Open AccessA novel predictor of clinical progression in patients on active surveillance for prostate cancer
Author(s) -
Guan Hee Tan,
Antonio Finelli,
Ardalan E. Ahmad,
Marian S. Wettstein,
Thenappan Chandrasekar,
Alexandre R. Zlotta,
Neil Fleshner,
Robert J. Hamilton,
Girish S. Kulkarni,
Khaled Ajib,
Gregory J. Nason,
Nathan Perlis
Publication year - 2019
Publication title -
canadian urological association journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.477
H-Index - 38
eISSN - 1920-1214
pISSN - 1911-6470
DOI - 10.5489/cuaj.6122
Subject(s) - medicine , prostate cancer , receiver operating characteristic , proportional hazards model , biopsy , urology , cancer , area under the curve , oncology , gastroenterology
Active surveillance (AS) is standard of care in low-risk prostate cancer (PC). This study describes a novel total cancer location (TCLo) density metric and aims to determine its performance in predicting clinical progression (CP) and grade progression (GP).
Methods: This was a retrospective study of patients on AS after confirmatory biopsy (CBx). We excluded patients with Gleason ≥7 at CBx and <2 years follow-up. TCLo was the number of locations with positive cores at diagnosis (DBx) and CBx. TCLo density was TCLo / prostate volume (PV). CP was progression to any active treatment while GP occurred if Gleason ≥7 was identified on repeat biopsy or surgical pathology. Independent predictors of time to CP or GP were estimated with Cox regression. Kaplan-Meier analysis compared progression-free survival curves between TCLo density groups. Test characteristics of TCLo were explored with receiver operating characteristic (ROC) curves.
Results: We included 181 patients who had CBx between 2012-2015, and met inclusion criteria. The mean age of patients was 62.58 years (SD=7.13) and median follow-up was 60.9 months (IQR=23.4). A high TCLo density score (>0.05) was independently associated with time to CP (HR 4.70, 95% CI: 2.62-8.42, p<0.001), and GP (HR 3.85, 95% CI: 1.91-7.73, p<0.001). ROC curves showed TCLo density has greater area under the curve than number of positive cores at CBx in predicting progression.
Conclusion: TCLo density is able to stratify patients on AS for risk of CP and GP. With further validation, it could be added to the decision-making algorithm in AS for low-risk localized PC.