Cost-Effectiveness of Mirogabalin for the Treatment of Diabetic Peripheral Neuropathic Pain in Taiwan

Abstract

Objectives

To assess the cost-effectiveness of 30 mg of mirogabalin versus no treatment or 300 mg of pregabalin in patients with diabetic peripheral neuropathic pain (DPNP) from a third-party perspective in Taiwan.

Methods

A Markov model, developed with cycles of 2-week and a 1-year timeframes, consisted of 3 health states: mild, moderate, and severe pain. Average daily pain score (ADPS) was assessed at the end of each 2-week cycle. All patients entered the model in moderate (4 ≤ ADPS 7) or severe (7 ≤ ADPS ≤ 10) pain health states. At the end of each cycle, patients remained in their assigned health state or transitioned to a different health state according to their pain score change. Efficacy data were informed by the pivotal phase III clinical trial (J303, NCT02318706) or by a network meta-analysis. Utility values were obtained from published literature, and resource use and cost data from Taiwanese clinical experts and Taiwan National Health Insurance Administration. One-way sensitivity, scenario, and probabilistic analyses were conducted to test the robustness of the results.

Results

A head-to-head analysis demonstrated that 30 mg of mirogabalin is a cost-effective treatment option versus placebo for DPNP. The base-case deterministic analysis estimated quality-adjusted life years (QALY) gains of 0.02 at an incremental cost of 9697 New Taiwan dollars (NT$) (equal to $323) versus placebo (incremental cost-effectiveness ratio [ICER]: 489 310 NT$/QALY [$15 860/QALY]). Mirogabalin was also cost-effective compared with 300 mg of pregabalin (ICER: 18 476 NT$/QALY [$600/QALY]). Sensitivity and scenario analyses results confirmed the robustness.

Conclusion

Economic analysis suggests that mirogabalin 30 mg, a potent and selective α2δ ligand, is a cost-effective treatment option for DPNP in Taiwan, with an ICER below the willingness-to-pay threshold.

Authors

Emma Gray Xin Ye Yen-Feng Wang Shuu-Jiun Wang

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