Cost-effectiveness analysis of a prognostic risk assessment for early-stage 1-3b diabetic kidney disease patients in the United States.

IF 3.1 4区 医学 Q3 HEALTH POLICY & SERVICES
Jacie T Cooper, John E Schneider, Thomas Mclain, Steven Coca, Michael J Donovan
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引用次数: 0

Abstract

Background: Diabetic kidney disease (DKD) accounts for 44% of new chronic kidney disease cases and is associated with significant morbidity and mortality. Although sodium-glucose co-transporter-2 inhibitors (SGLT2is) can reduce cardiorenal outcomes, current DKD staging relying on eGFR and albuminuria (KDIGO risk categories) leaves SGLT2is underutilized in clinical practice. A new biomarker-enriched, AI-enabled risk score (KidneyIntelX™; Renalytix, Inc.) was developed to predict a progressive decline in kidney function in patients with early-stage DKD. KidneyIntelX categorizes patients as low, intermediate, or high risk for disease progression, which can guide resource utilization, prescribing of drugs such as SGLT2is, and improvements in efficiency of care. We report a cost-effectiveness analysis comparing DKD patient stratification with KidneyIntelX to KDIGO by generating an incremental cost effectiveness ratio (ICER).

Methods: The model adopted a U.S. Medicare perspective and consisted of patients with DKD in stages G1-3b using KidneyIntelX or KDIGO. A 10-state Markov state transition structure was employed over a lifetime horizon which includes DKD stages 1-5, dialysis, kidney transplant, cardiovascular (CV) death, and non-CV death. Transition probabilities and risk group distributions for KidneyIntelX and KDIGO were sourced from a KidneyIntelX validation study. Evaluation resulting from KidneyIntelX or KDIGO informed SGLT2i use in the model. Cost inputs included testing, medications, and office visit costs, as well as annual costs for each DKD stage, dialysis, and kidney transplant. Quality of life for each disease state was captured as utility values informed by literature.

Results: The modeled use of SGLT2i directed by KidneyIntelX led to a reduction in kidney disease progression (ESKD) and CV events, as well as dialysis starts, dialysis crashes, and kidney transplants compared to KDIGO-guided treatment. KidneyIntelX patients also spent less time in DKD stages 4 and 5 and more time in 1 through 3b. KidneyIntelX led to cost savings of about $514 per patient and quality-adjusted life year (QALY) gains of 0.028, resulting in a negative ICER. Combining SGLT2i with MRA's further increased per patient cost savings to $530 for Medicare participants.

Conclusions: Wide deployment of KidneyIntelX in Medicare patients with DKD G1-3b is expected to be cost-effective compared to KDIGO from the Medicare perspective, with a negative, dominant ICER.

美国早期1-3b期糖尿病肾病患者预后风险评估的成本-效果分析
背景:糖尿病肾病(DKD)占新发慢性肾病病例的44%,并与显著的发病率和死亡率相关。尽管钠-葡萄糖共转运蛋白-2抑制剂(SGLT2is)可以降低心肾预后,但目前依赖于eGFR和蛋白尿(KDIGO风险类别)的DKD分期使SGLT2is在临床实践中未得到充分利用。一种新的富含生物标志物的ai风险评分(KidneyIntelX™;Renalytix, Inc.)被开发出来,用于预测早期DKD患者肾功能的进行性下降。KidneyIntelX将患者按照疾病进展的低、中、高风险进行分类,这可以指导资源利用、SGLT2is等药物的处方以及提高护理效率。我们报告了一项成本-效果分析,通过产生增量成本-效果比(ICER),比较了使用KidneyIntelX和KDIGO的DKD患者分层。方法:该模型采用美国Medicare视角,由G1-3b期DKD患者组成,使用KidneyIntelX或KDIGO。采用10状态马尔可夫状态转换结构,包括DKD阶段1-5、透析、肾移植、心血管(CV)死亡和非CV死亡。KidneyIntelX和KDIGO的转移概率和风险组分布来源于一项KidneyIntelX验证研究。KidneyIntelX或KDIGO的评估结果决定了在模型中使用SGLT2i。成本投入包括检测、药物和办公室就诊费用,以及每个DKD阶段、透析和肾移植的年度费用。每一种疾病状态的生活质量被捕获为文献所告知的效用值。结果:与kdigo指导的治疗相比,由KidneyIntelX指导的SGLT2i模型使用导致肾脏疾病进展(ESKD)和CV事件减少,以及透析开始、透析崩溃和肾移植。kidney yintelx患者在DKD 4期和5期的时间更短,在1至3b期的时间更长。KidneyIntelX导致每位患者节省约514美元的成本和0.028的质量调整生命年(QALY)收益,导致负ICER。将SGLT2i与MRA相结合,进一步增加了医疗保险参与者的每位患者成本节约至530美元。结论:从医疗保险的角度来看,与KDIGO相比,在患有DKD G1-3b的医疗保险患者中广泛部署KidneyIntelX预计具有成本效益,具有负的显性ICER。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cost Effectiveness and Resource Allocation
Cost Effectiveness and Resource Allocation HEALTH POLICY & SERVICES-
CiteScore
3.40
自引率
4.30%
发文量
59
审稿时长
34 weeks
期刊介绍: Cost Effectiveness and Resource Allocation is an Open Access, peer-reviewed, online journal that considers manuscripts on all aspects of cost-effectiveness analysis, including conceptual or methodological work, economic evaluations, and policy analysis related to resource allocation at a national or international level. Cost Effectiveness and Resource Allocation is aimed at health economists, health services researchers, and policy-makers with an interest in enhancing the flow and transfer of knowledge relating to efficiency in the health sector. Manuscripts are encouraged from researchers based in low- and middle-income countries, with a view to increasing the international economic evidence base for health.
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