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Reevaluation of statistically significant meta-analyses in advanced cancer patients using the Hartung-Knapp method
Waldemar Siemens1,2,3, Joerg J Meerpohl1,2, Miriam S Rohe3
1Institute for Evidence in Medicine, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Abstract:
Using the Hartung-Knapp method and 95% prediction intervals (PIs) in random-effects meta-analyses is recommended by experts but rarely applied. Therefore, we aimed to reevaluate statistically significant meta-analyses using the Hartung-Knapp method and 95% PIs. In this methodological study, three databases were searched from January 2010 to July 2019. We included systematic reviews reporting a statistically significant meta-analysis of at least four randomized controlled trials in advanced cancer patients using either a fixed-effect or random-effects model. We investigated the impact of switching from fixed-effect to random-effects meta-analysis and of using the recommended Hartung-Knapp method in random-effects meta-analyses. Furthermore, we calculated 95% PIs for all included meta-analyses. We identified 6234 hits, of which 261 statistically significant meta-analyses were included. Our recalculations of these 261 meta-analyses produced statistically significant results in 132 of 138 fixed-effect and 114 of 123 random-effects meta-analyses. When switching to a random-effects model, 19 of 132 fixed-effect meta-analyses (14.4%) were no longer statistically significant. Using the Hartung-Knapp method in random-effects meta-analyses resulted in 34 of 114 nonsignificant meta-analyses (29.8%). In the full sample (N = 261), the null effect was included by the 95% PI in 195 (74.7%) and the opposite effect (e.g., hazard ratio 0.5, opposite effect 2) in 98 meta-analyses (37.5%). Using the Hartung-Knapp method and PIs substantially influenced the interpretation of many published, statistically significant meta-analyses. We strongly encourage researchers to check if using the Hartung-Knapp method and reporting 95% PIs is appropriate in random-effects meta-analyses.
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