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Prediction of significant prostate cancer in biopsy-naive men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS.

ABSTRACT: BACKGROUND:Risk models (RM) need external validation to assess their value beyond the setting in which they were developed. We validated a RM combining mpMRI and clinical parameters for the probability of harboring significant prostate cancer (sPC, Gleason Score ? 3+4) for biopsy-naïve men. MATERIAL AND METHODS:The original RM was based on data of 670 biopsy-naïve men from Heidelberg University Hospital who underwent mpMRI with PI-RADS scoring prior to MRI/TRUS-fusion biopsy 2012-2015. Validity was tested by a consecutive cohort of biopsy-naïve men from Heidelberg (n = 160) and externally by a cohort of 133 men from University College London Hospital (UCLH). Assessment of validity was performed at fusion-biopsy by calibration plots, receiver operating characteristics curve and decision curve analyses. The RM`s performance was compared to ERSPC-RC3, ERSPC-RC3+PI-RADSv1.0 and PI-RADSv1.0 alone. RESULTS:SPC was detected in 76 men (48%) at Heidelberg and 38 men (29%) at UCLH. The areas under the curve (AUC) were 0.86 for the RM in both cohorts. For ERSPC-RC3+PI-RADSv1.0 the AUC was 0.84 in Heidelberg and 0.82 at UCLH, for ERSPC-RC3 0.76 at Heidelberg and 0.77 at UCLH and for PI-RADSv1.0 0.79 in Heidelberg and 0.82 at UCLH. Calibration curves suggest that prevalence of sPC needs to be adjusted to local circumstances, as the RM overestimated the risk of harboring sPC in the UCLH cohort. After prevalence-adjustment with respect to the prevalence underlying ERSPC-RC3 to ensure a generalizable comparison, not only between the Heidelberg and die UCLH subgroup, the RM`s Net benefit was superior over the ERSPC`s and the mpMRI`s for threshold probabilities above 0.1 in both cohorts. CONCLUSIONS:The RM discriminated well between men with and without sPC at initial MRI-targeted biopsy but overestimated the sPC-risk at UCLH. Taking prevalence into account, the model demonstrated benefit compared with clinical risk calculators and PI-RADSv1.0 in making the decision to biopsy men at suspicion of PC. However, prevalence differences must be taken into account when using or validating the presented risk model.

SUBMITTER: Radtke JP

PROVIDER: S-EPMC6710031 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Prediction of significant prostate cancer in biopsy-naïve men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS.

Radtke Jan Philipp JP Giganti Francesco F Wiesenfarth Manuel M Stabile Armando A Marenco Jose J Orczyk Clement C Kasivisvanathan Veeru V Nyarangi-Dix Joanne Nyaboe JN Schütz Viktoria V Dieffenbacher Svenja S Görtz Magdalena M Stenzinger Albrecht A Roth Wilfried W Freeman Alex A Punwani Shonit S Bonekamp David D Schlemmer Heinz-Peter HP Hohenfellner Markus M Emberton Mark M Moore Caroline M CM

PloS one 20190826 8

<h4>Background</h4>Risk models (RM) need external validation to assess their value beyond the setting in which they were developed. We validated a RM combining mpMRI and clinical parameters for the probability of harboring significant prostate cancer (sPC, Gleason Score ≥ 3+4) for biopsy-naïve men.<h4>Material and methods</h4>The original RM was based on data of 670 biopsy-naïve men from Heidelberg University Hospital who underwent mpMRI with PI-RADS scoring prior to MRI/TRUS-fusion biopsy 2012- ...[more]

PMID: 31450235

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Project description:BackgroundProstate Imaging Reporting and Data System version 2 (PI-RADS V2) 3 category lesions are of intermediate status with an equivocal risk of presenting clinically significant prostate cancer (csPCa). How to avoid excessive biopsies while improving the csPCa detection rate in these lesions has always been a clinical problem that needed to be solved. The purpose of this study is to explore the csPCa diagnostic value of clinical and magnetic resonance imaging (MRI) data for peripheral and transitional zone (PZ and TZ, respectively) PI-RADS 3 lesions to aid in clinical decision-making and reduce excessive biopsies.MethodsFrom March 2016 to October 2018, a total of 629 men who underwent a prostate MRI and subsequently biopsy were enrolled. Two radiologists (with 3 and 7 years of experience, respectively) independently reviewed and scored all images using the PI-RADS V2 scoring criteria. Clinical and MRI data of men with PI-RADS 3 index lesions were collected by another radiologist. Univariate and multivariate analyses were performed to identify the risk factors of csPCa.ResultsIn a subset of 121 men with 121 PI-RADS 3 index lesions, 25.6% of the lesions (31/121) were PCa (Gleason score ≥6), and 11.6% (14/121) were csPCa (Gleason score ≥7). Further, 44.6% of lesions (54/121) were located in the PZ and 55.4% (67/121) in the TZ. For PZ lesions, 18.5% of the lesions (10/54) were csPCa. Prostate-specific antigen density (PSAD) (P=0.024) and age (P=0.026) were independent risk factors for csPCa in the multivariate logistic analysis. The combination of PSAD and age yielded an area under the curve (AUC) value of 0.816 for predicting csPCa. If biopsy had been restricted to patients with a PSAD ≥0.15 ng/mL2 or an age >68 years, 24.1% (13/54) of patients would have avoided biopsy but only 1 (10%) csPCa would have been missed, with a sensitivity of 80.0% and negative predictive value (NPV) of 92.3%. For TZ lesions, only 6.0% of the lesions (4/67) were csPCa. The PSA and PSAD values in the PI-RADS 3 TZ lesions were higher in the csPCa group (45.07 and 0.47 ng/mL2, respectively) than in the non-csPCa group (10.03 and 0.17 ng/mL2, respectively).ConclusionsCsPCa was detected at a relatively high rate in PI-RADS 3 PZ lesions. Combining PSAD and age could help to reduce excessive biopsies of such lesions. CsPCa is unlikely to be detected in PI-RADS 3 TZ lesions; thus, active surveillance may be an optimal choice for these lesions, especially among patients without high-risk factors.

Dataset Information

Prediction of significant prostate cancer in biopsy-naive men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS.

Publications

Prediction of significant prostate cancer in biopsy-naïve men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS.

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