scholarly journals Family history of prostate cancer and prostate cancer risk in the Alpha‐Tocopherol, Beta‐Carotene Cancer Prevention (ATBC) Study

2008 ◽  
Vol 123 (5) ◽  
pp. 1154-1159 ◽  
Author(s):  
Jiyoung Ahn ◽  
Roxana Moslehi ◽  
Stephanie J. Weinstein ◽  
Kirk Snyder ◽  
Jarmo Virtamo ◽  
...  
2015 ◽  
Vol 137 (9) ◽  
pp. 2124-2132 ◽  
Author(s):  
Alison M. Mondul ◽  
Steven C. Moore ◽  
Stephanie J. Weinstein ◽  
Edward D. Karoly ◽  
Joshua N. Sampson ◽  
...  

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.


BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Zheng-Ju Ren ◽  
De-Hong Cao ◽  
Qin Zhang ◽  
Peng-Wei Ren ◽  
Liang-Ren Liu ◽  
...  

2016 ◽  
Author(s):  
Lauren E. Barber ◽  
Travis A. Gerke ◽  
Sarah C. Markt ◽  
Giovanni Parmigiani ◽  
Lorelei A. Mucci

2014 ◽  
Vol 2 (2) ◽  
pp. 31-36
Author(s):  
Jean-Alfred Thomas II ◽  
Leah Gerber ◽  
Robert J. Hamilton ◽  
Adriana C. Vidal ◽  
Daniel M. Moreira ◽  
...  

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Alison M. Mondul ◽  
Steven C. Moore ◽  
Stephanie J. Weinstein ◽  
Anne M. Evans ◽  
Edward D. Karoly ◽  
...  

Background. The Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study, a randomized controlled cancer prevention trial, showed a 32% reduction in prostate cancer incidence in response to vitamin E supplementation. Two other trials were not confirmatory, however.Objective. We compared the change in serum metabolome of the ATBC Study participants randomized to receive vitamin E to those who were not by randomly selecting 50 men from each of the intervention groups (50 mg/day all-rac-α-tocopheryl acetate (ATA), 20 mg/dayβ-carotene, both, placebo).Methods. Metabolomic profiling was conducted on baseline and follow-up fasting serum (Metabolon, Inc.).Results. After correction for multiple comparisons, five metabolites were statistically significantly altered (βis the change in metabolite level expressed as number of standard deviations on the log scale):α-CEHC sulfate (β=1.51,p=1.45×10-38),α-CEHC glucuronide (β=1.41,p=1.02×10-31),α-tocopherol (β=0.97,p=2.22×10-13),γ-tocopherol (β=-0.90,p=1.76×10-11), andβ-tocopherol (β=-0.73,p=9.40×10-8). Glutarylcarnitine, beta-alanine, ornithine, and N6-acetyllysine were also decreased by ATA supplementation (βrange 0.40 to −0.36), but not statistically significantly.Conclusions. Comparison of the observed metabolite alterations resulting from ATA supplementation to those in other vitamin E trials of different populations, dosages, or formulations may shed light on the apparently discordant vitamin E-prostate cancer risk findings.


1995 ◽  
Vol 60 (3) ◽  
pp. 361-364 ◽  
Author(s):  
Richard B. Hayes ◽  
Jonathan M Liff ◽  
Linda M. Pottern ◽  
Raymond S. Greenberg ◽  
Janet B. Schoenberg ◽  
...  

2009 ◽  
Vol 181 (4S) ◽  
pp. 49-49
Author(s):  
Joshua J Meeks ◽  
Brian T Helfand ◽  
Stacy Loeb ◽  
Donghui Kan ◽  
Angela J Fought ◽  
...  

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