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The Modulating Effects of Benign Prostate Enlargement Medications on Upgrading Predictors in Patients with Gleason 6 at Biopsy.

ABSTRACT: Upgrading following prostate biopsy is very common in clinical practice. This study investigated whether the use of 5-alpha reductase inhibitors (ARI) and alpha blockers affect known clinical predictors of Gleason score upgrading or not.A retrospective study on 998 patients treated with robotic assisted laparoscopic prostatectomy for clinically localized biopsy Gleason score 6 prostate cancer were studied. The logarithm of prostate specific antigen concentration, prostate size and tumor volume were compared on the basis of the medication history of 5-ARIs and alpha blockers in the cohort of biopsy Gleason 6 patients with benign prostatic hyperplasia history, and patients whose prostate sizes fall in the top quartile. We compared known clinical and pathologic characteristics associated with upgrading in regression models with and without the addition of medications.Alpha blockers, but not 5-ARI were associated with a bigger prostate. Upgrading was associated with older age (OR 1.03, 95% CI 1.01-1.06), higher BMI (OR 1.00 CI 1.01-1.08), higher log prostate specific antigen (OR 7.32, CI 3.546-15.52), smaller prostate size (OR 0.97, CI 0.96-0.98), fewer biopsy cores (OR 0.96 CI 0.92-0.99), more positive cores (OR 1.20, CI 1.08-1.34), and higher percentage of tumor at biopsy (OR 1.02, CI 1.01-1.03). Neither of the two medication classes were a significant predictor of upgrading. Medications made minimal changes in the multivariate predictive models.Although, alpha blockers were associate with bigger prostate size, the modulating effects of alpha blockers and 5-ARIs on common predictors of Gleason score upgrading was not significant.

SUBMITTER: Jazayeri SB

PROVIDER: S-EPMC5527191 | biostudies-other | 2017 Jul

REPOSITORIES: biostudies-other

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Project description:ObjectiveTo develop a model and methodology for predicting the risk of Gleason upgrading in patients with prostate cancer on active surveillance (AS) and using the predicted risks to create risk-based personalised biopsy schedules as an alternative to one-size-fits-all schedules (e.g. annually). Furthermore, to assist patients and doctors in making shared decisions on biopsy schedules, by providing them quantitative estimates of the burden and benefit of opting for personalised vs any other schedule in AS. Lastly, to externally validate our model and implement it along with personalised schedules in a ready to use web-application.Patients and methodsRepeat prostate-specific antigen (PSA) measurements, timing and results of previous biopsies, and age at baseline from the world's largest AS study, Prostate Cancer Research International Active Surveillance (PRIAS; 7813 patients, 1134 experienced upgrading). We fitted a Bayesian joint model for time-to-event and longitudinal data to this dataset. We then validated our model externally in the largest six AS cohorts of the Movember Foundation's third Global Action Plan (GAP3) database (>20 000 patients, 27 centres worldwide). Using the model predicted upgrading risks; we scheduled biopsies whenever a patient's upgrading risk was above a certain threshold. To assist patients/doctors in the choice of this threshold, and to compare the resulting personalised schedule with currently practiced schedules, along with the timing and the total number of biopsies (burden) planned, for each schedule we provided them with the time delay expected in detecting upgrading (shorter is better).ResultsThe cause-specific cumulative upgrading risk at the 5-year follow-up was 35% in PRIAS, and at most 50% in the GAP3 cohorts. In the PRIAS-based model, PSA velocity was a stronger predictor of upgrading (hazard ratio [HR] 2.47, 95% confidence interval [CI] 1.93-2.99) than the PSA level (HR 0.99, 95% CI 0.89-1.11). Our model had a moderate area under the receiver operating characteristic curve (0.6-0.7) in the validation cohorts. The prediction error was moderate (0.1-0.2) in theGAP3 cohorts where the impact of the PSA level and velocity on upgrading risk was similar to PRIAS, but large (0.2-0.3) otherwise. Our model required re-calibration of baseline upgrading risk in the validation cohorts. We implemented the validated models and the methodology for personalised schedules in a web-application (http://tiny.cc/biopsy).ConclusionsWe successfully developed and validated a model for predicting upgrading risk, and providing risk-based personalised biopsy decisions in AS of prostate cancer. Personalised prostate biopsies are a novel alternative to fixed one-size-fits-all schedules, which may help to reduce unnecessary prostate biopsies, while maintaining cancer control. The model and schedules made available via a web-application enable shared decision-making on biopsy schedules by comparing fixed and personalised schedules on total biopsies and expected time delay in detecting upgrading.

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The Modulating Effects of Benign Prostate Enlargement Medications on Upgrading Predictors in Patients with Gleason 6 at Biopsy.

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