A comparison of the statistical performance of different meta-analysis models for the synthesis of subgroup effects from randomized clinical trials.

Da Costa, Bruno R; Sutton, Alex J (2019). A comparison of the statistical performance of different meta-analysis models for the synthesis of subgroup effects from randomized clinical trials. BMC Medical research methodology, 19(1), p. 198. BioMed Central 10.1186/s12874-019-0831-8

[img]
Preview
Text
daCosta BMCMedResMethodol 2019.pdf - Published Version
Available under License Creative Commons: Attribution (CC-BY).

Download (2MB) | Preview

BACKGROUND When investigating subgroup effects in meta-analysis, it is unclear whether accounting in meta-regression for between-trial variation in treatment effects, but not between-trial variation in treatment interaction effects when such effects are present, leads to biased estimates, coverage problems, or wrong standard errors, and whether the use of aggregate data (AD) or individual-patient-data (IPD) influences this assessment. METHODS Seven different models were compared in a simulation study. Models differed regarding the use of AD or IPD, whether they accounted for between-trial variation in interaction effects, and whether they minimized the risk of ecological fallacy. RESULTS Models that used IPD and that allowed for between-trial variation of the interaction effect had less bias, better coverage, and more accurate standard errors than models that used AD or ignored this variation. The main factor influencing the performance of models was whether they used IPD or AD. The model that used AD had a considerably worse performance than all models that used IPD, especially when a low number of trials was included in the analysis. CONCLUSIONS The results indicate that IPD models that allow for the between-trial variation in interaction effects should be given preference whenever investigating subgroup effects within a meta-analysis.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Medical Education > Institute of General Practice and Primary Care (BIHAM)

UniBE Contributor:

Da Costa, Bruno

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services

ISSN:

1471-2288

Publisher:

BioMed Central

Language:

English

Submitter:

Doris Kopp Heim

Date Deposited:

29 Oct 2019 14:42

Last Modified:

31 Oct 2019 09:30

Publisher DOI:

10.1186/s12874-019-0831-8

PubMed ID:

31655550

Uncontrolled Keywords:

Evidence synthesis Individual patient data Interaction effects Meta-analysis Random-effects Subgroup analysis

BORIS DOI:

10.7892/boris.134370

URI:

https://boris.unibe.ch/id/eprint/134370

Actions (login required)

Edit item Edit item
Provide Feedback