2018
DOI: 10.1002/jrsm.1296
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A comparison of methods for meta‐analysis of a small number of studies with binary outcomes

Abstract: Meta-analyses often include only a small number of studies (≤5). Estimating between-study heterogeneity is difficult in this situation. An inaccurate estimation of heterogeneity can result in biased effect estimates and too narrow confidence intervals. The beta-binominal model has shown good statistical properties for meta-analysis of sparse data. We compare the beta-binominal model with different inverse variance random (eg, DerSimonian-Laird, modified Hartung-Knapp, and Paule-Mandel) and fixed effects method… Show more

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Cited by 94 publications
(87 citation statements)
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References 47 publications
(190 reference statements)
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“…Data from this analysis should be interpreted carefully as the low number of studies makes the estimation of heterogeneity difficult and the result can be biased …”
Section: Resultsmentioning
confidence: 99%
“…Data from this analysis should be interpreted carefully as the low number of studies makes the estimation of heterogeneity difficult and the result can be biased …”
Section: Resultsmentioning
confidence: 99%
“…The main analysis was the pooled prevalence along with its 95% confidence interval (CI) of Ph-like ALL among patients with ALL across the studies, which was calculated by the DerSimonian and Laird random-effects model with double arcsine transformation. 25 The same technique was also used to calculate several secondary outcomes, including the pooled 5-year OS rate, DFS rate, EFS rate, and CIR rate of Ph-like ALL patients across the studies. Comparative analyses of the odds of surviving at 5 years, experiencing DFS at 5 years, experiencing EFS at 5 years, and having at least one relapse at 5 years among Ph-like ALL, Ph þ ALL, and B-other ALL patients were also conducted by the Mantel-Haenszel method.…”
Section: Discussionmentioning
confidence: 99%
“…For remission incidence and adverse event incidence we will report the results of the analyses as risk ratio (RR), pooled using the Mantel-Haenszel method [7] , with 95% confidence intervals (CIs) with Hartung-Knapp adjustment for random effects model [8] . For Hb, RBC, reticulocyte counts, hematocrit and total bilirubin, we will report the results as mean differences (MDs), pooled using the inverse variance method [9] , with corresponding 95% CIs with Hartung-Knapp adjustment for random effects model [8] .…”
Section: Meta-analysismentioning
confidence: 99%