Presented by: Courtney Yong MD
Indiana University

Introduction

Preoperatively predicting extraprostatic extension (EPE) in prostate cancer is important to determine which patients can safely undergo a nerve-sparing prostatectomy while preserving oncologic control. We examined whether 68Ga-PSMA-11 PET CT (PSMA PET), multiparametric MRI (mpMRI), or Decipher analysis would independently predict EPE in prostate cancer patients undergoing radical prostatectomy.

Materials

We prospectively enrolled 50 patients with clinically significant, localized prostate cancer, defined as ≥3 cores of Gleason 3+4 or worse. The patients underwent both mpMRI and PSMA PET prior to radical prostatectomy. Images were read by dedicated radiologists to identify EPE at the nerve bundles, apex, and bladder neck and seminal vesicle invasion. Tissue from the final pathology specimen was also sent for Decipher analysis and given a score from 0 to 1, with 1 being highest risk and >0.6 being considered high risk. Multivariate logistic regression was used to determine the odds ratio (OR) for EPE based on positivity on imaging or Decipher score.

Results

,

The average age and PSA of patients was 61.5 and 6.97 respectively. 72% of patients had Gleason 4+3 or higher on biopsy. The average Decipher score was 0.58. Both PSMA PET positive for EPE (OR 9.8, 95% CI 1.5-62, p=0.02) and Decipher score higher than 0.6 (OR 2.4, 95% CI 1.0-5.7, p=0.05) were predictive of EPE on final pathology. However, positive mpMRI (OR 0.74, 95% CI 0.16-3.5, p=0.71) and PSA density > 0.15 (OR0.17, 95% CI 0.0038-7.7, p=0.36) were not predictive of EPE.

Conclusion

Both PSMA PET and Decipher score on final prostatectomy pathology are independent predictors of EPE on final pathology. Future research on Decipher score on preoperative biopsy tissue is necessary to assist in further stratifying these patients and identifying those who can safely undergo nerve-sparing.

Funding

American Cancer Society Institutional research grant #19-144-24-IRG

Co-Authors

Isamu Tachibana, MD
Indiana University

Mark Green, PhD
Indiana University

Mark Tann, MD
Indiana University

Michael Koch, MD
Indiana University

Clinton Bahler, MD
Indiana University