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Potential impact of missing outcome data on treatment effects in systematic reviews: imputation study.

Lara A KahaleAssem M KhamisBatoul DiabYaping ChangLuciane Cruz LopesArnav AgarwalLing LiReem A MustafaSerge KoujanianReem WaziryJason W BusseAbeer DakikHolger J SchünemannLotty HooftRob Jpm ScholtenGordon H GuyattElie A Akl
Published in: BMJ (Clinical research ed.) (2020)
Even when applying plausible assumptions to the outcomes of participants with definite missing data, the average change in pooled relative effect estimate is substantive, and almost a quarter (22%) of meta-analyses crossed the threshold of the null effect. Systematic review authors should present the potential impact of missing outcome data on their effect estimates and use this to inform their overall GRADE (grading of recommendations assessment, development, and evaluation) ratings of risk of bias and their interpretation of the results.
Keyphrases
  • systematic review
  • meta analyses
  • electronic health record
  • big data
  • adipose tissue
  • insulin resistance