Prognostic models for patients with metastatic castration-resistant prostate cancer (mCRPC) that are generalizable, current, and simple to apply are not yet available. Therefore, using information from 5 randomized clinical trials (RCTs), researchers created a nomogram to predict the overall survival (OS) of mCRPC patients undergoing conventional treatment.

Five RCTs (ASCENT 2, VENICE, CELGENE/MAINSAIL, ENTHUSE 14, and ENTHUSE 33) control arm patients were divided into training and validation cohorts at random (n=1,636, 70%; n=700, 30%). Cox regression evaluated each available variable’s prognostic value as a predictor of OS in the training cohort. A unique multivariable model was built using independent predictors of OS on multivariable analysis (nomogram). Using time-dependent area under the curve (tAUC) and calibration curves, the validity of this model was examined in the validation cohort.

The median (interquartile range) follow-up time was 13.9 (8.9-20.2) months, and the majority of the patients (44.5%) were aged 65 to 74. At multivariable analysis: (visceral vs. bone metastasis, hazard ratio [HR]: 1.24), prostate-specific antigen (HR: 1.00), aspartate transaminase (HR: 1.01), alkaline phosphatase (HR: 1.00), body mass index (HR: 0.97), and hemoglobin (≥13 g/dl vs. <11 g/dl, HR: 0.41; all P<0.05), among other factors, were independent predictors of overall survival (OS) in mCRPC patients. Based on these data, a nomogram was created, and external validation revealed that it had good calibration features and discrimination (tAUC at 12 and 24 months: 73% and 72%, respectively).

In order to predict OS for patients with mCRPC receiving first-line chemotherapy, a novel prognostic model was created. It could aid urologists and oncologists in patient counseling and may assist in more accurately stratifying patients for upcoming clinical trials.