Predicting biochemical recurrence and prostate cancer-specific mortality after radical prostatectomy: comparison of six prediction models in a cohort of patients with screening- and clinically detected prostate cancer

Abstract

Objectives: To perform a comparison and external validation of three models predicting biochemical recurrence (BCR) and three models predicting prostate cancer (PCa)-specific mortality (PCSM) in a screening setting, i.e. patients with screening-detected PCa (S-PCa) and in those with clinically detected PCa (C-PCa).

Subjects and methods: We retrospectively evaluated 795 men with S-PCa, from the European Randomized Study of Screening for Prostate Cancer, Rotterdam, and 1123 men with C-PCa initially treated with RP. The discriminative ability of the models was assessed according to the area under the curve (AUC) of the receiver-operating characteristic, and calibration was assessed graphically using calibration plots.

Results: The median (interquartile range [IQR]) follow-up for the S-PCa group was 10.4 (6.8-14.3) years and for the C-PCa group it was 8.8 (4.8-12.9) years. A total of 123 men with S-PCa (15%) and 389 men with C-PCa (35%) experienced BCR. Of the men with S-PCa and BCR, 24 (20%) died from PCa and 29 (23%) died from other causes. Of the men with C-PCa and BCR, 68 (17%) died from PCa and 105 (27%) died from other causes. The discrimination of the models predicting BCR or PCSM was higher for men with S-PCa (AUC: BCR 0.77-0.84, PCSM 0.60-0.77) than for the men with C-PCa (AUC: BCR 0.75-0.79, PCSM 0.51-0.68) as a result of the similar patient characteristics of the men with S-PCa in the present study and those of the cohorts used to develop these models. The risk of BCR was typically overestimated, while the risk of PCSM was typically underestimated.

Conclusion: Prediction models for BCR showed good discrimination and reasonable calibration for both men with S-PCa and men with C-PCa, and even better discrimination for men with S-PCa. For PCSM, the evaluated models are not applicable in both settings of this Dutch cohort as a result of substantial miscalibration. This warrants caution when using these models to communicate future risks in other clinical settings.

Keywords: #PCSM; #ProstateCancer; clinical decision-making; nomograms; probability; prostatectomy; prostatic neoplasms.