Prospective comparison of search strategies for systematic reviews: an objective approach yielded higher sensitivity than a conceptual one.

Background: In the development of search strategies for systematic reviews, "conceptual approaches" are generally recommended to identify appropriate search terms for those parts of the strategies for which no validated search filters exist. However, "objective approaches" based on search terms identified by text analysis are increasingly being applied.

Objectives: To prospectively compare an objective with a conceptual approach for the development of search strategies.

Searches for randomized controlled trials of drugs in MEDLINE and EMBASE using only generic drug names compared with searches applied in current practice in systematic reviews.

Background: It is unclear which terms should be included in bibliographic searches for randomized controlled trials (RCTs) of drugs, and identifying relevant drug terms can be extremely laborious. The aim of our analysis was to determine whether a bibliographic search using only the generic drug name produces sufficient results for the generation of informative systematic reviews (SRs).

Methods: We conducted a retrospective analysis of relevant references included in SRs of drugs.

Development of search strategies for systematic reviews: validation showed the noninferiority of the objective approach.

Background: Different approaches can be adopted for the development of search strategies of systematic reviews. The objective approach draws on already established text analysis methods for developing search filters. Our aim was to determine whether the objective approach for the development of search strategies was noninferior to the conceptual approach commonly used in Cochrane reviews (CRs).

A note on the graphical presentation of prediction intervals in random-effects meta-analyses.

Background: Meta-analysis is used to combine the results of several related studies. Two different models are generally applied: the fixed-effect (FE) and random-effects (RE) models. Although the two approaches estimate different parameters (that is, the true effect versus the expected value of the distribution of true effects) in practice, the graphical presentation of results is the same for both models.