Abstract
OBJECTIVE: To conduct a systematic, multi-dimensional clinical evaluation of five long-acting glucagon-like peptide-1 receptor agonists (GLP-1RAs) available in China, providing evidence-based guidance for clinical preference and institutional formulary selection. METHODS: This study was structured according to the "A Quick Guideline for Drug Evaluation and Selection in Chinese Medical Institutions. (Second Edition)" and the "Guidelines for the Workflow of Clinical Comprehensive Evaluation of Drugs" We constructed a quantitative evaluation system encompassing six core dimensions: efficacy, safety, economy, innovation, suitability, and accessibility. Indicator weights were determined via a Delphi expert consultation process. Dulaglutide, semaglutide, polyethylene glycol loxenatide, tirzepatide, and mazdutide were evaluated using a 100-point scoring system based on drug labels, systematic literature review, and real-world data. RESULTS: The comprehensive scores were as follows: semaglutide (76.6), dulaglutide (72.6), polyethylene glycol loxenatide (64.8), tirzepatide (62.9), and mazdutide (55.1). Semaglutide and dulaglutide, classified as Strong Recommendations, demonstrated superior efficacy (particularly in cardio-renal protection) and overall value. Tirzepatide and polyethylene glycol loxenatide were Conditionally Recommended; the former shows outstanding potential for glycaemic control and weight loss but is limited by cost, while the latter offers advantages in accessibility and economy but lacks high-level cardiovascular outcome evidence. Mazdutide is Not Recommended currently due to insufficient evidence, absence from the national reimbursement drug list, and high cost. CONCLUSION: This evaluation identifies semaglutide and dulaglutide as the preferred long-acting GLP-1RAs in China's current therapeutic landscape. The standardized, transparent six-dimensional framework provides a replicable methodology for the comprehensive assessment of chronic disease therapies, supporting rational drug selection and resource allocation.