Gradient Boosted Tree Approaches for Mapping European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 Onto 5-Level Version of EQ-5D Index for Patients With Cancer

•Although modern machine learning methods have led to improvements in many fields of medicine, they are rarely applied to mapping from a nonpreference-based measure onto health utility.•This study developed direct and response mapping algorithms from the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 onto the 5-level version of EQ-5D index using the gradient boosted tree, a promising modern machine learning method.•The gradient boosted tree approach did not improve the predictive performance measured by the root mean squared error and mean absolute error compared with regression approaches but had the potential to reduce overprediction and underprediction in poor and good health, respectively.