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Sparsentan for the Treatment of Immunoglobin A Nephropathy: An Innovative Method of Economic Modelling

Submitted:

24 April 2026

Posted:

27 April 2026

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Abstract
Background/Objectives: Immunoglobin A nephropathy (IgAN) is a type of chronic kidney disease (CKD) and the most common cause of kidney failure in patients <40 years of age. Previous economic models in CKD have generally defined health states solely by the progression of CKD. This manuscript presents an alternative method which also considers the level of proteinuria in a CKD patient. Methods: A cohort-level state transition model was developed comparing the health benefits of sparsentan, a dual endothelin angiotensin receptor antagonist, to irbesartan, an angiotensin receptor blocker, in IgAN. Within four UP/C (proteinuria) states, patients are assigned to three sub-health states according to CKD stage. Patients with end-stage renal disease are grouped together irrespective of UP/C, and are stratified instead by renal replacement therapy modality. Transition matrices are derived from a combination of data from PROTECT, a clinical trial comparing sparsentan to irbesartan, and the UK RaDaR registry. Health-related quality of life data from a general CKD population is used as a proxy. Results: Patients with IgAN who were modelled to receive treatment with sparsentan had estimated total undiscounted life years of 25.5 years, a gain of 0.9 years in comparison with irbesartan. Patients were also more likely to spend more time in earlier CKD stages while pre-ESRD. This translated to significant quality adjusted life year gains for patients treated with sparsentan in comparison with irbesartan. Conclusions: This study presents a new structure for health economic models in IgAN that more comprehensively captures the effect of proteinuria in combination with CKD progression. This new approach ultimately allows for the more robust implementation of clinical trial data in IgAN and estimates of the cost-effectiveness of new treatments.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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