Background: Older patients have increased risk of toxicity from chemotherapy. Current prediction tools do not provide information on cumulative risk.
Methods: Patients aged ≥ 70 years with solid cancer were prospectively enrolled. A prediction model was developed for adverse events (AEs) ≥ Grade 3 (G3), based on geriatric assessment (GA), laboratory, and clinical variables.
Results: 301 patients were enrolled (median age, 75 years). Median number of chemotherapy cycles was 4. During first-line chemotherapy, 53.8% of patients experienced AEs ≥ G3. Serum protein < 6.7 g/dL, initial full-dose chemotherapy, psychological stress or acute disease in the past 3 months, water consumption < 3 cups/day, unable to obey a simple command, and self-perception of poor health were significantly related with AEs ≥ G3. A predicting model with these six variables ranging 0-8 points was selected with the highest discriminatory ability (c-statistic= 0.646), which could classify patients into four risk groups. Predicted cumulative incidence of AEs ≥ G3 was discriminated according to risk groups.
Conclusions: This prediction tool could identify the risk of AEs ≥ G3 after chemotherapy and provide information on the cumulative incidence of AEs in each cycle.
Clinical trial id: WHO ICTRP number, KCT0001071.