Development and validation of high-sensitivity and high-specificity pubmed search filters for systematic and non-systematic reviews

Abstract

Objective: To develop and compare the accuracy of different PubMed search strategies (filters) for systematic and non-systematic reviews in dental journals. Methods: This validation study included articles published in 2019 in 15 dental journals. Two search filters were developed: (1) a high-sensitivity filter to retrieve all possible review articles, and (2) a high-specificity filter for systematic reviews. Two previously published filters were used as benchmarks. The gold standard method for identifying the study methodology was manual reading of the full text. Accuracy, sensitivity and specificity were calculated. Results: Among the 2246 articles published, 6.7% (n = 150) were systematic reviews and 5.9% (n = 132) were other types of reviews. The high-sensitivity filter retrieved 147 of 150 systematic reviews and showed a sensitivity of 98.0% (95%CI: 94.3–99.6) and specificity of 88.9% (95%CI: 87.5–90.2). The high-specificity filter had 96.7% (95%CI: 92.4–98.9) sensitivity and 99.1% (95%CI: 98.6–99.5) specificity for retrieving systematic reviews. The accuracy of this filter for systematic reviews was 97.9% (95%CI: 96.4–99.4), which was higher than the PubMed benchmark filter (p < 0.05) and similar to another longer filter. Conclusion: This study provides two new highly accurate search filters for PubMed that can be used by clinicians, researchers and policymakers.