Evidence map›Paper›PMID 40211371›Full record

ArticleSystematic reviews2025

Practical methods for incorporating summary time-to-event data into meta-analysis: updated guidance.

Jayne F Tierney, Sarah Burdett, David J Fisher

Erratum issuedAbstract read
In one paragraph

Article in Systematic reviews, 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 44 papers, 25 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 25 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

44 citing papers in PubMed, 25 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Jayne F TierneyMRC Clinical Trials Unit, Medical Research Council Clinical Trials Unit, University College London, London, UK. jayne.tierney@ucl.ac.uk.ORCID http://orcid.org/0000-0002-4734-3014
Sarah BurdettMRC Clinical Trials Unit, Medical Research Council Clinical Trials Unit, University College London, London, UK.
David J FisherMRC Clinical Trials Unit, Medical Research Council Clinical Trials Unit, University College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our previous guide to estimating hazard ratios (HRs) from published summary (aggregate) data has become very widely used, but many still have difficulties knowing when and how to apply the methods. Informed by our increased experience of applying them across a range of settings, the queries we have received and results of a survey of Cochrane editors on the methods, we have updated the guidance comprehensively. Previously, we described a range of scenarios for deriving a HR and logrank variance (V) from published time-to-event analyses. They are incorporated in this update, together with clarification of ambiguities and additional scenarios. We also provide further guidance on extracting and using data from publications and Kaplan-Meier (KM) curves, raise some of the challenges, and discuss recent alternatives to the "Parmar" KM methods. A new calculations spreadsheet will perform all possible calculations given the data that are entered and includes new features to enhance the user experience. This updated guidance and associated spreadsheet represent valuable additional tools for those conducting meta-analyses based on published, summary, time-to-event data.

Indexed as

Meta-Analysis as TopicData Interpretation, StatisticalGuidelines as TopicHumansKaplan-Meier EstimateProportional Hazards ModelsResearch DesignAggregate dataHazard ratioMeta-analysisMethodsSummary dataTime-to-event outcomes

Identifiers

PMID40211371
PMCPMC11984287

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.