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. 2015 Feb;115(2):308-16.
doi: 10.1111/bju.12802. Epub 2014 Aug 13.

Baseline characteristics predict risk of progression and response to combined medical therapy for benign prostatic hyperplasia (BPH)

Affiliations

Baseline characteristics predict risk of progression and response to combined medical therapy for benign prostatic hyperplasia (BPH)

Michael A Kozminski et al. BJU Int. 2015 Feb.

Abstract

Objective: To better risk stratify patients, using baseline characteristics, to help optimise decision-making for men with moderate-to-severe lower urinary tract symptoms (LUTS) secondary to benign prostatic hyperplasia (BPH) through a secondary analysis of the Medical Therapy of Prostatic Symptoms (MTOPS) trial.

Patients and methods: After review of the literature, we identified potential baseline risk factors for BPH progression. Using bivariate tests in a secondary analysis of MTOPS data, we determined which variables retained prognostic significance. We then used these factors in Cox proportional hazard modelling to: i) more comprehensively risk stratify the study population based on pre-treatment parameters and ii) to determine which risk strata stood to benefit most from medical intervention.

Results: In all, 3047 men were followed in MTOPS for a mean of 4.5 years. We found varying risks of progression across quartiles. Baseline BPH Impact Index score, post-void residual urine volume, serum prostate-specific antigen (PSA) level, age, American Urological Association Symptom Index score, and maximum urinary flow rate were found to significantly correlate with overall BPH progression in multivariable analysis.

Conclusions: Using baseline factors permits estimation of individual patient risk for clinical progression and the benefits of medical therapy. A novel clinical decision tool based on these analyses will allow clinicians to weigh patient-specific benefits against possible risks of adverse effects for a given patient.

Keywords: benign prostatic hyperplasia (BPH); lower urinary tract symptoms (LUTS); risk factors.

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Conflict of interest statement

DISCLOSURES

None of the four authors have any conflicts of interest.

Figures

Figure 1
Figure 1. Four-year risk of BPH progression stratified across quartiles
Linear predictor scores from our full model were used to generate a spectrum of risk, which we divided into quartiles. This was performed for all four arms of MTOPS. The observed mean event rates for each arm within each quartile were collected based on Kaplan-Meier estimated event rates within the MTOPS trial. ***Event rates (%) are listed in the table below.
Figure 2
Figure 2. Medication treatment effects in terms of absolute risk compared to serious adverse events (SAEs) that resulted in therapy interruption/discontinuation
Absolute risk reductions (with 95% CI) for the different treatment arms are calculated compared to the placebo arm and increase over quartiles of BPH progression, ordered from left to right (Q1->Q4), with each treatment arm reported (ordered as doxazosin (D), finasteride (F), combination (C) in each quartile). Serious adverse events (with 95% CI) are reported in raw percentages (listed as negative values for comparison). The number needed to treat (NNT) is derived from the absolute risk reductions in the respective groups, as listed in the table below. ARR = absolute risk reduction compared to placebo; NNT = number needed to treat (1/ARR)
Figure 3
Figure 3
Reduced Model--Clinical decision tool for predicting 4-year risk of clinical BPH progression using data from MTOPS, 4 predictor regression model. In order to determine an individual’s risk of progression, draw a vertical line from each of the patient’s factors to the “Points” line above. Add the four “Points” values together to arrive at a “Total Points.” Calculate the expected event rate with therapy by applying the hazard ratios below.

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