Journal
UROLOGY
Volume 88, Issue -, Pages 125-132Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.urology.2015.09.035
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Funding
- Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research
- NIH Center for Interventional Oncology
- NIH
- Pfizer Inc.
- Doris Duke Charitable Foundation
- Newport Foundation
- American Association for Dental Research
- Howard Hughes Medical Institute
- Colgate-Palmolive Company
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OBJECTIVE To validate the use of biparametric (T2- and diffusion-weighted) magnetic resonance imaging (B-MRI) and prostate-specific antigen (PSA) or PSA density (PSAD) in a biopsy-naive cohort at risk for prostate cancer (PCa). METHODS All patients (n = 59) underwent PSA screening and digital rectal exam prior to a B-MRI followed by MRI or transrectal ultrasound fusion-guided targeted biopsy. Previously reported composite formulas incorporating screen positive lesions (SPL) on B-MRI and PSA or PSAD were developed to maximize PCa detection. For PSA, a patient was considered screen positive if PSA level + 6 x (the number of SPL) > 14. For PSAD, screening was positive if PSAD x 14 + (the number of SPL) > 4.25. These schemes were employed in this new test set to validate the initial formulas. Performance assessment of these formulas was determined for all cancer detection and for tumors with Gleason >= 3 + 4. RESULTS Screen positive lesions on B-MRI had the highest sensitivity (95.5%) and negative predictive value of 71.4% compared with PSA and PSAD. B-MRI significantly improved sensitivity (43.2-72.7%, P = .0002) when combined with PSAD. The negative predictive value of PSA increased with B-MRI, achieving 91.7% for B-MRI and PSA for Gleason >= 3 + 4. Overall accuracies of the composite equations were 81.4% (B-MRI and PSA) and 78.0% (B-MRI and PSAD). CONCLUSION Validation with a biopsy-naive cohort demonstrates the parameter SPL performed better than PSA or PSAD alone in accurately detecting PCa. The combined use of B-MRI, PSA, and PSAD resulted in improved accuracy for detecting clinically significant PCa. 2016 Published by Elsevier Inc.
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