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 ◽  
...  

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).

2019 ◽  
Vol 49 (2) ◽  
pp. 587-596 ◽  
Author(s):  
Nabila Kazmi ◽  
Philip Haycock ◽  
Konstantinos Tsilidis ◽  
Brigid M Lynch ◽  
Therese Truong ◽  
...  

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.


Author(s):  
Eleanor L. Watts ◽  
Georgina K. Fensom ◽  
Karl Smith Byrne ◽  
Aurora Perez-Cornago ◽  
Naomi E. Allen ◽  
...  

AbstractBackgroundInsulin-like growth factor-I (IGF-I) and testosterone have been implicated in prostate cancer aetiology. Using newly available data from a large prospective full-cohort with standardised assays and repeat blood measurements, and genetic data from an international consortium, we aimed to investigate the associations of circulating concentrations of IGF-I, sex hormone-binding globulin (SHBG), total and calculated free testosterone with prostate cancer risk.Patients and methodsFor prospective analyses of prostate cancer incidence and mortality, we studied 199,698 male UK Biobank participants using Cox proportional hazards models. Multivariable-adjusted hazard ratios (HRs) were corrected for regression dilution bias using repeat hormone measurements from a subsample of up to 7,776 men. A 2-sample Mendelian randomization (MR) analysis of IGF-I and risk used genetic instruments identified from UK Biobank men and genetic outcome data from 79,148 cases and 61,106 controls from the PRACTICAL consortium. We used cis- and all (cis and trans) SNP MR approaches.ResultsAfter a mean follow-up of 6.9 years, 5,402 men were diagnosed with and 295 died from prostate cancer. Higher circulating IGF-I was associated with an elevated risk (HR per 5 nmol/L increment=1.09, 95% CI 1.05-1.12) and prostate cancer mortality (HR per 5 nmol/L increment=1.15,1.02-1.29) in observational analyses. Cis- and all SNPs MR analyses also supported the role of IGF-I in prostate cancer diagnosis (cis-MR odds ratio per 5 nmol/L increment=1.34,1.07-1.68). In observational analyses, higher free testosterone was associated with a higher risk of prostate cancer (HR per 50 pmol/L increment=1.10,1.05-1.15), and higher SHBG was associated with a lower risk of prostate cancer (HR per 10 nmol/L increment=0.95,0.94-0.97), but neither was associated with prostate cancer mortality. Total testosterone was not associated with prostate cancer.Conclusion(s)These findings implicate IGF-I and free testosterone in prostate cancer development and/or progression.Key messageProstate cancer is the second most common cancer in men, but modifiable risk factors have not been identified. Using large-scale prospective observational and genetic data we investigated the associations of circulating IGF-I, SHBG and testosterone with prostate cancer diagnosis and mortality. Our results implicate IGF-I and the sex hormones in prostate cancer development.HighlightsProstate cancer is the second most common cancer in men, but no modifiable risk factors are established.We examined the associations of circulating IGF-I, SHBG, total and free testosterone with prostate cancer risk in UK Biobank.Men with higher IGF-I had a higher risk of diagnosis and mortality. Mendelian randomization also supported a causal role.Men with higher free testosterone had a higher prostate cancer risk, and men with higher SHBG had a lower risk.The results implicate IGF-I and the sex hormones in prostate cancer development.


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.


2003 ◽  
Vol 2 (1) ◽  
pp. 26
Author(s):  
C. Auzanneau ◽  
J. Irani ◽  
L. Dahmani ◽  
F. Ouaki ◽  
C. Pirès ◽  
...  

2020 ◽  
Vol 9 (23) ◽  
pp. 9160-9167
Author(s):  
Xiong Chen ◽  
Jianqiu Kong ◽  
Xiayao Diao ◽  
Jiahao Cai ◽  
Junjiong Zheng ◽  
...  

2018 ◽  
Vol 110 (9) ◽  
pp. 1035-1038 ◽  
Author(s):  
James Yarmolinsky ◽  
Carolina Bonilla ◽  
Philip C Haycock ◽  
Ryan J Q Langdon ◽  
Luca A Lotta ◽  
...  

2021 ◽  
Author(s):  
Antonio Bandala-Jacques ◽  
Kevin Daniel Castellanos Esquivel ◽  
Fernanda Pérez-Hurtado ◽  
Cristobal Hernández-Silva ◽  
Nancy Reynoso-Noverón

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


2020 ◽  
Vol 29 (8) ◽  
pp. 1615-1626 ◽  
Author(s):  
Eleanor L. Watts ◽  
Aurora Perez-Cornago ◽  
Jaimal Kothari ◽  
Naomi E. Allen ◽  
Ruth C. Travis ◽  
...  

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