A novel predictor of clinical progression in patients on active surveillance for prostate cancer

Auteurs-es

  • Guan Hee Tan
  • Antonio Finelli
  • Ardalan Ahmad
  • Marian S. Wettstein
  • Thenappan Chandrasekar
  • Alexandre R. Zlotta
  • Neil E. Fleshner
  • Robert J. Hamilton
  • Girish S. Kulkarni
  • Khaled Ajib
  • Gregory Nason
  • Nathan Perlis

DOI :

https://doi.org/10.5489/cuaj.6122

Mots-clés :

prostate cancer, active surveillance

Résumé

Introduction: Active surveillance (AS) is standard of care in low-risk prostate cancer (PCa). 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 followup. 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 (PFS) curves between TCLo density groups. Test characteristics of TCLo density were explored with receiver operating characteristic (ROC) curves.

Results: We included 181 patients who had CBx from 2012‒2015 and met inclusion criteria. The mean age of patients was 62.58 years (standard deviation [SD] 7.13) and median followup was 60.9 months (interquartile range [IQR] 23.4). A high TCLo density score (>0.05) was independently associated with time to CP (hazard ratio [HR] 4.70; 95% confidence interval [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.

Conclusions: 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 PCa.

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Publié-e

2019-06-17

Comment citer

Tan, G. H., Finelli, A., Ahmad, A., Wettstein, M. S., Chandrasekar, T. ., Zlotta, A. R., … Perlis, N. (2019). A novel predictor of clinical progression in patients on active surveillance for prostate cancer. Canadian Urological Association Journal, 13(8). https://doi.org/10.5489/cuaj.6122

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Original Research