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Table 2 Combination of terms with the best sensitivity (keeping specificity ≥50%), best specificity (keeping sensitivity ≥50%), and best optimization of sensitivity and specificity (based on abs [sensitivity-specificity] < 1%) for detecting studies of prognosis in MEDLINE in 2000

From: Developing optimal search strategies for detecting clinically sound prognostic studies in MEDLINE: an analytic survey

Search Strategy OVID search* Sensitivity (%) Development Validation Diff (95% CI) Specificity (%) Development Validation Diff (95% CI) Precision (%) Development Validation Diff (95% CI) Accuracy (%) Development Validation Diff (95% CI)
Best Sensitivity     
incidence.sh. 90.1 79.7 1.7 79.7
OR exp mortality 82.3 79.7 1.6 79.7
OR follow-up studies.sh. -7.8 (-17.9 to 2.3) 0 -0.1 (-0.5 to 0.5) 0
OR prognos:.tw.     
OR predict:.tw.     
OR course:.tw.     
Best Specificity     
prognos:.tw. 52.3 94.1 3.3 93.9
OR first episode.tw. 48.1 94.2 3.2 94.0
OR cohort.tw. -4.2 (-18.6 to 10.3) 0.1 (-0.3 to 0.5) -0.1 (-1.3 to 1.3) 0.1 (-0.4 to 0.5)
Best Optimization of Sensitivity & Specificity     
prognosis.sh. 82.9 83.7 1.9 83.7
OR diagnosed.tw. 73.4 84.1 1.8 84.0
OR cohort:.mp. -9.5 (-21.5 to 2.5) -0.4 (-0.2 to 1.1) -0.1 (-0.7 to 0.5) 0.3 (-0.2 to 1.0)
OR predictor:.tw.     
OR death.tw.     
OR exp models, statistical     
  1. *Search strategies are reported using Ovid's search engine syntax for MEDLINE. The PubMed syntax is embedded in PubMed's Clinical Queries (see Discussion). Diff = Difference, comparing the development and validation data sets using the iterative method of Miettinen and Nurminen for two independent binomial proportions. None of the differences were statistically significant. sh = subject heading; exp = explode, a search term that automatically includes closely related indexing terms; : = truncation; tw = textword (word or phrase appears in title or abstract); mp = multiple posting (term appears in title, abstract, or MeSH heading).
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