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      Association of coffee consumption with risk of colorectal cancer: a meta-analysis of prospective cohort studies

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          A meta-analysis was performed to assess the association of coffee consumption with colorectal cancer and to investigate the shape of the association. Relevant prospective cohort studies were identified by a comprehensive search of the PubMed, Embase and Web of Science databases from their inception through August 2015. Either a random-effects model or fixed-effects model was used to compute the pooled risk estimates when appropriate. Linear and nonlinear dose-response meta-analyses were also performed. Nineteen prospective cohort studies involving 2,046,575 participants and 22,629 patients with colorectal cancer were included. The risk of colon cancer was decreased by 7% for every 4 cups per day of coffee (RR=0.93, 95%CI, 0.88-0.99; P=0.199). There was a threshold approximately five cups of coffee per day, and the inverse association for colorectal cancer appeared to be stronger at a higher range of intake. However, a nonlinear association of rectal cancer with coffee consumption was not observed ( P for nonlinearity = 0.214). In conclusion, coffee consumption is significantly associated with a decreased risk of colorectal cancer at ≥ 5 cups per day of coffee consumption. The findings support the recommendations of including coffee as a healthy beverage for the prevention of colorectal cancer.

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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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            Regression models in clinical studies: determining relationships between predictors and response.

            Multiple regression models are increasingly being applied to clinical studies. Such models are powerful analytic tools that yield valid statistical inferences and make reliable predictions if various assumptions are satisfied. Two types of assumptions made by regression models concern the distribution of the response variable and the nature or shape of the relationship between the predictors and the response. This paper addresses the latter assumption by applying a direct and flexible approach, cubic spline functions, to two widely used models: the logistic regression model for binary responses and the Cox proportional hazards regression model for survival time data.
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              Caffeinated and Decaffeinated Coffee Consumption and Risk of Type 2 Diabetes: A Systematic Review and a Dose-Response Meta-analysis

              OBJECTIVE Previous meta-analyses identified an inverse association of coffee consumption with the risk of type 2 diabetes. However, an updated meta-analysis is needed because new studies comparing the trends of association for caffeinated and decaffeinated coffee have since been published. RESEARCH DESIGN AND METHODS PubMed and Embase were searched for cohort or nested case-control studies that assessed the relationship of coffee consumption and risk of type 2 diabetes from 1966 to February 2013. A restricted cubic spline random-effects model was used. RESULTS Twenty-eight prospective studies were included in the analysis, with 1,109,272 study participants and 45,335 cases of type 2 diabetes. The follow-up duration ranged from 10 months to 20 years. Compared with no or rare coffee consumption, the relative risk (RR; 95% CI) for diabetes was 0.92 (0.90–0.94), 0.85 (0.82–0.88), 0.79 (0.75–0.83), 0.75 (0.71–0.80), 0.71 (0.65–0.76), and 0.67 (0.61–0.74) for 1–6 cups/day, respectively. The RR of diabetes for a 1 cup/day increase was 0.91 (0.89–0.94) for caffeinated coffee consumption and 0.94 (0.91–0.98) for decaffeinated coffee consumption (P for difference = 0.17). CONCLUSIONS Coffee consumption was inversely associated with the risk of type 2 diabetes in a dose-response manner. Both caffeinated and decaffeinated coffee was associated with reduced diabetes risk.

                Author and article information

                Impact Journals LLC
                21 March 2017
                7 April 2016
                : 8
                : 12
                : 18699-18711
                1 Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
                2 Bao’an Central Hospital of Shenzhen, Shenzhen, Guangdong, China
                3 Department of Management, School of Economics and Management, Jiangxi Science and Technology Normal University, Nanchang, Jiangxi, China
                4 Department of Pathophysiology, Shenyang Medical College, Shenyang, Liaoning, China
                5 National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, Changping, China
                6 Division of Health System, Policy and Management, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Sha Tin, Hong Kong SAR, China
                Author notes
                Correspondence to: Zuxun Lu, zuxunlu@
                Copyright: © 2017 Gan et al.

                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.

                Research Paper

                Oncology & Radiotherapy

                colorectal cancer, coffee, meta-analysis, prospective cohort, epidemiology


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