Prediction of clinical progression after radical prostatectomy in a nationwide population-based cohort.

The aim of this study was to create a model for predicting progression-free survival after radical prostatectomy for localized prostate cancer.

The risk of biochemical recurrence (BCR) was modelled in a cohort of 3452 men aged 70 years or younger who were primarily treated with radical prostatectomy after being diagnosed between 2003 and 2006 with localized prostate cancer [clinical stage T1c-T2, Gleason score 5-10, N0/NX, M0/MX, prostate-specific antigen (PSA) < 20 ng/ml]. The cohort was split into two: one cohort for model development (n = 3452) and one for validation (n = 1762). BCR was defined as two increasing PSA values of at least 0.2 ng/ml, initiation of secondary therapy, distant metastases or death from prostate cancer. Multivariable Cox proportional hazard regression was applied, predictive performance was assessed using the bootstrap resampling technique to calculate the c index, and calibration of the model was evaluated by comparing predicted and observed Kaplan-Meier 1 year BCR.

The overall 5 year progression-free survival was 83% after a median follow-up time of 6.8 years in the development cohort and 7.3 years in the validation cohort. The final model included T stage, PSA level, primary and secondary Gleason grade, and number of positive and negative biopsies. The c index for discrimination between high and low risk of recurrence was 0.68. The probability of progression-free survival ranged from 22% to 97% over the range of risk scores in the study population.

This model is based on nationwide population-based data and can be used with a fair predictive accuracy to guide decisions on clinical follow-up after prostatectomy. An online calculator for convenient clinical use of the model is available at

Scandinavian journal of urology. 2016 May 18 [Epub ahead of print]

Anders Bjartell, Matteo Bottai, Josefin Persson, Ola Bratt, Jan-Erik Damber, Pär Stattin, Olof Akre

a Department of Urology , Skåne University Hospital , Malmö , Sweden ;, c Unit of Biostatistics, Institute of Environmental Medicine , Karolinska Institutet , Stockholm , Sweden ;, d Department of Cardiothoracic Surgery , Sahlgrenska University Hospital , Gothenburg , Sweden ;, b Department of Translational Medicine, Division of Urological Cancers , Lund University , Sweden ;, f Department of Urology, Institute of Clinical Sciences , Sahlgrenska Academy, University of Gothenburg , Sweden ;, g Department of Surgical Sciences , Uppsala University , Uppsala , Sweden ;, i Department of Medicine Solna, Karolinska Institutet, and Department of Urology , Karolinska University Hospital , Stockholm , Sweden.