| Ref ID | 474 |
| First Author | J. P. Ioannidis |
| Journal | BMJ |
| Year Of Publishing | 2008 |
| URL | https://pubmed.ncbi.nlm.nih.gov/18566080/ |
| Keywords |
• General medical • Heterogeneity • Statistical • Expertise |
| Problem(s) |
• Poor execution of narrative synthesis • Lack of statistical expertise in handling of quantitative data |
| Article Type | Editorial |
| Article Subtype | Discussion piece |
| First Author Country | United States |
| Aim | To assess common reasons employed in systematic reviews for not producing a summary effect in reviews which did produce Forest plots from issue 4 of the Cochrane Database of Systematic Reviews (2005). |
| Level of Investigation | Descriptive |
| Summary of Findings | 135 of Cochrane reviews (8%) had 559 forest plots with no summary estimate. Reasons provided for avoiding quantitative synthesis typically revolved around heterogeneity. However, these typically revolve around statistical heterogeneity, such as the I squared statistic, which is not adequate to fully explain or explore heterogeneity. Conducting random effects meta-analysis, meta-regression or Bayesian meta-analysis are methods highlighted by the authors as potential methodological approaches to heterogenous data. Specifying clearer reasons would improve transparency of the systematic reviewers' implicit judgments about heterogeneity and the ability to meta-analyse. |
| Number of systematic reviews included | 135 |
| Number of eligible systematic reviews assessed | 1739 |
| Treatment impacted | No |
| Treatment impacted description | |
| Interpretation impacted | Not Applicable |
| Interpretation impacted description |