Literature DB >> 24447592

Estimating a test's accuracy using tailored meta-analysis-How setting-specific data may aid study selection.

Brian H Willis1, Christopher J Hyde2.   

Abstract

OBJECTIVES: To determine a plausible estimate for a test's performance in a specific setting using a new method for selecting studies. STUDY DESIGN AND
SETTING: It is shown how routine data from practice may be used to define an "applicable region" for studies in receiver operating characteristic space. After qualitative appraisal, studies are selected based on the probability that their study accuracy estimates arose from parameters lying in this applicable region. Three methods for calculating these probabilities are developed and used to tailor the selection of studies for meta-analysis. The Pap test applied to the UK National Health Service (NHS) Cervical Screening Programme provides a case example.
RESULTS: The meta-analysis for the Pap test included 68 studies, but at most 17 studies were considered applicable to the NHS. For conventional meta-analysis, the sensitivity and specificity (with 95% confidence intervals) were estimated to be 72.8% (65.8, 78.8) and 75.4% (68.1, 81.5) compared with 50.9% (35.8, 66.0) and 98.0% (95.4, 99.1) from tailored meta-analysis using a binomial method for selection. Thus, for a cervical intraepithelial neoplasia (CIN) 1 prevalence of 2.2%, the post-test probability for CIN 1 would increase from 6.2% to 36.6% between the two methods of meta-analysis.
CONCLUSION: Tailored meta-analysis provides a method for augmenting study selection based on the study's applicability to a setting. As such, the summary estimate is more likely to be plausible for a setting and could improve diagnostic prediction in practice.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Data interpretation, statistical; Decision making; Diagnosis tests, routine; Mass screening; Meta-analysis; Models, statistical

Mesh:

Year:  2014        PMID: 24447592     DOI: 10.1016/j.jclinepi.2013.10.016

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  12 in total

Review 1.  Comparing outcomes from tailored meta-analysis with outcomes from a setting specific test accuracy study using routine data of faecal calprotectin testing for inflammatory bowel disease.

Authors:  Karoline Freeman; Brian H Willis; Ronan Ryan; Sian Taylor-Phillips; Aileen Clarke
Journal:  BMC Med Res Methodol       Date:  2022-07-12       Impact factor: 4.612

2.  Summarising and validating test accuracy results across multiple studies for use in clinical practice.

Authors:  Richard D Riley; Ikhlaaq Ahmed; Thomas P A Debray; Brian H Willis; J Pieter Noordzij; Julian P T Higgins; Jonathan J Deeks
Journal:  Stat Med       Date:  2015-03-20       Impact factor: 2.373

3.  Measuring the statistical validity of summary meta-analysis and meta-regression results for use in clinical practice.

Authors:  Brian H Willis; Richard D Riley
Journal:  Stat Med       Date:  2017-06-15       Impact factor: 2.373

4.  Visual and radiographic caries detection: a tailored meta-analysis for two different settings, Egypt and Germany.

Authors:  Falk Schwendicke; Karim Elhennawy; Osama El Shahawy; Reham Maher; Thais Gimenez; Fausto M Mendes; Brian H Willis
Journal:  BMC Oral Health       Date:  2018-06-08       Impact factor: 2.757

5.  A novel method for interrogating receiver operating characteristic curves for assessing prognostic tests.

Authors:  Grégoire Thomas; Louise C Kenny; Philip N Baker; Robin Tuytten
Journal:  Diagn Progn Res       Date:  2017-11-15

6.  Faecal calprotectin to detect inflammatory bowel disease: a systematic review and exploratory meta-analysis of test accuracy.

Authors:  Karoline Freeman; Brian H Willis; Hannah Fraser; Sian Taylor-Phillips; Aileen Clarke
Journal:  BMJ Open       Date:  2019-03-08       Impact factor: 2.692

Review 7.  Untapped potential of multicenter studies: a review of cardiovascular risk prediction models revealed inappropriate analyses and wide variation in reporting.

Authors:  L Wynants; D M Kent; D Timmerman; C M Lundquist; B Van Calster
Journal:  Diagn Progn Res       Date:  2019-02-22

8.  Maximum likelihood estimation based on Newton-Raphson iteration for the bivariate random effects model in test accuracy meta-analysis.

Authors:  Brian H Willis; Mohammed Baragilly; Dyuti Coomar
Journal:  Stat Methods Med Res       Date:  2019-06-11       Impact factor: 3.021

9.  External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges.

Authors:  Richard D Riley; Joie Ensor; Kym I E Snell; Thomas P A Debray; Doug G Altman; Karel G M Moons; Gary S Collins
Journal:  BMJ       Date:  2016-06-22

10.  Tailored meta-analysis: an investigation of the correlation between the test positive rate and prevalence.

Authors:  Brian H Willis; Dyuti Coomar; Mohammed Baragilly
Journal:  J Clin Epidemiol       Date:  2018-09-29       Impact factor: 6.437

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