Evidence map›Paper›PMID 34727973›Full record

SynthesisSystematic reviews2021

Using median survival in meta-analysis of experimental time-to-event data.

Theodore C Hirst, Emily S Sena, Malcolm R Macleod

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Systematic reviews, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 4 pooled it
0.4field-weighted citation impact, top 21% of its field
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

12 citing papers in PubMed, 4 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
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  4. Modular (universal) CAR-T platformsFrontiers in immunology · 2024
    Pooled it
  5. Review
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  12. Assessment of NSCLC disease burden: A survival model-based meta-analysis study.Computational and structural biotechnology journal · 2024
    Article
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

3 authors at 2 institutions in 1 country.

Theodore C HirstCentre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK. theodore.hirst@ed.ac.uk.ORCID 0000-0003-3501-8422
Emily S SenaCentre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Malcolm R MacleodCentre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
University of Edinburgh · GBUniversity of Ulster · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTime-to-event data is frequently reported in both clinical and preclinical research spheres. Systematic review and meta-analysis is a tool that can help to identify pitfalls in preclinical research conduct and reporting that can help to improve translational efficacy. However, pooling of studies using hazard ratios (HRs) is cumbersome especially in preclinical meta-analyses including large numbers of small studies. Median survival is a much simpler metric although because of some limitations, which may not apply to preclinical data, it is generally not used in survival meta-analysis. We aimed to appraise its performance when compared with hazard ratio-based meta-analysis when pooling large numbers of small, imprecise studies.

methodsWe simulated a survival dataset with features representative of a typical preclinical survival meta-analysis, including with influence of a treatment and a number of covariates. We calculated individual patient data-based hazard ratios and median survival ratios (MSRs), comparing the summary statistics directly and their performance at random-effects meta-analysis. Finally, we compared their sensitivity to detect associations between treatment and influential covariates at meta-regression.

resultsThere was an imperfect correlation between MSR and HR, although the opposing direction of treatment effects between summary statistics appeared not to be a major issue. Precision was more conservative for HR than MSR, meaning that estimates of heterogeneity were lower. There was a slight sensitivity advantage for MSR at meta-analysis and meta-regression, although power was low in all circumstances.

conclusionsWe believe we have validated MSR as a summary statistic for use in a meta-analysis of small, imprecise experimental survival studies-helping to increase confidence and efficiency in future reviews in this area. While assessment of study precision and therefore weighting is less reliable, MSR appears to perform favourably during meta-analysis. Sensitivity of meta-regression was low for this set of parameters, so pooling of treatments to increase sample size may be required to ensure confidence in preclinical survival meta-regressions.

Indexed as

Survival AnalysisHumansExperimental studiesMedian survivalMeta-analysisSystematic reviewTime-to-event

Identifiers

PMID34727973
PMCPMC8561932
OpenAlexW3180188087

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.