Evidence map›Paper›PMID 22648676›Full record

ArticleJournal of general internal medicine2012

Chapter 8: meta-analysis of test performance when there is a "gold standard".

Thomas A Trikalinos, Cynthia M Balion, Craig I Coleman, Lauren Griffith, Pasqualina L Santaguida, Ben Vandermeer, Rongwei Fu

Abstract read
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In one paragraph

Article in Journal of general internal medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 23 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 23 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

40 citing papers in PubMed, 23 syntheses or guidelines pooled it.

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  6. A Systematic Review and Meta-analysis of Convolutional Neural Network in the Diagnosis of Colorectal Polyps and Cancer.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2023
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  14. Clinically Relevant Imaging Features forAJNR. American journal of neuroradiology · 2018
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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

7 authors.

Thomas A TrikalinosCenter for Evidence-based Medicine, and Department of Health Services Policy and Practice, Brown University, Providence, RI 02912, USA. thomas_trikalinos@brown.edu
Cynthia M Balion
Craig I Coleman
Lauren Griffith
Pasqualina L Santaguida
Ben Vandermeer
Rongwei Fu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Synthesizing information on test performance metrics such as sensitivity, specificity, predictive values and likelihood ratios is often an important part of a systematic review of a medical test. Because many metrics of test performance are of interest, the meta-analysis of medical tests is more complex than the meta-analysis of interventions or associations. Sometimes, a helpful way to summarize medical test studies is to provide a "summary point", a summary sensitivity and a summary specificity. Other times, when the sensitivity or specificity estimates vary widely or when the test threshold varies, it is more helpful to synthesize data using a "summary line" that describes how the average sensitivity changes with the average specificity. Choosing the most helpful summary is subjective, and in some cases both summaries provide meaningful and complementary information. Because sensitivity and specificity are not independent across studies, the meta-analysis of medical tests is fundamentaly a multivariate problem, and should be addressed with multivariate methods. More complex analyses are needed if studies report results at multiple thresholds for positive tests. At the same time, quantitative analyses are used to explore and explain any observed dissimilarity (heterogeneity) in the results of the examined studies. This can be performed in the context of proper (multivariate) meta-regressions.

Indexed as

Guidelines as TopicMeta-Analysis as TopicReview Literature as TopicAlgorithmsDiagnostic Techniques and ProceduresEvidence-Based MedicineHumansOutcome and Process Assessment, Health CarePredictive Value of TestsReference StandardsSensitivity and Specificity

Identifiers

PMID22648676
PMCPMC3364353

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.