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.

2020 
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 summarylevel 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. Efficacy-time course analysis showed that opioids had rapid time to efficacy onset, suggesting potentially powerful pain-relieving effects. It was also found that gastrointestinal adverse events were the most opioid-associated and dose-dependent adverse effects. In addition, the analysis revealed that opioids were well-tolerated at low to moderate doses. CONCLUSIONS: 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 more efficient trials.
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