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      Systematic Review and Meta-analysis of Circulatory Disease from Exposure to Low-Level Ionizing Radiation and Estimates of Potential Population Mortality Risks

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          Abstract

          Background: Although high doses of ionizing radiation have long been linked to circulatory disease, evidence for an association at lower exposures remains controversial. However, recent analyses suggest excess relative risks at occupational exposure levels.

          Objectives: We performed a systematic review and meta-analysis to summarize information on circulatory disease risks associated with moderate- and low-level whole-body ionizing radiation exposures.

          Methods: We conducted PubMed/ISI Thomson searches of peer-reviewed papers published since 1990 using the terms “radiation” AND “heart” AND “disease,” OR “radiation” AND “stroke,” OR “radiation” AND “circulatory” AND “disease.” Radiation exposures had to be whole-body, with a cumulative mean dose of < 0.5 Sv, or at a low dose rate (< 10 mSv/day). We estimated population risks of circulatory disease from low-level radiation exposure using excess relative risk estimates from this meta-analysis and current mortality rates for nine major developed countries.

          Results: Estimated excess population risks for all circulatory diseases combined ranged from 2.5%/Sv [95% confidence interval (CI): 0.8, 4.2] for France to 8.5%/Sv (95% CI: 4.0, 13.0) for Russia.

          Conclusions: Our review supports an association between circulatory disease mortality and low and moderate doses of ionizing radiation. Our analysis was limited by heterogeneity among studies (particularly for noncardiac end points), the possibility of uncontrolled confounding in some occupational groups by lifestyle factors, and higher dose groups (> 0.5 Sv) generally driving the observed trends. If confirmed, our findings suggest that overall radiation-related mortality is about twice that currently estimated based on estimates for cancer end points alone (which range from 4.2% to 5.6%/Sv for these populations).

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          Most cited references 64

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          Bias in meta-analysis detected by a simple, graphical test.

          Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews. Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution.
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            This paper examines eight published reviews each reporting results from several related trials. Each review pools the results from the relevant trials in order to evaluate the efficacy of a certain treatment for a specified medical condition. These reviews lack consistent assessment of homogeneity of treatment effect before pooling. We discuss a random effects approach to combining evidence from a series of experiments comparing two treatments. This approach incorporates the heterogeneity of effects in the analysis of the overall treatment efficacy. The model can be extended to include relevant covariates which would reduce the heterogeneity and allow for more specific therapeutic recommendations. We suggest a simple noniterative procedure for characterizing the distribution of treatment effects in a series of studies.
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              Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group.

               T Sipe,  D Rennie,  D Stroup (2000)
              Because of the pressure for timely, informed decisions in public health and clinical practice and the explosion of information in the scientific literature, research results must be synthesized. Meta-analyses are increasingly used to address this problem, and they often evaluate observational studies. A workshop was held in Atlanta, Ga, in April 1997, to examine the reporting of meta-analyses of observational studies and to make recommendations to aid authors, reviewers, editors, and readers. Twenty-seven participants were selected by a steering committee, based on expertise in clinical practice, trials, statistics, epidemiology, social sciences, and biomedical editing. Deliberations of the workshop were open to other interested scientists. Funding for this activity was provided by the Centers for Disease Control and Prevention. We conducted a systematic review of the published literature on the conduct and reporting of meta-analyses in observational studies using MEDLINE, Educational Research Information Center (ERIC), PsycLIT, and the Current Index to Statistics. We also examined reference lists of the 32 studies retrieved and contacted experts in the field. Participants were assigned to small-group discussions on the subjects of bias, searching and abstracting, heterogeneity, study categorization, and statistical methods. From the material presented at the workshop, the authors developed a checklist summarizing recommendations for reporting meta-analyses of observational studies. The checklist and supporting evidence were circulated to all conference attendees and additional experts. All suggestions for revisions were addressed. The proposed checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion. Use of the checklist should improve the usefulness of meta-analyses for authors, reviewers, editors, readers, and decision makers. An evaluation plan is suggested and research areas are explored.
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                Author and article information

                Affiliations
                [1]Radiation Epidemiology Branch, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Rockville, Maryland, USA
                [2]Southern Urals Biophysics Institute, Ozyorsk, Russia
                [3]Research Center for Radiation Medicine, Kyiv, Ukraine
                [4]Health Protection Agency, Centre for Radiation, Chemical and Environmental Hazards, Chilton, United Kingdom
                [5]Center for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
                [6]Medical Radiological Research Center of Russian Academy of Medical Sciences, Obninsk, Russia
                [7]NASA Johnson Space Center, Space Radiation Program, Houston, Texas, USA
                [8]Radiation Epidemiology Group, INSERM (Institut National de la Santé et de la Recherche Médicale) Unité U1018, Institut Gustave Roussy, Villejuif, France
                [9]Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
                [10]Department of Radiotherapy and Radiation Oncology, University of Leipzig, Leipzig, Germany
                [11]Department of Radiotherapy and Radiation Oncology, University of Rostock, Rostock, Germany
                [12]Federal Office for Radiation Protection, Department of Radiation Protection and Health, Oberschleissheim, Germany
                [13]Laboratoire d’Epidémiologie, Institut de Radioprotection et de Sûreté Nucleaire, Fontenay-aux-Roses, France
                [14]Department of Epidemiology, Radiation Effects Research Foundation, Hiroshima City, Japan
                [15]CEPN (Nuclear Evaluation Protection Center), Fontenay-aux-Roses, France
                [16]Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Radiation Biology (ISB), Radiation Proteomics, Oberschleissheim, Germany
                [17]University College London Institute of Cardiovascular Sciences & Great Ormond Street Hospital for Children, London, United Kingdom
                [18]Department of Epidemiology and Biostatistics, Imperial College Faculty of Medicine, London, United Kingdom
                [19]Dalton Nuclear Institute, University of Manchester, Manchester, United Kingdom
                [20]Department of Epidemiology and Biostatistics, University of California San Francisco School of Medicine, San Francisco, California, USA
                [21]Department of Pediatrics, Leonard M. Miller School of Medicine, University of Miami, Miami, Florida, USA
                Author notes
                Address correspondence to M.P. Little, Radiation Epidemiology Branch, National Cancer Institute, Executive Plaza South, 6120 Executive Blvd. MSC 7238, Rockville, MD 20852-7238 USA. Telephone: (301) 402-9138 (office); (301) 875-3413 (mobile). Fax: (301) 402-0207. E-mail: mark.little@123456nih.gov
                Journal
                Environ Health Perspect
                Environ. Health Perspect
                EHP
                Environmental Health Perspectives
                National Institute of Environmental Health Sciences
                0091-6765
                1552-9924
                22 June 2012
                November 2012
                : 120
                : 11
                : 1503-1511
                22728254
                3556625
                ehp.1204982
                10.1289/ehp.1204982

                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 work is properly cited.

                Categories
                Review

                Public health

                heart disease, circulatory disease, radiation, stroke, cancer

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