Evidence map›Paper›PMID 29268721›Full record

ArticleBMC medical research methodology2017

The development of CHAMP: a checklist for the appraisal of moderators and predictors.

Ralph van Hoorn, Marcia Tummers, Andrew Booth, Ansgar Gerhardus, Eva Rehfuess, Daniel Hind, Patrick M Bossuyt, Vivian Welch, Thomas P A Debray, Martin Underwood and 4 more

Abstract read
In one paragraph

Article in BMC medical research methodology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 3 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

16 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Frontiers in genetics · 2025
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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

14 authors.

Ralph van HoornRadboud Institute for Health Sciences, Radboud university medical center, Geert Grooteplein 21, Nijmegen, 6525, EZ, The Netherlands. Ralph.vanHoorn@radboudumc.nl.ORCID 0000-0003-1413-1602
Marcia TummersRadboud Institute for Health Sciences, Radboud university medical center, Geert Grooteplein 21, Nijmegen, 6525, EZ, The Netherlands.
Andrew BoothHealth Economics and Decision Science (HEDS), School of Health and Related Research (ScHARR), University of Sheffield Regent Court, Sheffield, UK.
Ansgar GerhardusDepartment of Health Services Research, Institute for Public Health and Nursing Research, University of Bremen and Health Sciences Bremen, University of Bremen, Bremen, Germany.
Eva RehfuessInstitute for Medical Information Processing, Biometry and Epidemiology; Pettenkofer School of Public Health, LMU Munich, Munich, Germany.
Daniel HindClinical Trials Research Unit, University of Sheffield Regent Court, Sheffield, UK.
Patrick M BossuytDepartment of Clinical Epidemiology, Biostatistics, and Bioinformatics, University of Amsterdam, Amsterdam, The Netherlands.
Vivian WelchBruyère Institute, Ottawa, Canada.
Thomas P A DebrayJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University; Cochrane Netherlands, University Medical Center Utrecht, Utrecht, The Netherlands.
Martin UnderwoodWarwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK.
Pim CuijpersDepartment of Clinical, Neuro and Developmental Psychology, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Helena KraemerDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Gert Jan van der WiltDonders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands.
Wietkse KievitInstitute for Health Sciences, Radboud university medical center, Nijmegen, The Netherlands.

Funding

FP7 Health 2012 Innovation 306141
6 · The paper itself

Abstract

backgroundPersonalized healthcare relies on the identification of factors explaining why individuals respond differently to the same intervention. Analyses identifying such factors, so called predictors and moderators, have their own set of assumptions and limitations which, when violated, can result in misleading claims, and incorrect actions. The aim of this study was to develop a checklist for critically appraising the results of predictor and moderator analyses by combining recommendations from published guidelines and experts in the field.

methodsCandidate criteria for the checklist were retrieved through systematic searches of the literature. These criteria were evaluated for appropriateness using a Delphi procedure. Two Delphi rounds yielded a pilot checklist, which was tested on a set of papers included in a systematic review on reinforced home-based palliative care. The results of the pilot informed a third Delphi round, which served to finalize the checklist.

resultsForty-nine appraisal criteria were identified in the literature. Feedback was obtained from fourteen experts from (bio)statistics, epidemiology and other associated fields elicited via three Delphi rounds. Additional feedback from other researchers was collected in a pilot test. The final version of our checklist included seventeen criteria, covering the design (e.g. a priori plausibility), analysis (e.g. use of interaction tests) and results (e.g. complete reporting) of moderator and predictor analysis, together with the transferability of the results (e.g. clinical importance). There are criteria both for individual papers and for bodies of evidence.

conclusionsThe proposed checklist can be used for critical appraisal of reported moderator and predictor effects, as assessed in randomized or non-randomized studies using individual participant or aggregate data. This checklist is accompanied by a user's guide to facilitate implementation. Its future use across a wide variety of research domains and study types will provide insights about its usability and feasibility.

Indexed as

Delphi TechniqueChecklistDelivery of Health CareFeasibility StudiesHumansOutcome Assessment, Health CarePrecision MedicineReproducibility of ResultsResearch DesignDelphiEvidence based medicineModeratorPersonalized health carePredictorQuality assessmentSubgroup

Identifiers

PMID29268721
PMCPMC5740883

What OpenQuestion holds

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Registered trials

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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.