PURPOSE: We examined if the percent of positive biopsies is associated with features of biologically aggressive prostate cancer, biochemical progression and development of distant metastases in patients undergoing radical prostatectomy (RP). MATERIALS AND METHODS: Multivariate analyses of preoperative features in 605 consecutive patients who underwent RP for clinically localized disease were evaluated to determine the association between the percent positive biopsy cores (PosBx), pathological stage and grade, and biochemical progression following RP. The percent of PosBx cores was defined using the formula, (number of positive biopsy cores/total number of biopsy cores) x 100. RESULTS: The mean number of biopsy cores and percent PosBx cores +/- SE was 8.8 +/- 6.0 and 31.4 +/-21.1, respectively. Higher percent PosBx was significantly associated with higher preoperative prostate specific antigen (PSA), extracapsular extension, seminal vesicle invasion, positive surgical margins, higher final Gleason sum, lymphovascular invasion, perineural invasion and metastases to regional lymph nodes. On multivariate analyses adjusted for the effects of standard preoperative features percent PosBx was associated with nonorgan confined disease, seminal vesicle invasion and biochemical progression after surgery (p = 0.049, 0.050 and 0.006, respectively). Percent PosBx retained its independent association with PSA progression after adjustment for the effects of postoperative pathological features (p = 0.015). Higher percent PosBx was associated with shorter PSA doubling time after PSA progression, and an increased risk of distant metastases and overall mortality (p = 0.039, 0.001 and 0.018, respectively). CONCLUSIONS: Percent PosBx is associated with established pathological features, biochemical progression, distant metastases and overall death in patients who undergo RP for clinically localized disease. Percent PosBx should be included in preoperative predictive models for prognosticating outcomes after primary treatment and it may assist in selecting patients for inclusion in neoadjuvant and/or adjuvant therapy trials.
PURPOSE: We examined if the percent of positive biopsies is associated with features of biologically aggressive prostate cancer, biochemical progression and development of distant metastases in patients undergoing radical prostatectomy (RP). MATERIALS AND METHODS: Multivariate analyses of preoperative features in 605 consecutive patients who underwent RP for clinically localized disease were evaluated to determine the association between the percent positive biopsy cores (PosBx), pathological stage and grade, and biochemical progression following RP. The percent of PosBx cores was defined using the formula, (number of positive biopsy cores/total number of biopsy cores) x 100. RESULTS: The mean number of biopsy cores and percent PosBx cores +/- SE was 8.8 +/- 6.0 and 31.4 +/-21.1, respectively. Higher percent PosBx was significantly associated with higher preoperative prostate specific antigen (PSA), extracapsular extension, seminal vesicle invasion, positive surgical margins, higher final Gleason sum, lymphovascular invasion, perineural invasion and metastases to regional lymph nodes. On multivariate analyses adjusted for the effects of standard preoperative features percent PosBx was associated with nonorgan confined disease, seminal vesicle invasion and biochemical progression after surgery (p = 0.049, 0.050 and 0.006, respectively). Percent PosBx retained its independent association with PSA progression after adjustment for the effects of postoperative pathological features (p = 0.015). Higher percent PosBx was associated with shorter PSA doubling time after PSA progression, and an increased risk of distant metastases and overall mortality (p = 0.039, 0.001 and 0.018, respectively). CONCLUSIONS: Percent PosBx is associated with established pathological features, biochemical progression, distant metastases and overall death in patients who undergo RP for clinically localized disease. Percent PosBx should be included in preoperative predictive models for prognosticating outcomes after primary treatment and it may assist in selecting patients for inclusion in neoadjuvant and/or adjuvant therapy trials.
Authors: Jouhyun Jeon; Ekaterina Olkhov-Mitsel; Honglei Xie; Cindy Q Yao; Fang Zhao; Sahar Jahangiri; Carmelle Cuizon; Seville Scarcello; Renu Jeyapala; John D Watson; Michael Fraser; Jessica Ray; Kristina Commisso; Andrew Loblaw; Neil E Fleshner; Robert G Bristow; Michelle Downes; Danny Vesprini; Stanley Liu; Bharati Bapat; Paul C Boutros Journal: J Natl Cancer Inst Date: 2020-03-01 Impact factor: 13.506
Authors: Ramzi Rajab; Gabrielle Fisher; Michael W Kattan; Christopher S Foster; Tim Oliver; Henrik Møller; Victor Reuter; Peter Scardino; Jack Cuzick; Daniel M Berney Journal: Virchows Arch Date: 2010-09-09 Impact factor: 4.064
Authors: D M Berney; F Algaba; P Camparo; E Compérat; D Griffiths; G Kristiansen; A Lopez-Beltran; R Montironi; M Varma; L Egevad Journal: Virchows Arch Date: 2014-03-04 Impact factor: 4.064