Factors Associated with Occult Adverse Pathologic Features in Prostate Cancer Patients Eligible for Active Surveillance

Author Info

Ahmed Haddad Jaimin Trivedi Murali Ankem Samarpit Rai

Corresponding Author

Ahmed Haddad
Department of Urology, University of Louisville, Louisville, Kentucky, USA

A B S T R A C T

Purpose: We examined factors associated with the presence of occult adverse pathologic features at prostatectomy in patients otherwise eligible for active surveillance. Materials and Methods: Using the National Cancer Database, we identified all low and favorableintermediate risk prostate cancer patients diagnosed from 2010-2016. The cohort was randomly divided into test and validation groups. Logistic regression was used to identify factors associated with adverse pathology at prostatectomy. Kaplan Meier analysis was used to determine overall survival difference in men with or without adverse pathology. Results: Among 168,505 active surveillance eligible patients, 83,153 underwent radical prostatectomy. In men who received prostatectomy, the rate of occult adverse pathologic features defined as pT≥3b, Grade Group ≥ 4 or pN1 was exceedingly low (2.3-6.1%). The rate of adverse pathology was 15.85-35.1% when using a less restrictive definition (pT≥3a, Grade Group ≥ 3 or pN1). The number of positive biopsy cores was independently associated with an increased risk of adverse pathology (OR= 1.11, p<0.01). The absolute risk of adverse pathology remained low even at high positive core count. The AUC of the logistic model for prediction of adverse pathology improved with the addition of a number of positive biopsy cores to the NCCN criteria (0.610 to 0.649 in the test cohort and 0.638 in the validation cohort). 7-year overall survival was 93%, with no difference between patients with or without adverse pathologic features. Conclusion: We identified pre-surgical factors associated with occult adverse pathology in active surveillance patients who underwent prostatectomy. This model may help select patients for additional risk stratification with genomic assays or multiparametric MRI prior to treatment decisions.

Article Info

Article Type

Research Article

Publication history

Received: Fri 01, May 2020
Accepted: Thu 14, May 2020
Published: Thu 21, May 2020

Copyright

© 2023 Ahmed Haddad. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Hosting by Science Repository.
DOI: 10.31487/j.COR.2020.05.08