Prostate Cancer Diagnosis Among Men With Isolated High-Grade Intraepithelial Neoplasia Enrolled Onto a 3-Year Prospective Phase III Clinical Trial of Oral Toremifene

2013 ◽  
Vol 31 (5) ◽  
pp. 523-529 ◽  
Author(s):  
Samir S. Taneja ◽  
Ronald Morton ◽  
Gary Barnette ◽  
Paul Sieber ◽  
Michael L. Hancock ◽  
...  

PurposeProstate cancer (PCa) prevention remains an appealing strategy for the reduction of overtreatment and secondary adverse effects. We evaluated the efficacy of toremifene citrate 20 mg in PCa prevention among men with isolated high-grade prostatic intraepithelial neoplasia (HGPIN) on biopsy.Patients and MethodsOne thousand five hundred ninety men with HGPIN, or HGPIN and atypia, and no PCa on prostate biopsy were randomly assigned 1:1 to receive toremifene citrate 20 mg or placebo in a 3-year phase III, double-blind, multicenter trial. Men underwent annual biopsy until cancer detection or study end. Efficacy analysis was performed in 1,467 men who underwent at least one on-study biopsy. Baseline risk factors were evaluated to determine influence on cancer detection.ResultsCancer was detected in 34.7% and 32.3% of men in the placebo and treatment groups, respectively, with no observed difference (P = .39, log-rank test) in PCa-free survival. The 3-year Kaplan-Meier PCa-free survival estimate was 54.9% (99% CI, 43.3% to 66.5%) in the placebo group and 59.5% (99% CI, 48.1% to 70.9%) in the treatment group. Exploration of baseline risk factors demonstrated no subset in which a risk reduction was observed. In the placebo group, 17.9%, 12.9%, and 13.6% of men at risk at the beginning of years 1, 2, and 3, respectively, were diagnosed with PCa.ConclusionAlthough toremifene 20 mg did not lower the PCa detection rate, men with isolated HGPIN have a high likelihood of eventual PCa diagnosis, demonstrating they are ideal candidates for inclusion in chemoprevention trials and require surveillance by periodic prostate biopsy.

2016 ◽  
Vol 35 (5) ◽  
pp. 721-728 ◽  
Author(s):  
Daimantas Milonas ◽  
Stasys Auskalnis ◽  
Giedrius Skulcius ◽  
Inga Gudinaviciene ◽  
Mindaugas Jievaltas ◽  
...  

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Johanna Tolksdorf ◽  
Michael W. Kattan ◽  
Stephen A. Boorjian ◽  
Stephen J. Freedland ◽  
Karim Saba ◽  
...  

Abstract Background Online clinical risk prediction tools built on data from multiple cohorts are increasingly being utilized for contemporary doctor-patient decision-making and validation. This report outlines a comprehensive data science strategy for building such tools with application to the Prostate Biopsy Collaborative Group prostate cancer risk prediction tool. Methods We created models for high-grade prostate cancer risk using six established risk factors. The data comprised 8492 prostate biopsies collected from ten institutions, 2 in Europe and 8 across North America. We calculated area under the receiver operating characteristic curve (AUC) for discrimination, the Hosmer-Lemeshow test statistic (HLS) for calibration and the clinical net benefit at risk threshold 15%. We implemented several internal cross-validation schemes to assess the influence of modeling method and individual cohort on validation performance. Results High-grade disease prevalence ranged from 18% in Zurich (1863 biopsies) to 39% in UT Health San Antonio (899 biopsies). Visualization revealed outliers in terms of risk factors, including San Juan VA (51% abnormal digital rectal exam), Durham VA (63% African American), and Zurich (2.8% family history). Exclusion of any cohort did not significantly affect the AUC or HLS, nor did the choice of prediction model (pooled, random-effects, meta-analysis). Excluding the lowest-prevalence Zurich cohort from training sets did not statistically significantly change the validation metrics for any of the individual cohorts, except for Sunnybrook, where the effect on the AUC was minimal. Therefore the final multivariable logistic model was built by pooling the data from all cohorts using logistic regression. Higher prostate-specific antigen and age, abnormal digital rectal exam, African ancestry and a family history of prostate cancer increased risk of high-grade prostate cancer, while a history of a prior negative prostate biopsy decreased risk (all p-values < 0.004). Conclusions We have outlined a multi-cohort model-building internal validation strategy for developing globally accessible and scalable risk prediction tools.


2014 ◽  
Vol 32 (3) ◽  
pp. 206-211 ◽  
Author(s):  
Kyung Park ◽  
James T. Dalton ◽  
Ramesh Narayanan ◽  
Christopher E. Barbieri ◽  
Michael L. Hancock ◽  
...  

Purpose High-grade prostatic intraepithelial neoplasia (HGPIN) is considered a precursor lesion of prostate cancer (PCa). The predictive value of ERG gene fusion in HGPIN for PCa was interrogated as a post hoc analysis in the context of a randomized clinical trial. Patients and Methods The GTx Protocol G300104 randomly assigned 1,590 men with biopsy-diagnosed HGPIN to receive toremifene or placebo for 3 years or until a diagnosis of PCa was made on prostate biopsy. As part of this phase III clinical trial, a central pathologist evaluated biopsies of patients with isolated HGPIN at baseline and 12, 24, and 36 months of follow-up. ERG immunohistochemistry was performed on biopsies from 461 patients and evaluated for protein overexpression. Results ERG expression was detected in 11.1% of patients (51 of 461 patients) with isolated HGPIN. In the first year and during the 3-year clinical trial, 14.7% and 36.9% of 461 patients were diagnosed with PCa, respectively. Patients with ERG expression were more likely to develop PCa, with 27 (53%) of 51 ERG-positive and 143 (35%) of 410 ERG-negative patients experiencing progression to PCa (P = .014, Fisher's exact test). ERG expression was not associated with age, baseline PSA, Gleason score, or tumor volume. Conclusion This study underscores the necessity of more stringent follow-up for men with HGPIN that is also positive for ERG overexpression. Clinicians should consider molecular characterization of HGPIN as a means to improve risk stratification.


2014 ◽  
Vol 13 (2) ◽  
pp. e1178
Author(s):  
D. Milonas ◽  
G. Skulcius ◽  
S. Auskalnis ◽  
I. Gudinaviciene ◽  
M. Jievaltas

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