Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Pivot Concepts:
Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Target Concepts:
Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Query: UMLS:C0026764 (
multiple myeloma
)
36,148
document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)
If
IPD
is available for some or all trials in a network meta-analysis (NMA), then incorporating this
IPD
into an NMA is routinely considered to be preferable. However, the situation often arises where a researcher has
IPD
for trials concerning a particular treatment (eg, from a sponsor) but none for other trials. Therefore, one can reweight the
IPD
so that the covariate characteristics in the
IPD
trials match that of the aggregate data (AgD) trials, using a matching-adjusted indirect comparison (MAIC). We assess the impact of using the reweighted aggregated data, obtained by the MAIC, in a Bayesian NMA for a connected treatment network. We apply this method to a network of
multiple myeloma
treatments in newly diagnosed patients (ndMM), where the outcome is progression free survival. We investigate the reliability of the methods and results through a simulation study. The ndMM network consists of three
IPD
studies comparing lenalidomide to placebo (Len-Placebo), one AgD study comparing Len-Placebo, and one AgD study comparing thalidomide to placebo (Thal-Placebo). We therefore investigate two options of weighting the covariates: (a) All three studies are weighted separately to match the AgD Thal-Placebo trial. (b) Patients are weighted across all three
IPD
studies to match the AgD Thal-Placebo trial, but the NMA considers each trial separately. We observe limited benefit to MAIC in the full network population. While MAIC can be beneficial as a sensitivity analysis to confirm results across patient populations, we advise that MAIC is used and interpreted with caution.
...
PMID:Assessing the impact of a matching-adjusted indirect comparison in a Bayesian network meta-analysis. 3136 53