医学
荟萃分析
置信区间
成本效益
检查表
成本效益分析
系统回顾
成本-效用分析
依那西普
类风湿性关节炎
出版偏见
梅德林
内科学
风险分析(工程)
心理学
政治学
法学
认知心理学
作者
S. Sajith Kumar,Bhavani Shankara Bagepally
标识
DOI:10.1080/14737167.2023.2249610
摘要
ABSTRACTObjective To systematically review the cost-utility evidence of TNF-a-i treatment for rheumatoid arthritis (RA) and to estimate the pooled incremental net benefit (INBp).Methods We selected economic evaluation studies reporting the cost-utility of TNF-a-i compared to other disease-modifying anti-rheumatic drugs (DMARDs) after a systematic search in PubMed, Embase, Scopus, and Tufts Medical Centers' cost-effective analysis registry. The results were reported as pooled INB in purchasing power parity-adjusted US dollars, along with 95% confidence intervals. We used GRADE quality assessment to present summaries of evidence and random-effects meta-analysis to synthesize cost-utility of TNF-a-i.Results We included 86 studies for systematic review, of which 27 for meta-analysis. TNF-a-i is not cost-effective [$ −4,129(−6,789 to −1,469)] compared to other DMARDs but with high heterogeneity. There was no evidence of publication bias (p = 0.447). On separate analysis, TNF-a-i is not cost-effective [$ −4,805(−7,882 to −1,728)] compared to conventional synthetic DMARDs for RA treatment. GRADE assessment indicated very low confidence in pooled cost-utility results and likely presence of risk of bias on the overall ECOBIAS checklist in studies.Conclusion Based on the available evidence during the study period, TNF-a-i is not a cost-effective option for treating RA compared to other DMARDs. However, high heterogeneity and low confidence in GRADE quality assessment preclude the results from being generalizable.KEYWORDS: TNF-i-acost-effectivenessrheumatoid arthritisbiologics Declaration of interestThe authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.Reviewer disclosuresPeer reviewers on this manuscript have no relevant financial or other relationships to disclose.Author contributionS Kumar: Data curation, original draft. B Bagepally: Conceptualisation, Data curation, Formal analysis, review & editing. All authors read and approved the final version of the manuscript for publication.Supplementary MaterialSupplemental data for this article can be accessed online at https://doi.org/10.1080/14737167.2023.2249610Additional informationFundingThe authors received no specific funding for this work. However, the Dept. of Health Research, Govt. of India funds the Health Technology Assessment resource center ICMR-NIE. Funders had no role in the study conceptualization, conduction, and manuscript preparation.
科研通智能强力驱动
Strongly Powered by AbleSci AI