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Combined Clinical Parameters and Multiparametric Magnetic Resonance Imaging for Advanced Risk Modeling of Prostate Cancer—Patient-tailored Risk Stratification Can Reduce Unnecessary Biopsies
- Source :
- European Urology. 72:888-896
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- Background Multiparametric magnetic resonance imaging (mpMRI) is gaining widespread acceptance in prostate cancer (PC) diagnosis and improves significant PC (sPC; Gleason score≥3+4) detection. Decision making based on European Randomised Study of Screening for PC (ERSPC) risk-calculator (RC) parameters may overcome prostate-specific antigen (PSA) limitations. Objective We added pre-biopsy mpMRI to ERSPC-RC parameters and developed risk models (RMs) to predict individual sPC risk for biopsy-naive men and men after previous biopsy. Design, setting, and participants We retrospectively analyzed clinical parameters of 1159 men who underwent mpMRI prior to MRI/transrectal ultrasound fusion biopsy between 2012 and 2015. Outcome measurements and statistical analysis Multivariate regression analyses were used to determine significant sPC predictors for RM development. The prediction performance was compared with ERSPC-RCs, RCs refitted on our cohort, Prostate Imaging Reporting and Data System (PI-RADS) v1.0, and ERSPC-RC plus PI-RADSv1.0 using receiver-operating characteristics (ROCs). Discrimination and calibration of the RM, as well as net decision and reduction curve analyses were evaluated based on resampling methods. Results and limitations PSA, prostate volume, digital-rectal examination, and PI-RADS were significant sPC predictors and included in the RMs together with age. The ROC area under the curve of the RM for biopsy-naive men was comparable with ERSPC-RC3 plus PI-RADSv1.0 (0.83 vs 0.84) but larger compared with ERSPC-RC3 (0.81), refitted RC3 (0.80), and PI-RADS (0.76). For postbiopsy men, the novel RM's discrimination (0.81) was higher, compared with PI-RADS (0.78), ERSPC-RC4 (0.66), refitted RC4 (0.76), and ERSPC-RC4 plus PI-RADSv1.0 (0.78). Both RM benefits exceeded those of ERSPC-RCs and PI-RADS in the decision regarding which patient to receive biopsy and enabled the highest reduction rate of unnecessary biopsies. Limitations include a monocentric design and a lack of PI-RADSv2.0. Conclusions The novel RMs, incorporating clinical parameters and PI-RADS, performed significantly better compared with RMs without PI-RADS and provided measurable benefit in making the decision to biopsy men at a suspicion of PC. For biopsy-naive patients, both our RM and ERSPC-RC3 plus PI-RADSv1.0 exceeded the prediction performance compared with clinical parameters alone. Patient summary Combined risk models including clinical and imaging parameters predict clinically relevant prostate cancer significantly better than clinical risk calculators and multiparametric magnetic resonance imaging alone. The risk models demonstrate a benefit in making a decision about which patient needs a biopsy and concurrently help avoid unnecessary biopsies.
- Subjects :
- Male
medicine.medical_specialty
Biopsy
Urology
Medizin
030232 urology & nephrology
Unnecessary Procedures
Risk Assessment
03 medical and health sciences
Prostate cancer
0302 clinical medicine
Prostate
medicine
Humans
Multiparametric Magnetic Resonance Imaging
Aged
Digital Rectal Examination
Retrospective Studies
medicine.diagnostic_test
business.industry
Ultrasound
Age Factors
Area under the curve
Prostatic Neoplasms
Magnetic resonance imaging
Organ Size
Middle Aged
Models, Theoretical
Prostate-Specific Antigen
medicine.disease
Magnetic Resonance Imaging
medicine.anatomical_structure
ROC Curve
030220 oncology & carcinogenesis
Cohort
Radiology
Neoplasm Grading
business
Subjects
Details
- ISSN :
- 03022838
- Volume :
- 72
- Database :
- OpenAIRE
- Journal :
- European Urology
- Accession number :
- edsair.doi.dedup.....5f3aedad569bf47a6a9dce13231f6bd8
- Full Text :
- https://doi.org/10.1016/j.eururo.2017.03.039