65 citations · 203 across the 11 of their papers we have counts for
11 papers
Effect modification and non-collapsibility leads to conflicting treatment decisions: a review of marginal and conditional estimands and recommendations for decision-making
David M. Phillippo, Antonio Remiro-Azócar, Anna Heath +4
Effect modification occurs when a covariate alters the relative effectiveness of treatment compared to control. It is widely understood that, when effect modification is present, t…
Broad versus narrow research questions in evidence synthesis: a parallel to (and plea for) estimands
Antonio Remiro-Azócar, Anders Gorst-Rasmussen
There has been a transition from broad to more specific research questions in the practice of network meta-analysis (NMA). Such convergence is also taking place in the context of i…
Methodological considerations for novel approaches to covariate-adjusted indirect treatment comparisons
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
We examine four important considerations in the development of covariate adjustment methodologies for indirect treatment comparisons. Firstly, we consider potential advantages of w…
Model-based standardization using multiple imputation
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
When studying the association between treatment and a clinical outcome, a parametric multivariable model of the conditional outcome expectation is often used to adjust for covariat…
Transportability of model-based estimands in evidence synthesis
Antonio Remiro-Azócar
In evidence synthesis, effect modifiers are typically described as variables that induce treatment effect heterogeneity at the individual level, through treatment-covariate interac…
Two-stage matching-adjusted indirect comparison
Antonio Remiro-Azócar
Anchored covariate-adjusted indirect comparisons inform reimbursement decisions where there are no head-to-head trials between the treatments of interest, there is a common compara…
Target estimands for population-adjusted indirect comparisons
Antonio Remiro-Azócar
Disagreement remains on what the target estimand should be for population-adjusted indirect treatment comparisons. This debate is of central importance for policy-makers and applie…
Parametric G-computation for Compatible Indirect Treatment Comparisons with Limited Individual Patient Data
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial difference…
Conflating marginal and conditional treatment effects: Comments on 'Assessing the performance of population adjustment methods for anchored indirect comparisons: A simulation study'
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
In this commentary, we highlight the importance of: (1) carefully considering and clarifying whether a marginal or conditional treatment effect is of interest in a population-adjus…
Effect modification in anchored indirect treatment comparisons: Comments on "Matching-adjusted indirect comparisons: Application to time-to-event data"
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
This commentary regards a recent simulation study conducted by Aouni, Gaudel-Dedieu and Sebastien, evaluating the performance of different versions of matching-adjusted indirect co…
Methods for Population Adjustment with Limited Access to Individual Patient Data: A Review and Simulation Study
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
Population-adjusted indirect comparisons estimate treatment effects when access to individual patient data is limited and there are cross-trial differences in effect modifiers. Pop…