ReviewPharmacoEconomics2013
A methodological review of models used to estimate the cost effectiveness of antiretroviral regimens for the treatment of HIV infection.
Review in PharmacoEconomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Quantitative Evidence Synthesis Methods for the Assessment of the Effectiveness of Treatment Sequences for Clinical and Economic Decision Making: A Review and Taxonomy of Simplifying Assumptions.PharmacoEconomics · 2021Pooled it
- Cabotegravir and Rilpivirine Long-Acting Antiretroviral Therapy Administered Every 2 Months is Cost-Effective for the Treatment of HIV-1 in Spain.Infectious diseases and therapy · 2023Article
- Machine learning aided multiscale modelling of the HIV-1 infection in the presence of NRTI therapy.PeerJ · 2023Article
- Cost-effectiveness and budget impact of dolutegravir/lamivudine for treatment of human immunodeficiency virus (HIV-1) infection in the United States.Journal of managed care & specialty pharmacy · 2021Article
- Development and Use of Disease-Specific (Reference) Models for Economic Evaluations of Health Technologies: An Overview of Key Issues and Potential Solutions.PharmacoEconomics · 2015Article
- Cost effectiveness of darunavir/ritonavir combination antiretroviral therapy for treatment-naive adults with HIV-1 infection in Canada.PharmacoEconomics · 2014Article
- Modelling technique, structural assumptions, input parameter values: which has the most impact on the results of a cost-effectiveness analysis?PharmacoEconomics · 2014Article
- The Diffusion of Discrete Event Simulation Approaches in Health Care Management in the Past Four Decades: A Comprehensive Review.MDM policy & practiceReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this article was to perform a detailed methodological review of models used to estimate the cost effectiveness of drug treatment regimens for HIV infection in Europe and North America and assess the relationship between the different modeling approaches or key structural assumptions and the results. Electronic searches in three databases (MEDLINE, EMBASE, and the Cochrane Library) identified the cost-effectiveness models. Modeling approaches and structural assumptions were abstracted for all models. For three case studies of multiple analyses that compared the cost effectiveness of two drug regimens using the same clinical data inputs, differences in results were compared with differences in modeling approaches and structural assumptions. Forty-one model publications were reviewed. Recent models included Monte Carlo simulations, Markov models, or discrete-event simulation models, all including multiple lines of therapy and capturing the long-expected duration of efficacy of highly active antiretroviral therapy. In the three case studies, assumptions about the duration of efficacy after the trial time period, whether differences between the two regimens persist after the trial time period, the sequence of regimens after initial regimen failure, and the cost and utility assigned to adverse events, but not the modeling approach, were the most important factors in explaining differences in the results. As the models and treatment pathways get more complex, models should be validated using clinical trial data and local observational databases. The results of sensitivity analyses testing the impact of the structural assumptions that might change the results as identified in this review should also be presented in modeling papers.
Indexed as
Identifiers
24234860What OpenQuestion holds
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.