Abstract
BACKGROUND: Predicting early death after a comprehensive geriatric assessment (CGA) is very difficult in clinical practice. The aim of this study was to develop a scoring system to estimate risk of death at 100 days in elderly cancer patients to assist the therapeutic decision. METHODS: This was a multicentric, prospective cohort study approved by an ethics committee. Elderly cancer patients aged older than 70 years were enrolled before the final therapeutic decision. A standardised CGA was made before the treatment decision at baseline. Within 100 days, event~(death), oncologic and geriatric data were collected. Multivariate logistic regression was used to select the risk factors for the overall population. Score points were assigned to each risk factor using the β coefficient. Internal validation was performed by a bootstrap method. Calibration was assessed with the Hosmer-Lemeshow goodness of fit test and accuracy with the mean c-statistic. FINDINGS: One thousand fifty patients (mean age: 82 years) joined the study from April 2012 to December 2014. The independent predictors were~metastatic cancers (odds ratio [OR] 2.5; 95% confidence interval [CI], [1.7-3.5] p\textless0 .001); gait speed\textless0.8~m/s (OR 2.1; 95% CI [1.3-3.3] p=0.001); Mini Nutritional Assessment (MNA)~\textless~17 (OR 8; 95% CI; [3.7-17.3] p\textless0.001), MNA <=23.5 and~>=~17 (OR 4.4; 95% CI, [2.1-9.1) p\textless0.001); performance status (PS)~\textgreater~2 (OR 1.7; 95% CI, [1.1-2.6)] p=0.015) and cancers other than breast cancer~(OR 4; 95% CI, [2.1-7.9] p\textless0.001). We attributed 4 points for MNA\textless17, 3 points for MNA between <=23.5 and~>=~17, 2 points for metastatic cancers, 1 point for gait speed \textless0.8~m/s, 1 point for PS~\textgreater~2 and 3 points for cancers other than breast cancer. The risk of death at 100 days was 4% for 0 to 6 points, 24% for 7 to 8 points, 39% for 9 to 10 points and 67% for 11 points. INTERPRETATION: To our knowledge, this is the first score which estimates early death in elderly cancer patients. The system could assist in the treatment decision for elderly cancer patients.