ReviewInternational journal of preventive medicine2025
Economic Evaluation of Medications in Prevention and Treatment of Obesity: A Systematic Review.
Review in International journal of preventive medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Review
- Advances in the management of obesity: non-pharmacological strategies, herbal formulations, current pharmacotherapy, emerging drugs, and future perspectives.Frontiers in endocrinology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Obesity imposes a heavy burden on healthcare systems and society. Despite various treatment options, choosing cost-effective pharmacological interventions remains a key concern for health policymakers. This study systematically reviews economic evaluations of antiobesity drugs, comparing their costs and outcomes with those of lifestyle interventions. Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Four databases (PubMed, Scopus, Web of Science, and Embase) were searched for full economic evaluations of FDA-approved antiobesity drugs, including semaglutide, liraglutide, tirzepatide, phentermine-topiramate, and orlistat. Inclusion criteria required studies to report cost-effectiveness, cost-utility, or cost-benefit outcomes. Data on incremental cost-effectiveness ratios (ICERs), quality-adjusted life years (QALY), or disability-adjusted life years (DALY) were extracted and adjusted to 2024 USD using PPP. Study quality was assessed using CHEERS 2022. Results: Fifteen studies met the inclusion criteria. Most used Markov models and cost-effectiveness analyses. The review of articles showed that 60% of the articles were conducted in the United States of America, 33.33% of the articles in Europe, and 6.66% of the articles in Australia. Among the reviewed studies, semaglutide was found to be the most cost-effective and clinically effective drug in most scenarios. Phentermine-topiramate showed acceptable cost-effectiveness, particularly in low-resource settings. Orlistat and naltrexone-bupropion were also considered affordable options, though with lower effectiveness. Tirzepatide, despite its high efficacy, demonstrated a higher ICER, making its cost-effectiveness context-dependent. Conclusions: These findings highlight the importance of integrating cost-effective pharmacological treatments into obesity management strategies. Semaglutide appears to be a highly effective and economically favorable option, while phentermine-topiramate and orlistat offer practical alternatives in resource-limited settings. Economic evaluations can inform policy decisions and optimize healthcare resource allocation in combating obesity.
Indexed as
Identifiers
What 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.