- 著者
- Hisashi Noma Kengo Nagashima Shogo Kato Satoshi Teramukai Toshi A. Furukawa
- 出版者
- Japan Epidemiological Association
- 雑誌
- Journal of Epidemiology (ISSN:09175040)
- 巻号頁・発行日
- vol.32, no.10, pp.441-448, 2022-10-05 (Released:2022-10-05)
- 参考文献数
- 30
- 被引用文献数
- 1 3
Background: In meta-analysis, the normal distribution assumption has been adopted in most systematic reviews of random-effects distribution models due to its computational and conceptual simplicity. However, this restrictive model assumption is possibly unsuitable and might have serious influences in practices.Methods: We provide two examples of real-world evidence that clearly show that the normal distribution assumption is explicitly unsuitable. We propose new random-effects meta-analysis methods using five flexible random-effects distribution models that can flexibly regulate skewness, kurtosis and tailweight: skew normal distribution, skew t-distribution, asymmetric Subbotin distribution, Jones–Faddy distribution, and sinh–arcsinh distribution. We also developed a statistical package, flexmeta, that can easily perform these methods.Results: Using the flexible random-effects distribution models, the results of the two meta-analyses were markedly altered, potentially influencing the overall conclusions of these systematic reviews.Conclusion: The restrictive normal distribution assumption in the random-effects model can yield misleading conclusions. The proposed flexible methods can provide more precise conclusions in systematic reviews.
- 著者
- Yuki Kataoka Shiho Oide Takashi Ariie Yasushi Tsujimoto Toshi A. Furukawa
- 出版者
- Society for Clinical Epidemiology
- 雑誌
- Annals of Clinical Epidemiology (ISSN:24344338)
- 巻号頁・発行日
- vol.3, no.2, pp.46-55, 2021 (Released:2021-04-01)
- 参考文献数
- 36
BACKGROUNDThe objective of this study was to investigate the methodological quality of coronavirus disease 2019 (COVID-19) systematic reviews (SRs) indexed in medRxiv and PubMed, compared with Cochrane COVID Reviews.METHODSThis is a cross-sectional meta-epidemiological study. We searched medRxiv, PubMed, and Cochrane Database of Systematic Reviews for SRs of COVID-19. We evaluated the methodological quality using A MeaSurement Tool to Assess systematic Reviews (AMSTAR) checklists. The maximum AMSTAR score is 11, and minimum is 0. Higher score means better quality.RESULTSWe included 9 Cochrane reviews as well as randomly selected 100 non-Cochrane reviews in medRxiv and PubMed. Compared with Cochrane reviews (mean 9.33, standard deviation 1.32), the mean AMSTAR scores of the articles in medRxiv were lower (mean difference (MD): −2.85, 98.3% confidence intervals (CI): −0.96 to −4.74), and those in PubMed were also lower (MD: −3.28, 98.3%CI: −1.40 to −5.15), with no difference between the latter two.CONCLUSIONSReaders should pay attention to the potentially low methodological quality of SRs related to COVID-19 in both PubMed and medRxiv. Evidence users might be better to search the Cochrane Library rather than medRxiv or PubMed to search SRs related to COVID-19.