Developing a multimorbidity prognostic score in elderly patients with solid cancer using administrative databases from Italy

Abstract

AbstractAimsTo develop and to validate a Cancer Multimorbidity Score (CMS) predictive of mortality in elderly patients affected by solid tumor, by using population‐based administrative Italian databases.MethodsThrough administrative databases of Lombardy Region (Northern Italy), a cohort of patients aged ≥65 years with a new diagnosis of solid tumor during the period 2009–2014 was identified. Sixty‐one conditions and diseases, measured from hospital inpatient diagnosis and outpatient drug prescription within 2 years before cancer diagnosis in a training set randomly including 70% of the cohort patients were tested to predict 5‐year mortality using a Cox regression model. Regression coefficients were used for assigning a weight to the predictive conditions, selected by the LASSO method. Weights were summed up in order to produce an aggregate score (the CMS). CMS performance was evaluated on a validation set, including the remaining 30% of the cohort patients, in terms of discrimination and calibration.ResultsThe study cohort included 148,242 cancer patients. Thirty conditions were selected as independent predictors of 5‐year mortality and were included in the computation of the CMS. The area under the receiving operating characteristics curve was 0.68, becoming 0.71 when considering 1‐year mortality as outcome and reaching values of 0.74 and 0.81 when focusing on patients with breast and prostate cancer, respectively. A strong increasing trend in mortality was observed with increasing CMS value.ConclusionsCMS represents a new useful tool for identifying high‐risk elderly cancer patients in everyday clinical practice, as well as for risk adjustment in clinical and epidemiological studies.