Model-based meta-analysis to compare primary efficacy-endpoint, efficacy-time course, safety and tolerability of opioids used in the management of osteoarthritic pain in humans

止痛药 随机对照试验 安慰剂 内科学 类阿片 慢性疼痛
作者
Suhaila Omar Alhaj-Suliman,Gary Milavetz,Aliasger K. Salem
出处
期刊:Current Drug Metabolism [Bentham Science]
卷期号:21 (5): 390-399 被引量:1
标识
DOI:10.2174/1389200221666200514130441
摘要

Background Despite recent therapeutic advances, osteoarthritis continues to be a challenging health problem, especially in the elderly population. Opioids, which are potent analgesics, have shown an extraordinary ability to reduce intense pain in many osteoarthritic clinical trials; however, there is an increased need for a study to integrate the reported outcomes and utilize them to achieve a better understanding. Herein, efficacy and safety aspects of opioids used to manage osteoarthritic pain were assessed and compared using a model-based meta-analysis (MBMA). Methods To perform the analysis, a comprehensive database consisting of pain relief compounds with information on summary-level of efficacy over time, adverse events and dropout rates was compiled from multiple sources. MBMA was conducted using a nonlinear mixed-effects modeling approach. Results The results of primary efficacy endpoint analysis indicated that the doses of oxycodone, oxymorphone, and tramadol required to produce 50% of the maximum effect were 47, 84, and 247 mg per day, respectively. Efficacytime course analysis showed that opioids had rapid time to efficacy onset, suggesting potentially powerful painrelieving effects. It was also found that gastrointestinal adverse events were the most opioid-associated and dosedependent adverse effects. In addition, the analysis revealed that opioids were well-tolerated at low to moderate doses. Conclusion This MBMA provides clinically meaningful insights into the efficacy and safety profiles of oxycodone, oxymorphone, and tramadol. Resultantly, the presented framework analysis can have an impact in the clinic on drug development where it can guide: the optimization of doses of opioids required to manage osteoarthritic pain; the making of precise key decisions for the positioning of new drugs, and; the design of more efficient trials.

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