotherapy toxicity was calculated (low, medium, or high risk) on the basis of the prediction model before the start of chemotherapy. Chemotherapy-related toxicity was captured (grade 3 [hospitalization indicated], grade 4 [life threatening], and grade 5 [treatment-related death]). Validation of the prediction model was performed by calculating the area under the receiver-operating characteristic curve. RESULTS: The study sample (N = 250) had a mean age of 73 years (range, 65 to 94 [standard deviation, 5.8]). More than one half of patients (58%) experienced grade ≥ 3 toxicity. Risk of toxicity increased with increasing risk score (36.7% low, 62.4% medium, 70.2% high risk; P < .001). The area under the curve of the receiver-operating characteristic curve was 0.65 (95% CI, 0.58 to 0.71), which was not statistically different from the development cohort (0.72; 95% CI, 0.68 to 0.77; P = .09). There was no association between Karnofsky Performance Status and chemotherapy toxicity (P = .25). CONCLUSION: This study externally validated a chemotherapy toxicity predictive model for older adults with cancer. This predictive model should be considered when discussing the risks and benefits of chemotherapy with older adults.
Hurria, A; Mohile, S; Gajra, A; Klepin, H; Muss, H; Chapman, A; Feng, T; Smith, D; Sun, C-L; De Glas, N; Cohen, HJ; Katheria, V; Doan, C; Zavala, L; Levi, A; Akiba, C; Tew, WP
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