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Real-world cost-effectiveness of sequential therapy of in-class transition to ixazomib versus daratumumab for transplant-ineligible newly diagnosed multiple myeloma in China

Year: 2026
Type: article
Abstract: Aim: Expanding treatment options for transplant-ineligible newly diagnosed multiple myeloma (ndMM) in China has increased the need to identify treatment strategies that improve patient outcomes while using healthcare resources efficiently. This study evaluated the cost-effectiveness of in-class transition (iCT) to ixazomib, lenalidomide and dexamethasone (IRd) versus daratumumab, lenalidomide and dexamethasone (DRd) for transplant-ineligible ndMM from the perspective of the Chinese healthcare system. Materials & methods: A cost-effectiveness analysis was conducted using a Markov cohort model that simulated lifetime health benefits and medical costs for the two treatment modalities. Model inputs were estimated from best available real-world evidence in the literature and from public data sources. Deterministic, probabilistic and scenario sensitivity analyses were performed to assess uncertainty in model results. Results: In the base-case analysis, iCT IRd was projected to generate 0.580 additional quality-adjusted life years versus DRd (4.724 vs 4.144) and save lifetime medical costs by $7751. One-way sensitivity analysis indicated that cost-effectiveness was driven by uncertainty in model inputs related to treatment discontinuation and subsequent disease progression. Probabilistic sensitivity analysis estimated that iCT IRd had 79.2%, 88.0% and 91.3% probabilities of being cost-effective at willingness-to-pay thresholds of one, two and three-times China’s 2025 gross domestic product per capita per quality-adjusted life year, respectively. Conclusion: Based on best available real-world evidence, the iCT IRd modality could be cost-effective compared with the DRd modality for transplant-ineligible patients with ndMM in China. Future real-world studies are needed to confirm the projected outcomes.
Language: English
Subfield: Hematology
Field: Medicine
Open Access status: diamond
OpenAlex ID: W7221616330
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Cites: 37
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