The relevance of serum levels of long chain omega-3 polyunsaturated fatty acids and prostate cancer risk: A Meta-analysis

Objective: Our objective was to systematically analyze the evidence for an association between serum level long chain omega-3 polyunsaturated fatty acid (n-3 PUFA) and prostate cancer risk from human epidemiological studies.Study Procedures: We searched biomedical literature databases up to November 2011 and included epidemiological studies with description of long chain n-3 PUFA and incidence of prostate cancer in humans. Critical appraisal was done by two independent reviewers. Data were pooled using the general variance-based method with random-effects model; effect estimates were expressed as risk ratio with 95% confidence interval (CI). Heterogeneity was assessed by Chi2 and quantified by I2, publication bias was also determined.Results: In total, 12 studies were included. Significant negative association was noted between high serum level of n-3 PUFA docosapentaenoicacid (DPA) and total prostate cancer risk (RR:0.756;95% CI 0.599, 0.955; p = 0.019). Likewise, a positive association between high blood level of fish oil contents, eicosapentaenoicacid (EPA) and docosahexaenoic acid (DHA), and high-grade prostate tumour incidence (RR:1.381; 95% CI 1.050, 1.817; p = 0.021) was noted; however, this finding was evident only after adjustment was done on interstudy variability through the removal of a lower quality study from the pool.Conclusions: High serum levels of long chain n-3 PUFA DPA is associated with reduced total prostate cancer risk. While high blood level of EPA and DHA is possibly associated with increased high-grade prostate tumour risk.

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Blood Level Omega-3 Fatty Acids as Risk Determinant Molecular Biomarker for Prostate Cancer

Prostate Cancer ◽

10.1155/2013/875615 ◽

2013 ◽

Vol 2013 ◽

pp. 1-15 ◽

Cited By ~ 9

Author(s):

Mishell Kris Sorongon-Legaspi ◽

Michael Chua ◽

Maria Christina Sio ◽

Marcelino Morales

Keyword(s):

Prostate Cancer ◽

Cancer Risk ◽

Blood Level ◽

Prostate Cancer Risk ◽

Positive Association ◽

Case Control ◽

Blood Levels ◽

High Grade ◽

Omega 3 ◽

High Blood Level

Previous researches involving dietary methods have shown conflicting findings. Authors sought to assess the association of prostate cancer risk with blood levels of omega-3 polyunsaturated fatty acids (n-3 PUFA) through a meta-analysis of human epidemiological studies in available online databases (July, 2012). After critical appraisal by two independent reviewers, Newcastle-Ottawa Quality Assessment Scale (NOQAS) was used to grade the studies. Six case control and six nested case control studies were included. Results showed nonsignificant association of overall effect estimates with total or advanced prostate cancer or high-grade tumor. High blood level of alpha-linolenic acid (ALA) had nonsignificant positive association with total prostate cancer risk. High blood level of docosapentaenoic acid (DPA) had significant negative association with total prostate cancer risk. Specific n-3 PUFA in fish oil, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) had positive association with high-grade prostate tumor risk only after adjustment of interstudy variability. There is evidence that high blood level of DPA that is linked with reduced total prostate cancer risk and elevated blood levels of fish oils, EPA, and DHA is associated with high-grade prostate tumor, but careful interpretation is needed due to intricate details involved in prostate carcinogenesis and N-3 PUFA metabolism.

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A Scoping Review of Interactions between Omega-3 Long-Chain Polyunsaturated Fatty Acids and Genetic Variation in Relation to Cancer Risk

Nutrients ◽

10.3390/nu12061647 ◽

2020 ◽

Vol 12 (6) ◽

pp. 1647

Author(s):

Karin Yurko-Mauro ◽

Mary Van Elswyk ◽

Lynn Teo

Keyword(s):

Prostate Cancer ◽

Fatty Acids ◽

Cancer Risk ◽

Polyunsaturated Fatty Acids ◽

Scoping Review ◽

Genetic Variants ◽

Prostate Cancer Risk ◽

Lymphocytic Leukemia ◽

Omega 3 ◽

Long Chain

This scoping review examines the interaction of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) and genetic variants of various types of cancers. A comprehensive search was performed to identify controlled and observational studies conducted through August 2017. Eighteen unique studies were included: breast cancer (n = 2), gastric cancer (n = 1), exocrine pancreatic cancer (n = 1), chronic lymphocytic leukemia (n = 1), prostate cancer (n = 7) and colorectal cancer (n = 6). An additional 13 studies that focused on fish intake or at-risk populations were summarized to increase readers’ understanding of the topic based on this review, DHA and EPA interact with certain genetic variants to decrease breast, colorectal and prostate cancer risk, although data was limited and identified polymorphisms were heterogeneous. The evidence to date demonstrates that omega-3 long-chain polyunsaturated fatty acids (n-3 LC-PUFA) may decrease cancer risk by affecting genetic variants of inflammatory pathways, oxidative stress and tumor apoptosis. Collectively, data supports the notion that once a genetic variant is identified, the benefits of a targeted, personalized therapeutic regimen that includes DHA and/or EPA should be considered.

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

BMC Medical Research Methodology ◽

10.1186/s12874-019-0839-0 ◽

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.

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