ArticlePharmacoEconomics2019
Trusting the Results of Model-Based Economic Analyses: Is there a Pragmatic Validation Solution?
Article in PharmacoEconomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 4 of them syntheses 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, 4 syntheses or guidelines pooled it.
- Economic evaluations of vaccines against respiratory infections in adults in Southeast Asia: A systematic review.Human vaccines & immunotherapeutics · 2025Pooled it
- Developing a Comprehensive Framework for Cost-Effectiveness Evaluation in Metastatic Castration-Sensitive Prostate Cancer: Insights from a Systematic Review.PharmacoEconomics · 2025Pooled 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
- Systematic Literature Review of Economic Evaluations of Biological Treatment Sequences for Patients with Moderate to Severe Rheumatoid Arthritis Previously Treated with Disease-Modifying Anti-rheumatic Drugs.PharmacoEconomics · 2020Pooled it
- Evaluating the Validation Process: Embracing Complexity and Transparency in Health Economic Modelling.PharmacoEconomics · 2024Article
- Four Aspects Affecting Health Economic Decision Models and Their Validation.PharmacoEconomics · 2022Article
- Cooking Up a Transparent Model Following a DICE Recipe.PharmacoEconomics · 2019Article
- An Educational Review About Using Cost Data for the Purpose of Cost-Effectiveness Analysis.PharmacoEconomics · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Models have become a nearly essential component of health technology assessment. This is because the efficacy and safety data available from clinical trials are insufficient to provide the required estimates of impact of new interventions over long periods of time and for other populations and subgroups. Despite more than five decades of use of these decision-analytic models, decision makers are still often presented with poorly validated models and thus trust in their results is impaired. Among the reasons for this vexing situation are the artificial nature of the models, impairing their validation against observable data, the complexity in their formulation and implementation, the lack of data against which to validate the model results, and the challenges of short timelines and insufficient resources. This article addresses this crucial problem of achieving models that produce results that can be trusted and the resulting requirements for validation and transparency, areas where our field is currently deficient. Based on their differing perspectives and experiences, the authors characterize the situation and outline the requirements for improvement and pragmatic solutions to the problem of inadequate validation.
Indexed as
Identifiers
30187294What Socratic 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 Socratic graph.