Willis Michael, Asseburg Christian, Nilsson Andreas, Johnsson Kristina, Kartman Bernt
The Swedish Institute for Health Economics, Lund, Sweden.
The Swedish Institute for Health Economics, Lund, Sweden.
Value Health. 2017 Mar;20(3):357-371. doi: 10.1016/j.jval.2016.10.004. Epub 2016 Dec 1.
Type 2 diabetes mellitus (T2DM) is chronic and progressive and the cost-effectiveness of new treatment interventions must be established over long time horizons. Given the limited durability of drugs, assumptions regarding downstream rescue medication can drive results. Especially for insulin, for which treatment effects and adverse events are known to depend on patient characteristics, this can be problematic for health economic evaluation involving modeling.
To estimate parsimonious multivariate equations of treatment effects and hypoglycemic event risks for use in parameterizing insulin rescue therapy in model-based cost-effectiveness analysis.
Clinical evidence for insulin use in T2DM was identified in PubMed and from published reviews and meta-analyses. Study and patient characteristics and treatment effects and adverse event rates were extracted and the data used to estimate parsimonious treatment effect and hypoglycemic event risk equations using multivariate regression analysis.
Data from 91 studies featuring 171 usable study arms were identified, mostly for premix and basal insulin types. Multivariate prediction equations for glycated hemoglobin A lowering and weight change were estimated separately for insulin-naive and insulin-experienced patients. Goodness of fit (R) for both outcomes were generally good, ranging from 0.44 to 0.84. Multivariate prediction equations for symptomatic, nocturnal, and severe hypoglycemic events were also estimated, though considerable heterogeneity in definitions limits their usefulness.
Parsimonious and robust multivariate prediction equations were estimated for glycated hemoglobin A and weight change, separately for insulin-naive and insulin-experienced patients. Using these in economic simulation modeling in T2DM can improve realism and flexibility in modeling insulin rescue medication.
2型糖尿病（T2DM）是一种慢性进展性疾病，新治疗干预措施的成本效益必须在较长时间范围内确定。鉴于药物的耐久性有限，关于下游救援药物的假设可能会影响结果。特别是对于胰岛素，其治疗效果和不良事件已知取决于患者特征，这对于涉及建模的卫生经济评估可能存在问题。
估计简约的多变量治疗效果和低血糖事件风险方程，用于基于模型的成本效益分析中参数化胰岛素救援治疗。
在PubMed以及已发表的综述和荟萃分析中确定了T2DM中胰岛素使用的临床证据。提取研究和患者特征、治疗效果及不良事件发生率，并使用多变量回归分析这些数据来估计简约的治疗效果和低血糖事件风险方程。
确定了来自91项研究的171个可用研究组的数据，主要针对预混胰岛素和基础胰岛素类型。分别为初治胰岛素患者和有胰岛素使用经验的患者估计了糖化血红蛋白降低和体重变化的多变量预测方程。两种结果的拟合优度（R）总体良好，范围为0.44至0.84。还估计了有症状、夜间和严重低血糖事件的多变量预测方程，尽管定义上存在相当大的异质性限制了它们的实用性。
分别为初治胰岛素患者和有胰岛素使用经验的患者估计了糖化血红蛋白和体重变化的简约且稳健的多变量预测方程。在T2DM的经济模拟模型中使用这些方程可以提高胰岛素救援药物建模的真实性和灵活性。
