Evidence map›Paper›PMID 32299367›Full record

ArticleBMC medical research methodology2020

Data sources and methods used to determine pretest probabilities in a cohort of Cochrane diagnostic test accuracy reviews.

Michiel S Oerbekke, Kevin Jenniskens, Rob J P M Scholten, Lotty Hooft

Abstract read
In one paragraph

Article in BMC medical research methodology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Ultrasound for diagnosis of birth weight discordance in twin pregnancies.The Cochrane database of systematic reviews · 2021
    Pooled it
  2. Effect of gender on spect myocardial perfusion imaging results in Egypt.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2024
    Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Michiel S OerbekkeKnowledge Institute of the Federation of Medical Specialists, Utrecht, The Netherlands. M.Oerbekke@kennisinstituut.nl.
Kevin JenniskensJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Rob J P M ScholtenCochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Lotty HooftCochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA pretest probability must be selected to calculate data to help clinicians, guideline boards and policy makers interpret diagnostic accuracy parameters. When multiple analyses for the same target condition are compared, identical pretest probabilities might be selected to facilitate the comparison. Some pretest probabilities may lead to exaggerations of the patient harms or benefits, and guidance on how and why to select a specific pretest probability is minimally described. Therefore, the aim of this study was to assess the data sources and methods used in Cochrane diagnostic test accuracy (DTA) reviews for determining pretest probabilities to facilitate the interpretation of DTA parameters. A secondary aim was to assess the use of identical pretest probabilities to compare multiple meta-analyses within the same target condition.

methodsCochrane DTA reviews presenting at least one meta-analytic estimate of the sensitivity and/or specificity as a primary analysis published between 2008 and January 2018 were included. Study selection and data extraction were performed by one author and checked by other authors. Observed data sources (e.g. studies in the review, or external sources) and methods to select pretest probabilities (e.g. median) were categorized.

resultsFifty-nine DTA reviews were included, comprising of 308 meta-analyses. A pretest probability was used in 148 analyses. Authors used included studies in the DTA review, external sources, and author consensus as data sources for the pretest probability. Measures of central tendency with or without a measure of dispersion were used to determine the pretest probabilities, with the median most commonly used. Thirty-two target conditions had at least one identical pretest probability for all of the meta-analyses within their target condition. About half of the used identical pretest probabilities were inside the prevalence ranges from all analyses within a target condition.

conclusionsMultiple sources and methods were used to determine (identical) pretest probabilities in Cochrane DTA reviews. Indirectness and severity of downstream consequences may influence the acceptability of the certainty in calculated data with pretest probabilities. Consider: whether to present normalized frequencies, the influence of pretest probabilities on normalized frequencies, and whether to use identical pretest probabilities for meta-analyses in a target condition.

Indexed as

Diagnostic Tests, RoutineInformation Storage and RetrievalCohort StudiesData AccuracyHumansProbabilityAbsolute numbersBackground prevalenceDiagnostic test accuracyNatural frequenciesNormalized frequenciesPretest probabilityPretest riskReview literature as topic

Identifiers

PMID32299367
PMCPMC7161259

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.