Abstract
Background and objectives
To simulate the cost-effectiveness of Mesenchymal Stromal Cell (MSC) therapy compared to sodium/glucose co-transporter 2 inhibitors (SGLT2i) or usual care (UC) in treating patients with Diabetic Kidney Disease (DKD).
Design, setting, participants, and measurements
This Markov-chain Monte Carlo model adopted a societal perspective and simulated 10,000 patients with DKD eligible for MSC therapy alongside UC using a lifetime horizon. This cohort was compared with an SGLT2i alongside UC arm and a UC only arm. Model input data were extracted from the literature. A threshold of $47,000 per quality-adjusted life year and a discount rate of 3% were used. The primary outcome measure was incremental net monetary benefit (INMB). Sensitivity analysis was conducted to examine: parameter uncertainty; threshold effects regarding MSC effectiveness and cost; and INMB according to patient age (71 vs 40 years), sex, and jurisdiction (UK, Italy and Ireland).
Results
While MSC was more cost-effective than UC, both the UC and MSC arms were dominated by SLGT2i. Relative to SGLT2i, the INMB’s for MSC and UC were -$4,158 and -$10,085 respectively indicating that SGLT2i, MSC and UC had a 64%, 34% and 1% probability of being cost-effective at the given threshold, respectively. This pattern was consistent across most scenarios; driven by the relatively low cost of SGLT2i and demonstrated class-effect in delaying kidney failure and all-cause mortality. When examining younger patients at baseline, SGLT2i was still the most cost-effective but MSC performed better against UC given the increased lifetime benefit from delaying progression to ESRD.
Conclusions
The evidence base regarding the effectiveness of MSC therapy continues to evolve. The potential for these therapies to reverse kidney damage would see large improvements in their cost-effectiveness as would targeting such therapies at younger patients and/or those for whom SGLT2i is contra-indicated.
Funder
Horizon 2020
Science Foundation Ireland
Publisher
Public Library of Science (PLoS)
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