The management of active surveillance in prostate cancer: validation of the Canary Prostate Active Surveillance Study risk calculator with the Spanish Urological Association Registry

Abstract

The follow up of patients on active surveillance requires to repeat prostate biopsies. Predictive models that identify patients at low risk of progression or reclassification are essential to reduce the number of unnecessary biopsies. The aim of this study is to validate the Prostate Active Surveillance Study risk calculator (PASS-RC) in the multicentric Spanish Urological Association Registry of patients on active surveillance (AS), from common clinical practice.ResultsWe find significant differences in age, PSA and clinical stage between our validation cohort and the PASS-RC generation cohort (p < .0001), with a reclassification rate of 10–22% on the follow-up Bx, no cancer was found in 43% of the first follow-up Bx. The calibration curve shows underestimation of real appearance of reclassification. The AUC is 0.65 (C.I.95%: 0.60–0.71). PDF and CUC do not suggest a specific cut-off point of clinical use.MethodsWe select 498 patients on AS with a minimum of one follow-up biopsy (Bx) from the 1,024 males registered by 36 Spanish centers recruiting patients on the Spanish Urological Association Registry on AS. PASS-RC external validation is carried by means of calibration curve and area under de ROC-curve (AUC), identifying cut-offs of clinical utility by probability density functions (PDF) and clinical utility curves (CUC).ConclusionsIn our first external validation of the PASS-RC we have obtained a moderate discrimination ability, although we cannot recommend cut-off points of clinical use. We suggest the exploration of new biomarkers and/or morpho-functional parameters from multiparametric magnetic resonance image, to improve those necessary tools on AS.

Role of Multiparametric Prostate Magnetic Resonance Imaging before Confirmatory Biopsy in Assessing the Risk of Prostate Cancer Progression during Active Surveillance

“…However, the study protocol during the follow-up of an AS patient was considerably different from the current protocols, which could invalidate the conclusion ( 9 ). To improve the safety of AS programs, some tools ( 10 ) and risk calculators ( 11 12 ) have been explored with mixed results. Further studies and recalibrations are still warranted to increase the widespread use of such programs.…”

Risk of progression following a negative biopsy in prostate cancer active surveillance

“…While our findings suggested limited ability to accurately predict serious upgrading among those with negative biopsy findings, several risk assessment tools with greater discriminatory ability are available for men on AS [ 21 ]. For example, the ‘Canary Active Surveillance Study Risk Calculator’ [ 22 ], which predicts grade reclassification based on age at diagnosis, latest PSA concentration, percentage of positive cores and prior number of negative biopsies, has moderately good discriminatory ability (area under receiver operating curve 0.74 in the original test cohort [ 22 ] and 0.65–0.68 in external validation datasets [ 23 , 24 ]). Likewise, modelling risk based on PSA velocity (PRIAS tool) provides moderate discrimination for upgrading in AS cohorts [ 25 ], suggesting that monitoring rates of change in PSA may be sufficient for men with negative biopsy findings.…”

Sample sizes of prediction model studies in prostate cancer were rarely justified and often insufficient

“…We chose to focus on CPMs within prostate cancer because this is a common context in which CPMs are developed in both a diagnostic and prognostic prediction setting. This is largely due to their many practical uses, including predicting disease onset [21]; risk stratification [22]; predicting risk of upgrading during active surveillance [23]; predicting risk of recurrence [24]; predicting risk of treatment toxicity [25]; and predicting survival [26].…”