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      Age at Menarche and Risk of Colorectal Cancer: A Meta-Analysis

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          Abstract

          Background

          Various observational studies have focused on the relationship between menarcheal age and the risk of colorectal cancer (CRC). However, the association is still controversial because of inconsistent results. Therefore, we performed a meta-analysis to assess this issue from epidemiological studies.

          Methods

          After a literature search in MEDLINE, EMBASE, and Web of Science for studies of menarcheal age and CRC risk published through the end of January 2013, we pooled the relative risks (RRs) from included studies using a fixed- or random-effects model and performed heterogeneity and publication bias analyses. All statistical tests were two-sided.

          Results

          Eleven case-control and 11 cohort studies were eligible for inclusion in our analysis. The random-effects pooled RR for oldest versus youngest menarcheal age was 0.95 [95% confidence intervals (CIs) = 0.85–1.06], with significant heterogeneity ( Q = 61.03, P<0.001, I 2 = 65.6%). When separately analyzed, case-control (RR = 0.95, 95% CI = 0.75–1.21) and cohort studies (RR = 0.97, 95% CI = 0.90–1.04) yielded similar results. Moreover, similar results were also observed among the subgroup analyses by study quality, population, exposure assessment, anatomic cancer site, subsite of colon cancer, and several potential important confounders and risk factors. There was no evidence of publication bias and significant heterogeneity between subgroups detected by meta-regression analyses.

          Conclusions

          Findings from this meta-analysis demonstrated that menarcheal age was not associated with the risk of CRC in humans. Further studies are warranted to stratify results by the subsite of colon cancer and menopause status in the future.

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          Most cited references54

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          Global cancer statistics

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            Facilitating meta-analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category.

            Epidemiological studies relating a particular exposure to a specified disease may present their results in a variety of ways. Often, results are presented as estimated odds ratios (or relative risks) and confidence intervals (CIs) for a number of categories of exposure, for example, by duration or level of exposure, compared with a single reference category, often the unexposed. For systematic literature review, and particularly meta-analysis, estimates for an alternative comparison of the categories, such as any exposure versus none, may be required. Obtaining these alternative comparisons is not straightforward, as the initial set of estimates is correlated. This paper describes a method for estimating these alternative comparisons based on the ideas originally put forward by Greenland and Longnecker, and provides implementations of the method, developed using Microsoft Excel and SAS. Examples of the method based on studies of smoking and cancer are given. The method also deals with results given by categories of disease (such as histological types of a cancer). The method allows the use of a more consistent comparison when summarizing published evidence, thus potentially improving the reliability of a meta-analysis. Copyright (c) 2007 John Wiley & Sons, Ltd.
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              Nonlinear reduction in risk for colorectal cancer by fruit and vegetable intake based on meta-analysis of prospective studies.

              The association between fruit and vegetable intake and colorectal cancer risk has been investigated by many studies but is controversial because of inconsistent results and weak observed associations. We summarized the evidence from cohort studies in categorical, linear, and nonlinear, dose-response meta-analyses. We searched PubMed for studies of fruit and vegetable intake and colorectal cancer risk that were published until the end of May 2010. We included 19 prospective studies that reported relative risk estimates and 95% confidence intervals (CIs) of colorectal cancer-associated with fruit and vegetable intake. Random effects models were used to estimate summary relative risks. The summary relative risk for the highest vs the lowest intake was 0.92 (95% CI: 0.86-0.99) for fruit and vegetables combined, 0.90 (95% CI: 0.83-0.98) for fruit, and 0.91 (95% CI: 0.86-0.96) for vegetables (P for heterogeneity=.24, .05, and .54, respectively). The inverse associations appeared to be restricted to colon cancer. In linear dose-response analysis, only intake of vegetables was significantly associated with colorectal cancer risk (summary relative risk=0.98; 95% CI: 0.97-0.99), per 100 g/d. However, significant inverse associations emerged in nonlinear models for fruits (Pnonlinearity<.001) and vegetables (Pnonlinearity=.001). The greatest risk reduction was observed when intake increased from very low levels of intake. There was generally little evidence of heterogeneity in the analyses and there was no evidence of small-study bias. Based on meta-analysis of prospective studies, there is a weak but statistically significant nonlinear inverse association between fruit and vegetable intake and colorectal cancer risk. Copyright © 2011 AGA Institute. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                6 June 2013
                : 8
                : 6
                : e65645
                Affiliations
                [1 ]Department of Gastroenterology, the First Affiliated Hospital of Dalian Medical University, Dalian, China
                [2 ]Department of Pathology, Dalian Medical University, Dalian, China
                [3 ]Laboratory Center for Diagnostics, Dalian Medical University, Dalian, China
                [4 ]Fudan University, Shanghai, China
                [5 ]Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
                MOE Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: C-YL Q-JW H-CL. Performed the experiments: C-YL Q-JW. Analyzed the data: C-YL Q-JW. Contributed reagents/materials/analysis tools: C-YL BS Y-YW HM S-BG L-NL H-CL Q-JW. Wrote the paper: C-YL. Approved the final manuscript: C-YL BS Y-YW HM S-BG L-NL H-CL Q-JW. Had full access to all of the data and the final responsibility for the decision to submit for publication: C-YL.

                Article
                PONE-D-13-11685
                10.1371/journal.pone.0065645
                3675201
                23762403
                ded9ac27-74d0-4080-9523-2358f7350d4d
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 March 2013
                : 25 April 2013
                Page count
                Pages: 7
                Funding
                These authors have no support or funding to report.
                Categories
                Research Article
                Medicine
                Clinical Research Design
                Meta-Analyses
                Epidemiology
                Cancer Epidemiology
                Clinical Epidemiology
                Environmental Epidemiology
                Gastroenterology and Hepatology
                Colon
                Gastrointestinal Cancers
                Global Health
                Obstetrics and Gynecology
                Menstrual Abnormalities
                Oncology
                Cancer Risk Factors
                Hormonal Causes of Cancer
                Lifestyle Causes of Cancer

                Uncategorized
                Uncategorized

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