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

JMIR Cancer ◽  
10.2196/30430 ◽  
2021 ◽  
Author(s):  
Antonio Bandala-Jacques ◽  
Kevin Daniel Castellanos Esquivel ◽  
Fernanda Pérez-Hurtado ◽  
Cristobal Hernández-Silva ◽  
Nancy Reynoso-Noverón
Keyword(s):  
Prostate Cancer ◽  
Systematic Review ◽  
Cancer Risk ◽  
Prostate Cancer Risk ◽  
Healthy Population

scholarly journals The Association of Nighttime Fasting Duration and Prostate Cancer Risk: Results from the Multicase-Control (MCC) Study in Spain

Nutrients ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 2662
Author(s):  
Anna Palomar-Cros ◽  
Ana Espinosa ◽  
Kurt Straif ◽  
Beatriz Pérez-Gómez ◽  
Kyriaki Papantoniou ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Lower Risk ◽  
Night Shift ◽  
Prostate Cancer Risk ◽  
Meal Timing ◽  
Risk Of Cancer ◽  
Fasting Duration ◽  
Population Controls ◽  
Reduced Risk

Nighttime fasting has been inconclusively associated with a reduced risk of cancer. The purpose of this study was to investigate this association in relation to prostate cancer risk. We examined data from 607 prostate cancer cases and 848 population controls who had never worked in night shift work from the Spanish multicase-control (MCC) study, 2008–2013. Through an interview, we collected circadian information on meal timing at mid-age. We estimated odds ratios (OR) and 95% confidence intervals (CI) with unconditional logistic regression. After controlling for time of breakfast, fasting for more than 11 h overnight (the median duration among controls) was associated with a reduced risk of prostate cancer compared to those fasting for 11 h or less (OR = 0.77, 95% 0.54–1.07). Combining a long nighttime fasting and an early breakfast was associated with a lower risk of prostate cancer compared to a short nighttime fasting and a late breakfast (OR = 0.54, 95% CI 0.27–1.04). This study suggests that a prolonged nighttime fasting duration and an early breakfast may be associated with a lower risk of prostate cancer. Findings should be interpreted cautiously and add to growing evidence on the importance of chrononutrition in relation to cancer risk.

A Systematic Review of Vitamin D Receptor Gene Polymorphisms and Prostate Cancer Risk

2006 ◽  
Vol 175 (5) ◽  
pp. 1613-1623 ◽  
Author(s):  
Sonja I. Berndt ◽  
Jennifer L. Dodson ◽  
Wen-Yi Huang ◽  
Kristin K. Nicodemus
Keyword(s):  
Prostate Cancer ◽  
Systematic Review ◽  
Vitamin D ◽  
Cancer Risk ◽  
Vitamin D Receptor ◽  
Gene Polymorphisms ◽  
Receptor Gene ◽  
Prostate Cancer Risk ◽  
Vitamin D Receptor Gene ◽  
Receptor Gene Polymorphisms

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

scholarly journals First-degree family history of breast cancer is associated with prostate cancer risk: a systematic review and meta-analysis

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Zheng-Ju Ren ◽  
De-Hong Cao ◽  
Qin Zhang ◽  
Peng-Wei Ren ◽  
Liang-Ren Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prostate Cancer ◽  
Systematic Review ◽  
Family History ◽  
Cancer Risk ◽  
Meta Analysis ◽  
Prostate Cancer Risk ◽  
History Of

scholarly journals Effect of statins type on incident prostate cancer risk: a meta-analysis and systematic review

2017 ◽  
Vol 19 (6) ◽  
pp. 666 ◽  
Author(s):  
Lu Yang ◽  
Qiang Wei ◽  
Ping Tan ◽  
Chen Zhang ◽  
Shi-You Wei ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Systematic Review ◽  
Cancer Risk ◽  
Meta Analysis ◽  
Prostate Cancer Risk

Abstract 3327: Correlating blood-based DNA methylation markers and prostate cancer risk factors in African-American men

2018 ◽  
Author(s):  
Bernard Kwabi-Addo ◽  
Emmauel Moses-Fynn ◽  
Wei Tang ◽  
Desta Beyene ◽  
Victor Apprey ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Dna Methylation ◽  
African American ◽  
Cancer Risk ◽  
African American Men ◽  
Prostate Cancer Risk ◽  
Cancer Risk Factors

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 The impact of genetic variants in inflammatory-related genes on prostate cancer risk among men of African Descent: a case control study

2013 ◽  
Vol 11 (1) ◽  
Author(s):  
Dominique Z Jones ◽  
Camille Ragin ◽  
Nayla C Kidd ◽  
Rafael E Flores-Obando ◽  
Maria Jackson ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Genetic Variants ◽  
Case Control Study ◽  
African Descent ◽  
Prostate Cancer Risk ◽  
Case Control ◽  
The Impact ◽  
Control Study
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