Evidence map›Paper›PMID 31571244›Full record

ArticleStatistics in medicine2019

Quantifying how diagnostic test accuracy depends on threshold in a meta-analysis.

Hayley E Jones, Constantine A Gatsonsis, Thomas A Trikalinos, Nicky J Welton, A E Ades

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In one paragraph

Article in Statistics in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 8 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

17 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Hayley E JonesPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.ORCID 0000-0002-4265-2854
Constantine A GatsonsisDepartment of Biostatistics, Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island.
Thomas A TrikalinosCenter for Evidence Synthesis in Health, Brown University School of Public Health, Providence, Rhode Island.
Nicky J WeltonPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
A E AdesPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.

Funding

Medical Research Council G0802413Medical Research Council MC_U145079307Medical Research Council MR/M014533/1
6 · The paper itself

Abstract

Tests for disease often produce a continuous measure, such as the concentration of some biomarker in a blood sample. In clinical practice, a threshold C is selected such that results, say, greater than C are declared positive and those less than C negative. Measures of test accuracy such as sensitivity and specificity depend crucially on C, and the optimal value of this threshold is usually a key question for clinical practice. Standard methods for meta-analysis of test accuracy (i) do not provide summary estimates of accuracy at each threshold, precluding selection of the optimal threshold, and furthermore, (ii) do not make use of all available data. We describe a multinomial meta-analysis model that can take any number of pairs of sensitivity and specificity from each study and explicitly quantifies how accuracy depends on C. Our model assumes that some prespecified or Box-Cox transformation of test results in the diseased and disease-free populations has a logistic distribution. The Box-Cox transformation parameter can be estimated from the data, allowing for a flexible range of underlying distributions. We parameterise in terms of the means and scale parameters of the two logistic distributions. In addition to credible intervals for the pooled sensitivity and specificity across all thresholds, we produce prediction intervals, allowing for between-study heterogeneity in all parameters. We demonstrate the model using two case study meta-analyses, examining the accuracy of tests for acute heart failure and preeclampsia. We show how the model can be extended to explore reasons for heterogeneity using study-level covariates.

Indexed as

Diagnostic Tests, RoutineMeta-Analysis as TopicModels, StatisticalBiomarkersFemaleHeart FailureHumansPre-EclampsiaPregnancySensitivity and SpecificityBiomarkersBox-Cox transformationevidence synthesisROC curvesensitivityspecificitytest cutoff

Identifiers

PMID31571244
PMCPMC6856843

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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 OpenQuestion graph.