A Novel Approach for Identifying and Addressing Case-Mix Heterogeneity in Individual Participant Data Meta-Analysis
In: Research Synthesis Methods, Jg. 10 (2019-12-01), Heft 4, S. 582-596
Online
academicJournal
Zugriff:
Case-mix heterogeneity across studies complicates meta-analyses. As a result of this, treatments that are equally effective on patient subgroups may appear to have different effectiveness on patient populations with different case mix. It is therefore important that meta-analyses be explicit for what patient population they describe the treatment effect. To achieve this, we develop a new approach for meta-analysis of randomized clinical trials, which use individual patient data (IPD) from all trials to infer the treatment effect for the patient population in a given trial, based on direct standardization using either outcome regression (OCR) or inverse probability weighting (IPW). Accompanying random-effect meta-analysis models are developed. The new approach enables disentangling heterogeneity due to case mix from that due to beyond case-mix reasons.
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A Novel Approach for Identifying and Addressing Case-Mix Heterogeneity in Individual Participant Data Meta-Analysis
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Autor/in / Beteiligte Person: | Vo, Tat-Thang ; Porcher, Raphael ; Chaimani, Anna ; Vansteelandt, Stijn |
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Zeitschrift: | Research Synthesis Methods, Jg. 10 (2019-12-01), Heft 4, S. 582-596 |
Veröffentlichung: | 2019 |
Medientyp: | academicJournal |
ISSN: | 1759-2879 (print) |
DOI: | 10.1002/jrsm.1382 |
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