Improved curve fits to summary survival data: application to economic evaluation of health technologies.
Improved curve fits to summary survival data: application to economic evaluation of health technologies.
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DOI：
10.1186/1471-2288-11-139
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发表时间：
2011-10-10
影响因子：
4
通讯作者：
Henley W
中科院分区：
文献类型：
--
作者：
Hoyle MW;Henley W
平均成本和质量调整生命年对卫生技术的成本效益至关重要。它们通常根据时间和事件曲线计算，如总生存期和无进展生存期。理想情况下，估计应该通过拟合适当的参数模型来获得个体患者数据。然而，独立研究人员通常无法获得这些数据。相反，通常是通过回归或最小二乘法将曲线拟合到Kaplan-Meier图中。这里，描述了一种更准确的生存曲线拟合总结生存数据的方法。首先，根据处于危险中的患者数量（或其他公开信息）和Kaplan-Meier图估计潜在的个体患者数据。然后，生存曲线可以通过最大似然估计或其他适用于估计的个体患者数据的合适方法进行拟合。通过模拟数千个试验中患者的生存情况，将所提出方法的准确性与回归和最小二乘方法以及使用实际个体患者数据的准确性进行了比较。舒尼替尼与干扰素- α治疗转移性肾细胞癌的成本效益，最近在英国NICE计算，在几种方法下重新评估，包括拟议的方法。仿真结果表明，该方法在实际场景下的拟合精度高于传统方法。此外，在估计平均生存时间时，所提出的方法与分析完整的潜在个体患者数据所获得的结果具有相似的偏差和均方误差。所提出的方法还可以自然地对曲线拟合中的不确定性进行估计，这是传统方法无法实现的。舒尼替尼与干扰素- α的成本效益在使用该方法时发生了实质性的改变。当只有总结生存数据可用时，推荐使用该方法进行成本-效果分析。提供了一个易于使用的Excel电子表格来实现该方法。
Mean costs and quality-adjusted-life-years are central to the cost-effectiveness of health technologies. They are often calculated from time to event curves such as for overall survival and progression-free survival. Ideally, estimates should be obtained from fitting an appropriate parametric model to individual patient data. However, such data are usually not available to independent researchers. Instead, it is common to fit curves to summary Kaplan-Meier graphs, either by regression or by least squares. Here, a more accurate method of fitting survival curves to summary survival data is described. First, the underlying individual patient data are estimated from the numbers of patients at risk (or other published information) and from the Kaplan-Meier graph. The survival curve can then be fit by maximum likelihood estimation or other suitable approach applied to the estimated individual patient data. The accuracy of the proposed method was compared against that of the regression and least squares methods and the use of the actual individual patient data by simulating the survival of patients in many thousands of trials. The cost-effectiveness of sunitinib versus interferon-alpha for metastatic renal cell carcinoma, as recently calculated for NICE in the UK, is reassessed under several methods, including the proposed method. Simulation shows that the proposed method gives more accurate curve fits than the traditional methods under realistic scenarios. Furthermore, the proposed method achieves similar bias and mean square error when estimating the mean survival time to that achieved by analysis of the complete underlying individual patient data. The proposed method also naturally yields estimates of the uncertainty in curve fits, which are not available using the traditional methods. The cost-effectiveness of sunitinib versus interferon-alpha is substantially altered when the proposed method is used. The method is recommended for cost-effectiveness analysis when only summary survival data are available. An easy-to-use Excel spreadsheet to implement the method is provided.
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影响因子：
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作者：
Tierney JF;Stewart LA;Ghersi D;Burdett S;Sydes MR
通讯作者：
Sydes MR
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作者：
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作者：
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