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Indexed/Abstracted in: BIOSIS Previews, Current Contents/Clinical Medicine, EMBASE, PubMed/MEDLINE, Science Citation Index Expanded (SciSearch), Scopus
Impact Factor 1,6
Online ISSN 1827-1898
Domenico GABRIELE 1, Monica GARIBALDI 1, Giuseppe GIRELLI 2, Stefano TARAGLIO 3, Eleonora DUREGON 4, Pietro GABRIELE 5, Caterina GUIOT 1, Enrico BOLLITO 4, THE EUREKA-2 CONSORTIUM
1 Neuroscience Department, Human Physiology Section University of Torino, Turin, Italy; 2 Division of Radiation Oncology, Civile Hospital, Ivrea, Italy; 3 Division of Pathology, San Giovanni Bosco Hospital, Turin, Italy; 4 Division of Pathology, San Luigi Gonzaga University Hospital, Orbassano, Turin, Italy; 5 Division of Radiation Oncology, FPO‑IRCCS Cancer Center of Candiolo, Turin, Italy
BACKGROUND: This work aims to definitely show the ability of percentage of positive biopsy cores (%PC) to independently predict biochemical outcome beyond traditional pretreatment risk-factors in prostate cancer (PCa) patients treated with radiotherapy.
METHODS: A cohort of 2493 men belonging to the EUREKA-2 retrospective multicentric database on (PCa) and treated with external-beam radiation therapy (EBRT) as primary treatment comprised the study population (median follow-up 50 months). A Cox regression time to prostate-specific antigen (PSA) failure analysis was performed to evaluate the predictive power of %PC, both in univariate and multivariate settings, with age, pretreatment PSA, clinical-radiological staging, bioptic Gleason Score (bGS), RT dose and RT +/- ADT as covariates.
RESULTS: P statistics for %PC is lower than 0.001 both in univariate and multivariate models. %PC as a continuous variable yields an AUC of 69% in ROC curve analysis for biochemical relapse. Four classes of %PC (1-20%, 21-50%, 51-80% and 81-100%) distinctly split patients for risk of biochemical relapse (overall log-rank test P<0.0001), with biochemical progression free survival (bPFS) at 5-years ranging from 88% to 58% and 10-years bPFS ranging from 80% to 38%.
CONCLUSIONS: We strongly affirm the usefulness of %PC information beyond main risk factors (PSA, staging and bGS) in predicting biochemical recurrence after EBRT for PCa. The stratification of patients according to %PC may be valuable to further discriminate cases with favourable or adverse prognosis.