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.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9635741 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0274136 | PLOS |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!