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The Article Alert for the week of August 18, 2014 (sample articles)
van Enst WA, Scholten RJ, Whiting P, Zwinderman AH, Hooft L. Meta-epidemiologic analysis indicates that MEDLINE searches are sufficient for diagnostic test accuracy systematic reviews. J.Clin.Epidemiol. Epub 2014 Jul 1. PMID: 24996667.
OBJECTIVES: To investigate how the summary estimates in diagnostic test accuracy (DTA) systematic reviews are affected when searches are limited to MEDLINE.
STUDY DESIGN AND SETTING: A systematic search was performed to identify DTA reviews that had conducted exhaustive searches and included a meta-analysis. Primary studies included in selected reviews were assessed to determine whether they were indexed on MEDLINE. The effect of omitting non-MEDLINE studies from meta-analyses was investigated by calculating the summary relative diagnostic odds ratio (RDORs) = DORMEDLINE only/DORall studies. We also calculated the summary difference in sensitivity and specificity between all studies and only MEDLINE-indexed studies.
RESULTS: Ten reviews contributing 15 meta-analyses met inclusion criteria for quantitative analysis. The RDOR comparing MEDLINE-only studies with all studies was 1.04 (95% confidence interval [CI], 0.95, 1.15). Summary estimates of sensitivity and specificity remained almost unchanged (difference in sensitivity: -0.08%; 95% CI -1% to 1%; difference in specificity: -0.1%; 95% CI -0.8% to 1%).
CONCLUSION: Restricting to studies indexed on MEDLINE did not influence the summary estimates of the meta-analyses in our sample. In certain circumstances, for instance, when resources are limited, it may be appropriate to restrict searches to MEDLINE. However, the impact on individual reviews cannot be predicted.
Copyright © 2014 Elsevier Inc. All rights reserved.
- DOI: http://dx.doi.org/10.1016/j.jclinepi.2014.05.008
- PubMed: http://www.ncbi.nlm.nih.gov/pubmed/24996667
Koricheva J, Gurevitch J. Uses and misuses of meta-analysis in plant ecology. Journal of Ecology. 2014 Jul;102(4):828-44
- The number of published meta-analyses in plant ecology has increased greatly over the last two decades. Meta-analysis has made a significant contribution to the field, allowing review of evidence for various ecological hypotheses and theories, estimation of effects of major environmental drivers (climate change, habitat fragmentation, invasive species, air pollution), assessment of management and conservation strategies, and comparison of effects across different temporal and spatial scales, taxa and ecosystems, as well as research gap identification.
- We identified 322 meta-analyses published in the field of plant ecology between 1996 and 2013 in 95 different journals and assessed their methodological and reporting quality according to standard criteria. Despite significant recent developments in the methodology of meta-analysis, the quality of published meta-analyses was uneven and showed little improvement over time.
- We found many cases of imprecise and inaccurate usage of the term ‘meta-analysis’ in plant ecology, particularly confusion between meta-analysis and vote counting and incorrect application of statistical techniques designed for primary studies to meta-analytical data, without recognition of the violation of statistical assumptions of the analyses.
- Methodological issues for meta-analyses in plant ecology include incomplete reporting of search strategy used to retrieve primary studies, failure to test for possible publication bias and to conduct sensitivity analysis to test the robustness of the results, as well as lack of availability of the data set used for the analyses.
- The use of meta-analysis is particularly common in community ecology, ecophysiology and ecosystem ecology, but meta-analyses in ecophysiology are more likely not to meet standard quality criteria than papers in other subdisciplines. Fewer meta-analyses have been conducted in plant population ecology. 6.Synthesis. Over the past two decades, plant ecologists have embraced meta-analysis as a statistical tool to combine results across studies, and much has been learned as a result. However, as the popularity and usage of meta-analysis in the field of plant ecology has grown, establishment of quality standards, as has been done in other disciplines, becomes increasingly important. In order to improve the quality of future meta-analyses in plant ecology, we suggest adoption of a checklist of quality criteria for meta-analysis for use by research synthesists, peer reviewers and journal editors.
- FREE FULL TEXT: http://onlinelibrary.wiley.com/doi/10.1111/1365-2745.12224/pdf
- DOI: http://dx.doi.org/10.1111/1365-2745.12224
Rooney AA, Boyles AL, Wolfe MS, Bucher JR, Thayer KA. Systematic review and evidence integration for literature-based environmental health science assessments. Environ.Health Perspect. 2014 Jul;122(7):711-8. PMID: 24755067.
BACKGROUND: Systematic-review methodologies provide objectivity and transparency to the process of collecting and synthesizing scientific evidence in reaching conclusions on specific research questions. There is increasing interest in applying these procedures to address environmental health questions.
OBJECTIVES: The goal was to develop a systematic-review framework to address environmental health questions by extending approaches developed for clinical medicine to handle the breadth of data relevant to environmental health sciences (e.g., human, animal, and mechanistic studies).
METHODS: The Office of Health Assessment and Translation (OHAT) adapted guidance from authorities on systematic-review and sought advice during development of the OHAT Approach through consultation with technical experts in systematic review and human health assessments, as well as scientific advisory groups and the public. The method was refined by considering expert and public comments and through application to case studies.
RESULTS AND DISCUSSION: Here we present a seven-step framework for systematic review and evidence integration for reaching hazard identification conclusions: 1) problem formulation and protocol development, 2) search for and select studies for inclusion, 3) extract data from studies, 4) assess the quality or risk of bias of individual studies, 5) rate the confidence in the body of evidence, 6) translate the confidence ratings into levels of evidence, and 7) integrate the information from different evidence streams (human, animal, and "other relevant data" including mechanistic or in vitro studies) to develop hazard identification conclusions.
CONCLUSION: The principles of systematic review can be successfully applied to environmental health questions to provide greater objectivity and transparency to the process of developing conclusions.