Evidence map›Paper›PMID 40569092›Full record

ArticleJournal of evaluation in clinical practice2025

Prediction Performance of Earlier Studies for Later Studies in Cochrane Reviews.

Fahad M Al Amer, Lifeng Lin

Erratum issuedAbstract read
In one paragraph

Article in Journal of evaluation in clinical practice, 2025. 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Fahad M Al AmerDepartment of Mathematics, College of Science and Arts, Najran University, Najran, Saudi Arabia.
Lifeng LinDepartment of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA.ORCID 0000-0002-3562-9816

Funding

Statistical Methods and Software for Multivariate Meta-analysisR01LM012982 · NLM · UNIVERSITY OF MINNESOTA · PI LIN, LIFENG, SIEGEL, LIANNE · 2019 to 2022
$1.3M
Advanced Methods and Software for Trial Sequential Analysis in Living Systematic ReviewsR21LM014533 · NLM · UNIVERSITY OF ARIZONA · PI LIN, LIFENG · 2024 to 2025
$364k
Innovative Data Integration Models for Handling Evidence Inconsistency in AD/ADRD ResearchR03AG093555 · NIA · UNIVERSITY OF ARIZONA · PI LIN, LIFENG · 2025 to 2025
$301k
Joint modeling of continuous and binary data in meta-analysisR03MH128727 · NIMH · UNIVERSITY OF ARIZONA · PI LIN, LIFENG · 2022 to 2023
$146k
Fahad M. Al Amer was supported by the Deanship of Graduate Studies and Scientific Research at Najran University grant code (NU/EFP/SERC/13/1). Lifeng Lin was supported in part by the US National Institute of Mental Health grant R03 MH128727, the US National Institute on Aging grant R03 AG093555, the US National Library of Medicine grants R21 LM014533 and R01 LM012982, and the Arizona Biomedical Research Centre grant RFGA2023-008-11. The content is solely the responsibility of the authors and does not necessarily represent the official views of the US National Institutes of Health and the Arizona Department of Health Services.NIA NIH HHS R03 AG093555NIMH NIH HHS R03 MH128727NLM NIH HHS R01 LM012982NLM NIH HHS R21 LM014533
6 · The paper itself

Abstract

rationaleBetween-study heterogeneity poses challenges to the generalisability of meta-analytical results, which can influence their ability to predict outcomes in future studies. Prediction intervals have been proposed to account for both uncertainty and heterogeneity, yet their real-world performance in predicting future studies has not been systematically evaluated. AIMS AND

objectivesThis study aims to assess the prediction performance of meta-analyses, focusing on how effectively they predict later study results based on meta-analyses of earlier studies.

methodsThis empirical study used a comprehensive collection of meta-analyses from the Cochrane Database of Systematic Reviews. Through in-sample evaluation, the success of predicting later study results was assessed based on meta-analyses of earlier studies in Cochrane reviews. The impact of factors such as the number of studies in the meta-analysis and uncertainties in heterogeneity estimation was also analysed.

resultsThe findings reveal that prediction failures are common, particularly as the number of studies in the meta-analysis increases. This may be attributed to uncertainties in estimating between-study heterogeneity. Conversely, when the number of studies is small, the proportion of successful predictions is high. However, this is likely due to large uncertainties in predictions and the limited information provided by fewer studies, which may reduce their utility in providing valuable evidence for future studies.

conclusionsThese results underscore the importance of cautious interpretation and further investigation when applying meta-analytical findings to future studies. Our findings suggest several potential strategies for predicting future study results through evidence synthesis, with particular emphasis on carefully considering between-study heterogeneity, the number of studies included in a meta-analysis, and the temporal trends in individual study results.

Indexed as

Meta-Analysis as TopicReview Literature as TopicForecastingHumansUncertaintyCochrane reviewheterogeneitymeta‐analysispredictionsystematic review

Identifiers

PMID40569092
PMCPMC12204203

What OpenQuestion holds

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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.