Evidence map›Paper›PMID 31759339›Full record

SynthesisResearch synthesis methods2020

Individual participant data meta-analysis of intervention studies with time-to-event outcomes: A review of the methodology and an applied example.

Valentijn M T de Jong, Karel G M Moons, Richard D Riley, Catrin Tudur Smith, Anthony G Marson, Marinus J C Eijkemans, Thomas P A Debray

Open access · hybridAbstract readMeta-AnalysisReview
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Research synthesis methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 22 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 22 pooled it
6.1field-weighted citation impact, top 2% 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

47 citing papers in PubMed, 22 syntheses or guidelines pooled it, 103 citations in OpenAlex.

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  12. Risk of Peritoneal Carcinomatosis After Risk-Reducing Salpingo-Oophorectomy: A Systematic Review and Individual Patient Data Meta-Analysis.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022
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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 at 3 institutions in 2 countries.

Valentijn M T de JongJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.ORCID https://orcid.org/0000-0001-9921-3468
Karel G M MoonsJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Richard D RileyCentre for Prognosis Research, Research Institute for Primary Care and Health Sciences, Keele University, Staffordshire, UK.ORCID https://orcid.org/0000-0001-8699-0735
Catrin Tudur SmithDepartment of Biostatistics, University of Liverpool, Liverpool, UK.
Anthony G MarsonDepartment of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK.
Marinus J C EijkemansJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.ORCID https://orcid.org/0000-0001-9400-0615
Thomas P A DebrayJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.ORCID https://orcid.org/0000-0002-1790-2719
Utrecht University · NLUniversity of Liverpool · GBKeele University · GB

Funding

European Union, European Commission, Directorate-General for Research and Innovation, Horizon 2020 Framework Programme 825746ZonMW, Netherlands Organization for Health Research and Development 91617050ZonMW, Netherlands Organization for Health Research and Development 91810615
6 · The paper itself

Abstract

Many randomized trials evaluate an intervention effect on time-to-event outcomes. Individual participant data (IPD) from such trials can be obtained and combined in a so-called IPD meta-analysis (IPD-MA), to summarize the overall intervention effect. We performed a narrative literature review to provide an overview of methods for conducting an IPD-MA of randomized intervention studies with a time-to-event outcome. We focused on identifying good methodological practice for modeling frailty of trial participants across trials, modeling heterogeneity of intervention effects, choosing appropriate association measures, dealing with (trial differences in) censoring and follow-up times, and addressing time-varying intervention effects and effect modification (interactions).We discuss how to achieve this using parametric and semi-parametric methods, and describe how to implement these in a one-stage or two-stage IPD-MA framework. We recommend exploring heterogeneity of the effect(s) through interaction and non-linear effects. Random effects should be applied to account for residual heterogeneity of the intervention effect. We provide further recommendations, many of which specific to IPD-MA of time-to-event data from randomized trials examining an intervention effect.We illustrate several key methods in a real IPD-MA, where IPD of 1225 participants from 5 randomized clinical trials were combined to compare the effects of Carbamazepine and Valproate on the incidence of epileptic seizures.

Indexed as

Meta-Analysis as TopicRandomized Controlled Trials as TopicResearch DesignBayes TheoremCarbamazepineData Interpretation, StatisticalHumansProportional Hazards ModelsSeizuresSoftwareTime FactorsValproic AcidCarbamazepineValproic Acidheterogeneityindividual participant datainterventionmeta-analysistime-to-event

Identifiers

PMID31759339
PMCPMC7079159
OpenAlexW2989869936

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.