PURPOSE: To assess the prognostic value of the percentage of positive biopsy cores (PPC) and perineural invasion in predicting the clinical outcomes after radiotherapy (RT) for prostate cancer and to explore the possibilities to improve on existing risk-stratification models. METHODS AND MATERIALS: Between 1993 and 2004, 1,056 patients with clinical Stage T1c-T3N0M0 prostate cancer, who had four or more biopsy cores sampled and complete biopsy core data available, were treated with external beam RT, with or without a high-dose-rate brachytherapy boost at William Beaumont Hospital. The median follow-up was 7.6 years. Multivariate Cox regression analysis was performed with PPC, Gleason score, pretreatment prostate-specific antigen, T stage, PNI, radiation dose, androgen deprivation, age, prostate-specific antigen frequency, and follow-up duration. A new risk stratification (PPC classification) was empirically devised to incorporate PPC and replace the T stage. RESULTS: On multivariate Cox regression analysis, the PPC was an independent predictor of distant metastasis, cause-specific survival, and overall survival (all p < .05). A PPC >50% was associated with significantly greater distant metastasis (hazard ratio, 4.01; 95% confidence interval, 1.86-8.61), and its independent predictive value remained significant with or without androgen deprivation therapy (all p < .05). In contrast, PNI and T stage were only predictive for locoregional recurrence. Combining the PPC (≤50% vs. >50%) with National Comprehensive Cancer Network risk stratification demonstrated added prognostic value of distant metastasis for the intermediate-risk (hazard ratio, 5.44; 95% confidence interval, 1.78-16.6) and high-risk (hazard ratio, 4.39; 95% confidence interval, 1.70-11.3) groups, regardless of the use of androgen deprivation and high-dose RT (all p < .05). The proposed PPC classification appears to provide improved stratification of the clinical outcomes relative to the National Comprehensive Cancer Network classification. CONCLUSIONS: The PPC is an independent and powerful predictor of clinical outcomes of prostate cancer after RT. A risk model replacing T stage with the PPC to reduce subjectivity demonstrated potentially improved stratification.
PURPOSE: To assess the prognostic value of the percentage of positive biopsy cores (PPC) and perineural invasion in predicting the clinical outcomes after radiotherapy (RT) for prostate cancer and to explore the possibilities to improve on existing risk-stratification models. METHODS AND MATERIALS: Between 1993 and 2004, 1,056 patients with clinical Stage T1c-T3N0M0 prostate cancer, who had four or more biopsy cores sampled and complete biopsy core data available, were treated with external beam RT, with or without a high-dose-rate brachytherapy boost at William Beaumont Hospital. The median follow-up was 7.6 years. Multivariate Cox regression analysis was performed with PPC, Gleason score, pretreatment prostate-specific antigen, T stage, PNI, radiation dose, androgen deprivation, age, prostate-specific antigen frequency, and follow-up duration. A new risk stratification (PPC classification) was empirically devised to incorporate PPC and replace the T stage. RESULTS: On multivariate Cox regression analysis, the PPC was an independent predictor of distant metastasis, cause-specific survival, and overall survival (all p < .05). A PPC >50% was associated with significantly greater distant metastasis (hazard ratio, 4.01; 95% confidence interval, 1.86-8.61), and its independent predictive value remained significant with or without androgen deprivation therapy (all p < .05). In contrast, PNI and T stage were only predictive for locoregional recurrence. Combining the PPC (≤50% vs. >50%) with National Comprehensive Cancer Network risk stratification demonstrated added prognostic value of distant metastasis for the intermediate-risk (hazard ratio, 5.44; 95% confidence interval, 1.78-16.6) and high-risk (hazard ratio, 4.39; 95% confidence interval, 1.70-11.3) groups, regardless of the use of androgen deprivation and high-dose RT (all p < .05). The proposed PPC classification appears to provide improved stratification of the clinical outcomes relative to the National Comprehensive Cancer Network classification. CONCLUSIONS: The PPC is an independent and powerful predictor of clinical outcomes of prostate cancer after RT. A risk model replacing T stage with the PPC to reduce subjectivity demonstrated potentially improved stratification.
Authors: Zachary S Zumsteg; Zinan Chen; Lauren E Howard; Christopher L Amling; William J Aronson; Matthew R Cooperberg; Christopher J Kane; Martha K Terris; Daniel E Spratt; Howard M Sandler; Stephen J Freedland Journal: Prostate Date: 2017-10-10 Impact factor: 4.104
Authors: Arash O Naghavi; Tobin J Strom; Kevin Nethers; Alex A Cruz; Nicholas B Figura; Kushagra Shrinath; Binglin Yue; Jongphil Kim; Matthew C Biagioli; Daniel C Fernandez; Randy V Heysek; Richard B Wilder Journal: Int J Clin Oncol Date: 2014-09-06 Impact factor: 3.402
Authors: Benedict Oerther; Moritz V Buren; Christina M Klein; Simon Kirste; Nils H Nicolay; Tanja Sprave; Simon Spohn; Deepa Darshini Gunashekar; Leonard Hagele; Lars Bielak; Michael Bock; Anca-L Grosu; Fabian Bamberg; Matthias Benndorf; Constantinos Zamboglou Journal: In Vivo Date: 2020 Nov-Dec Impact factor: 2.155
Authors: Jure Murgic; Matthew H Stenmark; Schuyler Halverson; Kevin Blas; Felix Y Feng; Daniel A Hamstra Journal: Radiat Oncol Date: 2012-08-01 Impact factor: 3.481