scholarly journals Addressing the contribution of previously described genetic and epidemiological risk factors associated with increased prostate cancer risk and aggressive disease within men from South Africa

BMC Urology ◽  
2013 ◽  
Vol 13 (1) ◽  
Author(s):  
Elizabeth A Tindall ◽  
MS Riana Bornman ◽  
Smit van Zyl ◽  
Alpheus M Segone ◽  
L Richard Monare ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
South Africa ◽  
Cancer Risk ◽  
Prostate Cancer Risk ◽  
Factors Associated ◽  
Aggressive Disease ◽  
Epidemiological Risk

scholarly journals Prostate cancer risk variants of the HOXB genetic locus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
William D. Dupont ◽  
Joan P. Breyer ◽  
Spenser H. Johnson ◽  
W. Dale Plummer ◽  
Jeffrey R. Smith
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Cancer Genetics ◽  
Genetic Locus ◽  
Familial Cancer ◽  
Prostate Cancer Risk ◽  
European Ancestry ◽  
Ovarian Cancer Screening ◽  
Hereditary Prostate Cancer ◽  
Aggressive Disease

AbstractThe G84E germline mutation of HOXB13 predisposes to prostate cancer and is clinically tested for familial cancer care. We investigated the HOXB locus to define a potentially broader contribution to prostate cancer heritability. We sought HOXB locus germline variants altering prostate cancer risk in three European-ancestry case–control study populations (combined 7812 cases and 5047 controls): the International Consortium for Prostate Cancer Genetics Study; the Nashville Familial Prostate Cancer Study; and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Multiple rare genetic variants had concordant and strong risk effects in these study populations and exceeded genome-wide significance. Independent risk signals were best detected by sentinel variants rs559612720 within SKAP1 (OR = 8.1, P = 2E−9) and rs138213197 (G84E) within HOXB13 (OR = 5.6, P = 2E−11), separated by 567 kb. Half of carriers inherited both risk alleles, while others inherited either alone. Under mutual adjustment, the variants separately carried 3.6- and 3.1-fold risk, respectively, while joint inheritance carried 11.3-fold risk. These risks were further accentuated among men meeting criteria for hereditary prostate cancer, and further still for those with early-onset or aggressive disease. Among hereditary prostate cancer cases diagnosed under age 60 and with aggressive disease, joint inheritance carried a risk of OR = 27.7 relative to controls, P = 2E−8. The HOXB sentinel variant pair more fully captured genetic risk for prostate cancer within the study populations than either variant alone.

scholarly journals Multi-cohort modeling strategies for scalable globally accessible prostate cancer risk tools

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Johanna Tolksdorf ◽  
Michael W. Kattan ◽  
Stephen A. Boorjian ◽  
Stephen J. Freedland ◽  
Karim Saba ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Family History ◽  
Cancer Risk ◽  
Risk Prediction ◽  
Prostate Biopsy ◽  
Prostate Cancer Risk ◽  
High Grade ◽  
Prediction Tools ◽  
History Of

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.

Androgen independent progression in prostate cancer: Risk factors

2003 ◽  
Vol 2 (1) ◽  
pp. 26
Author(s):  
C. Auzanneau ◽  
J. Irani ◽  
L. Dahmani ◽  
F. Ouaki ◽  
C. Pirès ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Cancer Risk ◽  
Prostate Cancer Risk ◽  
Cancer Risk Factors ◽  
Androgen Independent

Prostate cancer risk calculators for healthy population: A systematic review (Preprint)

2021 ◽  
Author(s):  
Antonio Bandala-Jacques ◽  
Kevin Daniel Castellanos Esquivel ◽  
Fernanda Pérez-Hurtado ◽  
Cristobal Hernández-Silva ◽  
Nancy Reynoso-Noverón
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Systematic Review ◽  
Cancer Risk ◽  
Digital Rectal Examination ◽  
Prostate Cancer Risk ◽  
Individual Risk ◽  
Healthy Population ◽  
Risk Of Cancer ◽  
The Impact

BACKGROUND Screening for prostate cancer has long been a debated, complex topic. The use of risk calculators for prostate cancer is recommended for determining patients’ individual risk of cancer and the subsequent need for a prostate biopsy. These tools could lead to a better discrimination of patients in need of invasive diagnostic procedures and for optimized allocation of healthcare resources OBJECTIVE To systematically review available literature on current prostate cancer risk calculators’ performance in healthy population, by comparing the impact factor of individual items on different cohorts, and the models’ overall performance. METHODS We performed a systematic review of available prostate cancer risk calculators targeted at healthy population. We included studies published from January 2000 to March 2021 in English, Spanish, French, Portuguese or German. Two reviewers independently decided for or against inclusion based on abstracts. A third reviewer intervened in case of disagreements. From the selected titles, we extracted information regarding the purpose of the manuscript, the analyzed calculators, the population for which it was calibrated, the included risk factors, and the model’s overall accuracy. RESULTS We included a total of 18 calculators across 53 different manuscripts. The most commonly analyzed ones were they PCPT and ERSPC risk calculators, developed from North American and European cohorts, respectively. Both calculators provided high precision for the diagnosis of aggressive prostate cancer (AUC as high as 0.798 for PCPT and 0.91 for ERSPC). We found 9 calculators developed from scratch for specific populations, which reached diagnostic precisions as high as 0.938. The most commonly included risk factors in the calculators were age, PSA levels and digital rectal examination findings. Additional calculators included race and detailed personal and family history CONCLUSIONS Both the PCPR and the ERSPC risk calculators have been successfully adapted for cohorts other than the ones they were originally created for with no loss of diagnostic accuracy. Furthermore, designing calculators from scratch considering each population’s sociocultural differences has resulted in risk tools that can be well adapted to be valid in more patients. The best risk calculator for prostate cancer will be that which was has been calibrated for its intended population and can be easily reproduced and implemented CLINICALTRIAL CRD42021242110

scholarly journals Appraising causal relationships of dietary, nutritional and physical-activity exposures with overall and aggressive prostate cancer: two-sample Mendelian-randomization study based on 79 148 prostate-cancer cases and 61 106 controls

2019 ◽  
Vol 49 (2) ◽  
pp. 587-596 ◽  
Author(s):  
Nabila Kazmi ◽  
Philip Haycock ◽  
Konstantinos Tsilidis ◽  
Brigid M Lynch ◽  
Therese Truong ◽  
...  
Keyword(s):  
Physical Activity ◽  
Prostate Cancer ◽  
Risk Factors ◽  
Cancer Risk ◽  
Serum Iron ◽  
Mendelian Randomization ◽  
Prostate Cancer Risk ◽  
Uk Biobank ◽  
Monounsaturated Fat ◽  
Aggressive Prostate Cancer

Abstract Background Prostate cancer is the second most common male cancer worldwide, but there is substantial geographical variation, suggesting a potential role for modifiable risk factors in prostate carcinogenesis. Methods We identified previously reported prostate cancer risk factors from the World Cancer Research Fund (WCRF)’s systematic appraisal of the global evidence (2018). We assessed whether each identified risk factor was causally associated with risk of overall (79 148 cases and 61 106 controls) or aggressive (15 167 cases and 58 308 controls) prostate cancer using Mendelian randomization (MR) based on genome-wide association-study summary statistics from the PRACTICAL and GAME-ON/ELLIPSE consortia. We assessed evidence for replication in UK Biobank (7844 prostate-cancer cases and 204 001 controls). Results WCRF identified 57 potential risk factors, of which 22 could be instrumented for MR analyses using single nucleotide polymorphisms. For overall prostate cancer, we identified evidence compatible with causality for the following risk factors (odds ratio [OR] per standard deviation increase; 95% confidence interval): accelerometer-measured physical activity, OR = 0.49 (0.33–0.72; P = 0.0003); serum iron, OR = 0.92 (0.86–0.98; P = 0.007); body mass index (BMI), OR = 0.90 (0.84–0.97; P = 0.003); and monounsaturated fat, OR = 1.11 (1.02–1.20; P = 0.02). Findings in our replication analyses in UK Biobank were compatible with our main analyses (albeit with wide confidence intervals). In MR analysis, height was positively associated with aggressive-prostate-cancer risk: OR = 1.07 (1.01–1.15; P = 0.03). Conclusions The results for physical activity, serum iron, BMI, monounsaturated fat and height are compatible with causality for prostate cancer. The results suggest that interventions aimed at increasing physical activity may reduce prostate-cancer risk, although interventions to change other risk factors may have negative consequences on other diseases.

scholarly journals Appraising causal relationships of dietary, nutritional and physical-activity exposures with overall and aggressive prostate cancer: two-sample Mendelian randomization study based on 79,148 prostate cancer cases and 61,106 controls

2019 ◽  
Author(s):  
Nabila Kazmi ◽  
Philip Haycock ◽  
Konstantinos Tsilidis ◽  
Brigid M. Lynch ◽  
Therese Truong ◽  
...  
Keyword(s):  
Physical Activity ◽  
Prostate Cancer ◽  
Risk Factors ◽  
Cancer Research ◽  
Cancer Risk ◽  
Serum Iron ◽  
Mendelian Randomization ◽  
Prostate Cancer Risk ◽  
Uk Biobank ◽  
Unsaturated Fat

SummaryBackgroundProstate cancer is the second most common male cancer worldwide, but there is substantial geographical variation suggesting a potential role for modifiable risk factors in prostate carcinogenesis.MethodsWe identified previously reported prostate cancer risk factors from the World Cancer Research Fund’s (WCRF) systematic appraisal of the global evidence (2018). We assessed whether each identified risk factor was causally associated with risk of overall (79,148 cases and 61,106 controls) or aggressive (15,167 cases and 58,308 controls) prostate cancer using Mendelian randomization (MR) based on genome wide association study (GWAS) summary statistics from the PRACTICAL and GAME-ON/ELLIPSE consortia. We assessed evidence for replication in UK Biobank (7,844 prostate cancer cases and 204,001 controls).FindingsWCRF identified 57 potential risk factors, of which 22 could be instrumented for MR analyses using single nucleotide polymorphisms (SNPs). In MR analyses for overall prostate cancer, we identified evidence compatible with causality for the following risk factors (odds ratio [OR] per standard deviation increase; 95% confidence interval): accelerometer-measured physical-activity, OR=0.49 (0.33-0.72; p=0.0003); serum iron, OR=0.92 (0.86-0.98; p=0.007); body mass index (BMI), OR=0.90 (0.84-0.97; p=0.003); and mono-unsaturated fat, OR=1.11 (1.02-1.20; p=0.02). Findings in our replication analyses in UK Biobank were compatible with our main analyses (albeit with wide confidence intervals). In MR analysis, height was positively associated with aggressive prostate cancer risk: OR=1.07 (1.01-1.15; p=0.03).InterpretationThe results for physical-activity, serum iron, BMI, mono-unsaturated fat and height are compatible with causality for prostate cancer but more research is needed to rule out violations of MR assumptions for some risk factors. The results suggest that interventions aimed at increasing physical activity may reduce prostate cancer risk, but the direction of effects of BMI, and iron are at odds with their effects on other diseases, so the overall public health impact of intervening on these need to be considered.FundingWorld Cancer Research Fund International (2015/1421), Cancer Research UK program grant (C18281/A19169), National Institute for Health Research, Bristol Biomedical Research Centre, and Victorian Cancer Agency (MCRF18005).

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