ArticleStatistics in medicine2020
Assessing the performance of population adjustment methods for anchored indirect comparisons: A simulation study.
Article in Statistics in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 4 of them syntheses that pooled it.
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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.
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Who cites it
41 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Methodological pitfalls in indirect treatment comparisons: insights from a recent systematic review and analysis for C3 glomerulopathy.Journal of comparative effectiveness research · 2026Pooled it
- Effect of Dexmedetomidine Dose on Reducing Delirium in Adults: An Indirect Comparison of Controlled Trials.Medical science monitor : international medical journal of experimental and clinical research · 2025Pooled it
- Systematic review and indirect treatment comparisons of ritlecitinib against baricitinib in alopecia areata.Journal of the European Academy of Dermatology and Venereology : JEADV · 2025Pooled it
- Survival trends using DPd vs. other triplets in early RRMM patients: a population-adjusted indirect treatment comparison.Future oncology (London, England) · 2025Pooled it
- Unanchored simulated treatment comparison on survival outcomes using parametric and Royston-Parmar models with application to lenvatinib plus pembrolizumab in renal cell carcinoma.BMC medical research methodology · 2025Trial
- Confounder Identification in Diffuse Large B-Cell Lymphoma: Findings from an Expert Panel of German and Austrian Hematologists.Advances in therapy · 2026Article
- Oral Semaglutide 25 mg Versus Orforglipron 36 mg in Obesity: A Population-Adjusted Indirect Treatment Comparison.Diabetes, obesity & metabolism · 2026Article
- Indirect Comparative Efficacy and Safety of Tirzepatide Versus Oral Semaglutide for the Treatment of Overweight and Obesity.Diabetes, obesity & metabolism · 2026Article
- Missing Data Handling in the Application of Matching-Adjusted Indirect Comparison.Therapeutic innovation & regulatory science · 2026Article
- Between Rigor and Relevance: Why the EU HTA Guidelines on Indirect Comparisons Miss the Mark.Journal of market access & health policy · 2026Article
- Can We Trust PAICs in Rare Diseases? Methodological Challenges and Limitations.Journal of market access & health policy · 2026Article
- The Comparative Effectiveness of Enlonstobart and Camrelizumab as Second-Line Recurrent or Metastatic Cervical Cancer Therapies: Matching-Adjusted and Simulated Treatment Comparisons.ImmunoTargets and therapy · 2026Article
- A Review of Methods for Research Synthesis.Statistics in medicine · 2025Article
- An Indirect Treatment Comparison of Avalglucosidase Alfa versus Cipaglucosidase Alfa Plus Miglustat in Patients with Late-Onset Pompe Disease.Advances in therapy · 2025Article
- Regression augmented weighting adjustment for indirect comparisons in health decision modelling.Research synthesis methods · 2025Article
- Efficacy of Intravitreal Pegcetacoplan vs Avacincaptad Pegol in Patients With Geographic Atrophy.Journal of vitreoretinal diseases · 2025Article
- Accounting for Misclassification of Binary Outcomes in External Control Arm Studies for Unanchored Indirect Comparisons: Simulations and Applied Example.Statistics in medicine · 2025Article
- Is the Use of Unanchored Matching-Adjusted Indirect Comparison Always Superior to Naïve Indirect Comparison on Survival Outcomes? A Simulation Study.Applied health economics and health policy · 2025Article
- A Framework for Reliable, Transparent, and Reproducible Population-Adjusted Indirect Comparisons.PharmacoEconomics · 2025Article
- Treatment recommendations based on network meta-analysis: Rules for risk-averse decision-makers.Research synthesis methods · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
Standard network meta-analysis and indirect comparisons combine aggregate data from multiple studies on treatments of interest, assuming that any factors that interact with treatment effects (effect modifiers) are balanced across populations. Population adjustment methods such as multilevel network meta-regression (ML-NMR), matching-adjusted indirect comparison (MAIC), and simulated treatment comparison (STC) relax this assumption using individual patient data from one or more studies, and are becoming increasingly prevalent in health technology appraisals and the applied literature. Motivated by an applied example and two recent reviews of applications, we undertook an extensive simulation study to assess the performance of these methods in a range of scenarios under various failures of assumptions. We investigated the impact of varying sample size, missing effect modifiers, strength of effect modification and validity of the shared effect modifier assumption, validity of extrapolation and varying between-study overlap, and different covariate distributions and correlations. ML-NMR and STC performed similarly, eliminating bias when the requisite assumptions were met. Serious concerns are raised for MAIC, which performed poorly in nearly all simulation scenarios and may even increase bias compared with standard indirect comparisons. All methods incur bias when an effect modifier is missing, highlighting the necessity of careful selection of potential effect modifiers prior to analysis. When all effect modifiers are included, ML-NMR and STC are robust techniques for population adjustment. ML-NMR offers additional advantages over MAIC and STC, including extending to larger treatment networks and producing estimates in any target population, making this an attractive choice in a variety of scenarios.
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Registered trials
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.