Predicting anxiety in cancer survivors presenting to primary care - A machine learning approach accounting for physical comorbidity.

Prediction of clinically significant anxiety in cancer survivors using readily available predictors is feasible. The findings highlight the need for considering cancer survivors' physical functioning regardless of the degree of comorbidity when assessing their psychological well-being. The generalizability of the model to other populations should be investigated in future external validations.