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Introduction to meta-analysis (1612_MA_workshop)

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Chapter 1: Introduction to Meta-analysis

- From the 1612 MA Workshop that will be held on 11th, December, 2016 at Dokki, Giza, Egypt
- Workshop instructor: Mr. Ahmed Negida, MBBCh candidate

Publicado en: Salud y medicina
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Introduction to meta-analysis (1612_MA_workshop)

  1. 1. Meta-analysis Workshop From ZERO to HERO Ahmed Negida MBBCh candidate, Fifth Year Student School of Medicine, Zagazig University, Egypt
  2. 2. Learning Objectives • Introduction to descriptive and inferential statistics. • Concept of meta-analysis • Meta-analysis software • Meta-analysis models • Assessment of heterogeneity • Assessment of publication bias
  3. 3. What is new in this workshop? • Overview of different meta-analysis softwares • Meta-analysis functions on MS Excel • Quality effects meta-analysis model • Q index as a safe-guards score • Inverse variance heterogeneity model • DOI plot and LFK index for assessment of publication bias • Overview of the concept of indirect comparison of three- treatment network using the “single closed loop” method.
  4. 4. Important Terms • Effect estimate • Effect size • Mean difference • Standardized mean difference • Prospective study • Retrospective study • Clinical Trial • Randomized Controlled trial
  5. 5. Combining Effect Estimates The drug (x) is being investigated for the treatment of insomnia. Multiple clinical trials have evaluated the efficacy of drug (x). Sleeping hours (h): Improvement = Post - Pre There are 10 studies reporting the improvement in sleeping duration with drug (x) in patients with insomnia. How can you combine the results of these studies in one single combined effect estimate?
  6. 6. The mean average?
  7. 7. Using the mean average to summarize effect estimates is not correct! The mean average assumes that all studies have the same power (weight) to influence the final effect estimate. This is not correct because studies do not have the same power and are not equal in sample size or population distribution. Why?
  8. 8. Concept ofmeta-analysis A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. The idea of meta-analysis is to pool the weighted average of studies/subgroups to give one single effect estimate. Pooled Effect Estimate Study 3 Study 1 Study 2
  9. 9. Concept of meta-analysis
  10. 10. Why can not werely onsingle high-quality studies? Under the most rigorous study design conditions, a well-planned single study, even if prospective and randomized, rarely provides definitive results, and primary studies tend to overestimate treatment effects. A recent study reported that 32% of a set of studies with at least 1,000 citations were either contradicted by or reported stronger effects than subsequent studies (Ioannidis, 2005). Ioannidis JPA. Why Most Published Research Findings Are False. PLoS Medicine. 2005;2(8):e124. doi:10.1371/journal.pmed.0020124.
  11. 11. Advantages of meta-analysis - Larger power (sample size) - Reproducible (systematic review protocol) - A small but clinically significant effect size might be apparent in meta-analysis
  12. 12. Disadvantages of Meta-analysis - Complicated statistical analysis - Heterogeneity among studies - Difference in outcome reporting