Evidence map›Paper›PMID 24004523›Full record

SynthesisBMC medical research methodology2013

Consensus-based recommendations for investigating clinical heterogeneity in systematic reviews.

Joel J Gagnier, Hal Morgenstern, Doug G Altman, Jesse Berlin, Stephanie Chang, Peter McCulloch, Xin Sun, David Moher, Ann Arbor Clinical Heterogeneity Consensus Group

Abstract readConsensus StatementSystematic Review
In one paragraph

Synthesis in BMC medical research methodology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 26 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 26 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, 26 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Pooled it
  11. Pooled it
  12. Epidural steroid compared to placebo injection in sciatica: a systematic review and meta-analysis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2021
    Pooled it
  13. Pooled it
  14. Pooled it
  15. Pooled it
  16. Pooled it
  17. Biofeedback for treatment of irritable bowel syndrome.The Cochrane database of systematic reviews · 2019
    Pooled it
  18. BMJ open · 2019
    Pooled it
  19. Pooled it
  20. Pooled it
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.

Joel J GagnierDepartment of Orthopaedic Surgery, University of Michigan, MedSport, 24 Frank Lloyd Wright Drive, Ann Arbor, MI 48106, USA. jgagnier@umich.edu.
Hal Morgenstern
Doug G Altman
Jesse Berlin
Stephanie Chang
Peter McCulloch
Xin Sun
David Moher
Ann Arbor Clinical Heterogeneity Consensus Group

Funding

Development of guidelines for investigating heterogeneity in systematic reviewsR21LM010832 · NLM · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GAGNIER, JOEL JOSEPH, MORGENSTERN, HAL · 2010 to 2011
$417k
NLM NIH HHS R21LM010832-02
6 · The paper itself

Abstract

backgroundCritics of systematic reviews have argued that these studies often fail to inform clinical decision making because their results are far too general, that the data are sparse, such that findings cannot be applied to individual patients or for other decision making. While there is some consensus on methods for investigating statistical and methodological heterogeneity, little attention has been paid to clinical aspects of heterogeneity. Clinical heterogeneity, true effect heterogeneity, can be defined as variability among studies in the participants, the types or timing of outcome measurements, and the intervention characteristics. The objective of this project was to develop recommendations for investigating clinical heterogeneity in systematic reviews.

methodsWe used a modified Delphi technique with three phases: (1) pre-meeting item generation; (2) face-to-face consensus meeting in the form of a modified Delphi process; and (3) post-meeting feedback. We identified and invited potential participants with expertise in systematic review methodology, systematic review reporting, or statistical aspects of meta-analyses, or those who published papers on clinical heterogeneity.

resultsBetween April and June of 2011, we conducted phone calls with participants. In June 2011 we held the face-to-face focus group meeting in Ann Arbor, Michigan. First, we agreed upon a definition of clinical heterogeneity: Variations in the treatment effect that are due to differences in clinically related characteristics. Next, we discussed and generated recommendations in the following 12 categories related to investigating clinical heterogeneity: the systematic review team, planning investigations, rationale for choice of variables, types of clinical variables, the role of statistical heterogeneity, the use of plotting and visual aids, dealing with outlier studies, the number of investigations or variables, the role of the best evidence synthesis, types of statistical methods, the interpretation of findings, and reporting.

conclusionsClinical heterogeneity is common in systematic reviews. Our recommendations can help guide systematic reviewers in conducting valid and reliable investigations of clinical heterogeneity. Findings of these investigations may allow for increased applicability of findings of systematic reviews to the management of individual patients.

Indexed as

Review Literature as TopicConsensusDelphi TechniqueEvidence-Based MedicineHumansMeta-Analysis as TopicRandomized Controlled Trials as TopicTreatment Outcome

Identifiers

PMID24004523
PMCPMC3847163

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.