Evidence map›Paper›PMID 31360890›Full record

ReviewJNCI cancer spectrum2019

A Systematic Review and Recommendation for Reporting of Surrogate Endpoint Evaluation Using Meta-analyses.

Wanling Xie, Susan Halabi, Jayne F Tierney, Matthew R Sydes, Laurence Collette, James J Dignam, Marc Buyse, Christopher J Sweeney, Meredith M Regan

Abstract readReview
In one paragraph

Review in JNCI cancer spectrum, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 11 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

50 citing papers in PubMed, 11 syntheses or guidelines pooled it.

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  20. Multi-omics and Mendelian randomization identifyTranslational lung cancer research · 2025
    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

9 authors.

Wanling Xie
Susan Halabi
Jayne F Tierney
Matthew R Sydes
Laurence Collette
James J Dignam
Marc Buyse
Christopher J Sweeney
Meredith M Regan

Funding

Medical Research Council MC_EX_UU_G0800814Medical Research Council MC_UU_12023/21Medical Research Council MC_UU_12023/24Medical Research Council MC_UU_12023/25
6 · The paper itself

Abstract

backgroundMeta-analysis of randomized controlled trials (RCTs) has been widely conducted for the evaluation of surrogate endpoints in oncology, but little attention has been given to the adequacy of reporting and interpretation. This review evaluated the reporting quality of published meta-analyses on surrogacy evaluation and developed recommendations for future reporting.

methodsWe searched PubMed through August 2017 to identify studies that evaluated surrogate endpoints using the meta-analyses of RCTs in oncology. Both individual patient data (IPD) and aggregate data (AD) meta-analyses were included for the review.

resultsEighty meta-analyses were identified: 22 used IPD and 58 used AD from multiple RCTs. We observed variability and reporting deficiencies in both IPD and AD meta-analyses, especially on reporting of trial selection, endpoint definition, study and patient characteristics for included RCTs, and important statistical methods and results. Based on these findings, we proposed a checklist and recommendations to improve completeness, consistency, and transparency of reports of meta-analytic surrogacy evaluation. We highlighted key aspects of the design and analysis of surrogate endpoints and presented explanations and rationale why these items should be clearly reported in surrogacy evaluation.

conclusionsOur reporting of surrogate endpoint evaluation using meta-analyses (ReSEEM) guidelines and recommendations will improve the quality in reporting and facilitate the interpretation and reproducibility of meta-analytic surrogacy evaluation. Also, they should help promote greater methodological consistency and could also serve as an evaluation tool in the peer review process for assessing surrogacy research.

Identifiers

PMID31360890
PMCPMC6649812

What OpenQuestion holds

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LicenceCC BY-NC
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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.