Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2024 Mar 15;21(3):e1004362.
doi: 10.1371/journal.pmed.1004362. eCollection 2024 Mar.

Risk factors for prostate cancer: An umbrella review of prospective observational studies and mendelian randomization analyses

Affiliations
Meta-Analysis

Risk factors for prostate cancer: An umbrella review of prospective observational studies and mendelian randomization analyses

Huijie Cui et al. PLoS Med. .

Abstract

Background: The incidence of prostate cancer is increasing in older males globally. Age, ethnicity, and family history are identified as the well-known risk factors for prostate cancer, but few modifiable factors have been firmly established. The objective of this study was to identify and evaluate various factors modifying the risk of prostate cancer reported in meta-analyses of prospective observational studies and mendelian randomization (MR) analyses.

Methods and findings: We searched PubMed, Embase, and Web of Science from the inception to January 10, 2022, updated on September 9, 2023, to identify meta-analyses and MR studies on prostate cancer. Eligibility criteria for meta-analyses were (1) meta-analyses including prospective observational studies or studies that declared outcome-free at baseline; (2) evaluating the factors of any category associated with prostate cancer incidence; and (3) providing effect estimates for further data synthesis. Similar criteria were applied to MR studies. Meta-analysis was repeated using the random-effects inverse-variance model with DerSimonian-Laird method. Quality assessment was then conducted for included meta-analyses using AMSTAR-2 tool and for MR studies using STROBE-MR and assumption evaluation. Subsequent evidence grading criteria for significant associations in meta-analyses contained sample size, P values and 95% confidence intervals, 95% prediction intervals, heterogeneity, and publication bias, assigning 4 evidence grades (convincing, highly suggestive, suggestive, or weak). Significant associations in MR studies were graded as robust, probable, suggestive, or insufficient considering P values and concordance of effect directions. Finally, 92 selected from 411 meta-analyses and 64 selected from 118 MR studies were included after excluding the overlapping and outdated studies which were published earlier and contained fewer participants or fewer instrument variables for the same exposure. In total, 123 observational associations (45 significant and 78 null) and 145 causal associations (55 significant and 90 null) were categorized into lifestyle; diet and nutrition; anthropometric indices; biomarkers; clinical variables, diseases, and treatments; and environmental factors. Concerning evidence grading on significant associations, there were 5 highly suggestive, 36 suggestive, and 4 weak associations in meta-analyses, and 10 robust, 24 probable, 4 suggestive, and 17 insufficient causal associations in MR studies. Twenty-six overlapping factors between meta-analyses and MR studies were identified, with consistent significant effects found for physical activity (PA) (occupational PA in meta: OR = 0.87, 95% CI: 0.80, 0.94; accelerator-measured PA in MR: OR = 0.49, 95% CI: 0.33, 0.72), height (meta: OR = 1.09, 95% CI: 1.06, 1.12; MR: OR = 1.07, 95% CI: 1.01, 1.15, for aggressive prostate cancer), and smoking (current smoking in meta: OR = 0.74, 95% CI: 0.68, 0.80; smoking initiation in MR: OR = 0.91, 95% CI: 0.86, 0.97). Methodological limitation is that the evidence grading criteria could be expanded by considering more indices.

Conclusions: In this large-scale study, we summarized the associations of various factors with prostate cancer risk and provided comparisons between observational associations by meta-analysis and genetically estimated causality by MR analyses. In the absence of convincing overlapping evidence based on the existing literature, no robust associations were identified, but some effects were observed for height, physical activity, and smoking.

PubMed Disclaimer

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Flowchart of literature search, inclusion, and results.
MR, mendelian randomization.
Fig 2
Fig 2. Overall presentation of associations with the risk of prostate cancer.
(A) Observational associations from meta-analyses (Meta). (B) Causal associations from MR studies. Numbers presented in the graphs are OR with 95% confidence intervals. Different colors indicate different categories; ¶ represents significant associations (P < 0.05). Metrics with * denoting the outcome was advanced, aggressive, high-grade, or lethal prostate cancer, and metrics with # denoting the outcome was non-advanced, non-aggressive, or localized prostate cancer in graph (A). Metrics with * denoting the outcome of MR studies was aggressive prostate cancer, and metrics with # denoting the outcome of MR studies was early-onset prostate cancer in graph (B). Note that the null associations of biomarkers (N = 58) in MR studies are not presented here considering the graph size. Abbreviations in meta-analyses: PA, physical activity; DHA, docosahexaenoic acids; EPA, eicosapentaenoic; HDL, high-density lipoprotein; LDL, low-density lipoprotein; CRP, C-reactive protein; T2D, type 2 diabetes; BPH, benign prostate hyperplasia; HIV, human immunodeficiency virus; AIDS, acquired immune deficiency syndrome; CD, Crohn’s disease; UC, ulcerative colitis; AASVs, anti-neutrophil cytoplasm antibody associated vasculitides; ACEI, angiotensin converting enzyme inhibitors; NSAID, nonsteroidal anti-inflammatory drug; CCB, calcium channel blockers. Abbreviations in MR studies: PA, physical activity; BMI, body mass index; UFA, unfavorable adiposity; FA, favorable adiposity; LTL, leukocyte telomere length; CCL2, Chemokine (C-C motif) ligand 2; CCL4, Chemokine (C-C motif) ligand 4; TG, triglyceride; IGF, insulin-like growth factor; LDL, low-density lipoprotein; HGF, hepatocyte growth factor; IL-1ra, IL-1 receptor antagonist; MUFAs, monounsaturated fatty acids; TOR1AIP1, Torsin-1A-interacting protein 1; IL-6, interleukin-6; ALT, alanine aminotransferase; IDO 1, Indoleamine 2,3-dioxygenase 1; PDGF-bb, platelet-derived growth factor BB; SCGF-β, stem cell growth factor-beta; TSH, thyroid-stimulating hormone; β-NGF, beta nerve growth factor; M.VLDL.TG, Triglycerides in medium VLDL; MSP, microseminoprotein-beta; CCB, calcium channel blockers; PCSK9, proprotein convertase subtilisin/kexin type 9; PPARG, peroxisome proliferator activated receptor γ; ABCC8, ATP binding cassette subfamily C member 8; GLP1R, glucagon-like peptide 1 receptor; ACE, angiotensin-converting enzyme; ADRB1, β-1 adrenergic receptor; NCC, sodium-chloride symporter; SBP, systolic blood pressure; DBP, diastolic blood pressure; MDD, major depressive disorder; SLE, systemic lupus erythematosus; IBD, inflammatory bowel disease; CD, Crohn’s disease; UC, ulcerative colitis; T2D, type 2 diabetes; HMG-CoA, 3-hydroxy-3-methylglutaryl coenzyme A; NPC1L1, Niemann-Pick C1-Like 1. MR, mendelian randomization; OR, odds ratio.
Fig 3
Fig 3. Quality assessment of meta-analyses using AMSTAR-2.
The total number of meta-analyses included was 90. The items were scored as No (0 point), Partial yes (0.5 point), or Yes (1 point). Abbreviation: PI(E)CO, population, intervention or exposure, comparator, outcome.
Fig 4
Fig 4. Forest plot of evidence grading for significant associations with the risk of prostate cancer in categories from meta-analyses.
The statistical test to determine the P value in meta-analyses was the random-effects inverse-variance model with DerSimonian—Laird method. The pooled effect estimate OR of each association is represented by the green colored square and 95% CI by the horizontal lines. Metrics with * denoting the outcome was high-grade, aggressive, or advanced prostate cancer. PA, physical activity; CRP, C-reactive protein; T2D, type 2 diabetes; BPH, benign prostate hyperplasia; UC, ulcerative colitis; HIV, human immunodeficiency virus; AIDS, acquired immune deficiency syndrome; OR, odds ratio.
Fig 5
Fig 5. Forest plot of evidence grading for significant associations with the risk of prostate cancer in categories from MR studies.
The statistical test to determine the P value in MR study was the IVW regression analysis. The effect estimate OR of each association is represented by the blue colored square and 95% CI by the horizontal lines. Metrics with * denoting the outcome was high-grade, aggressive, or advanced prostate cancer. Metrics with # denoting the outcome was early-onset prostate cancer. Note that UFA meets the evidence criteria for probable though the P value for main analysis is larger than 0.05. SD, standard deviation; PA, physical activity; BMI, body mass index; LTL, leukocyte telomere length; CCL2, Chemokine (C-C motif) ligand 2; CCL4, Chemokine (C-C motif) ligand 4; TG, triglyceride; IGF, insulin-like growth factor; LDL, low-density lipoprotein; HGF, hepatocyte growth factor; IL-1ra, IL-1 receptor antagonist; MUFAs, monounsaturated fatty acids; TOR1AIP1, Torsin-1A-interacting protein 1; UFA, unfavorable adiposity; IL-6, interleukin-6; ALT, alanine aminotransferase; IDO 1, Indoleamine 2,3-dioxygenase 1; PDGF-bb, platelet-derived growth factor BB; SCGF-β, stem cell growth factor-beta; TSH, thyroid-stimulating hormone; β-NGF, beta nerve growth factor; M.VLDL.TG, Triglycerides in medium VLDL; MSP, microseminoprotein-beta; CCB, calcium channel blockers; PPARG, peroxisome proliferator activated receptor γ; PCSK9, proprotein convertase subtilisin/kexin type 9; SLE, systemic lupus erythematosus; IVW, inverse variance weighted; MR, mendelian randomization; OR, odds ratio.
Fig 6
Fig 6. Comparison between meta-analyses and MR studies.
The statistical test to determine the P value in meta-analyses was the random-effects inverse-variance model with DerSimonian—Laird method. The statistical test to determine the P value in MR study was the IVW regression analysis. The effect estimates OR from meta-analyses and MR studies are represented by the green and blue squares, respectively, and 95% CI by the horizontal lines. Metrics with * denoting the outcome was high-grade, aggressive, or advanced prostate cancer. NA, not available; SD, standard deviation; PA, physical activity; CRP, C-reactive protein; T2D, type 2 diabetes; UC, ulcerative colitis; LDL, low-density lipoprotein; BMI, body mass index; IVW, inverse variance weighted; MR, mendelian randomization; OR, odds ratio.

Similar articles

References

    1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al.. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–49. Epub 2021/02/05. doi: 10.3322/caac.21660 . - DOI - PubMed
    1. Sandhu S, Moore CM, Chiong E, Beltran H, Bristow RG, Williams SG. Prostate cancer. Lancet. 2021;398(10305):1075–90. Epub 2021/08/10. doi: 10.1016/S0140-6736(21)00950-8 . - DOI - PubMed
    1. Benke IN, Leitzmann MF, Behrens G, Schmid D. Physical activity in relation to risk of prostate cancer: a systematic review and meta-analysis. Ann Oncol. 2018;29(5):1154–79. Epub 2018/05/23. doi: 10.1093/annonc/mdy073 . - DOI - PubMed
    1. Hong S, Khil H, Lee DH, Keum N, Giovannucci EL. Alcohol Consumption and the Risk of Prostate Cancer: A Dose-Response Meta-Analysis. Nutrients. 2020;12(8). Epub 2020/07/29. doi: 10.3390/nu12082188 . - DOI - PMC - PubMed
    1. Amadou A, Freisling H, Jenab M, Tsilidis KK, Trichopoulou A, Boffetta P, et al.. Prevalent diabetes and risk of total, colorectal, prostate and breast cancers in an ageing population: meta-analysis of individual participant data from cohorts of the CHANCES consortium. Br J Cancer. 2021;124(11):1882–90. Epub 2021/03/28. doi: 10.1038/s41416-021-01347-4 . - DOI - PMC - PubMed

Publication types

Grants and funding

The National Natural Science Foundation of China: U22A20359, 81874283, and 81673255, granted to BZ; the National Key R&D Program of China: 2022YFC3600604, granted to BZ; the Recruitment Program for Young Professionals of China, the Promotion Plan for Basic Medical Sciences and the Development Plan for Cutting-Edge Disciplines, Sichuan University, and other Projects from West China School of Public Health and West China Fourth Hospital, Sichuan University, granted to BZ. The National Natural Science Foundation of China for young scholars: 82204170, granted to XJ; the National Natural Science Foundation of China for young outstanding scholars (overseas), granted to XJ. The sponsors or funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
-