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Prediction of clinical progression after radical prostatectomy in a nationwide population-based cohort
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2016 (English)In: Scandinavian journal of urology, ISSN 2168-1805, E-ISSN 2168-1813, Vol. 50, no 4, 255-259 p.Article in journal (Refereed) PublishedText
Abstract [en]

Objective: The aim of this study was to create a model for predicting progression-free survival after radical prostatectomy for localized prostate cancer. Material and methods: 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. Results: 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. Conclusions: 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 www.npcr.se/nomogram

Place, publisher, year, edition, pages
Taylor & Francis, 2016. Vol. 50, no 4, 255-259 p.
Keyword [en]
Biochemical recurrence, nomogram, predictive models, prostate cancer, radical prostatectomy
National Category
Urology and Nephrology
Identifiers
URN: urn:nbn:se:umu:diva-124277DOI: 10.1080/21681805.2016.1183226ISI: 000379024000003PubMedID: 27192553OAI: oai:DiVA.org:umu-124277DiVA: diva2:950525
Available from: 2016-08-01 Created: 2016-07-29 Last updated: 2016-08-01Bibliographically approved

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Stattin, Pär
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