Evidence map›Paper›PMID 24234860›Full record

ReviewPharmacoEconomics2013

A methodological review of models used to estimate the cost effectiveness of antiretroviral regimens for the treatment of HIV infection.

Josephine Mauskopf

Abstract readReview
PubMed Publisher
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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  8. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Josephine Mauskopf

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Models, EconomicAnti-HIV AgentsAntiretroviral Therapy, Highly ActiveCost-Benefit AnalysisEuropeHIV InfectionsHumansMarkov ChainsMonte Carlo MethodNorth AmericaTime FactorsAnti-HIV Agents

Identifiers

What OpenQuestion holds

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Registered trials

None linked

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.