Estimating medical costs from incomplete follow-up data
Estimating medical costs from incomplete follow-up data
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作者：
Lin, DY;Feuer, EJ;Wax, Y
由于某些研究对象的生存时间被删减，其后续成本未知，因此对治疗患有特定疾病的患者的平均总成本的估计往往变得复杂。从所有研究对象或仅从未经审查的病例中观察到的成本的原始样本平均值可能存在严重偏差，并且标准生存分析技术不适用。为了尽量减少审查引起的偏见，我们感兴趣的整个时间段分割成许多小的间隔和估计平均总成本通过kaplan meier估计量之和为死在每个区间的概率乘以总成本的样本均值与观察到的死亡时间间隔或kaplan meier估计量之和为活着的每个区间的概率乘以一个适当的条件的时间间隔内平均成本的估计量存活到间隔开始时；如果滤波只发生在区间的边界处，所得估计量是一致的。此外，估计量是渐近正态的，方差易于估计。大量的数值研究表明，渐近逼近足以用于实际应用，并且即使在区间内部可能发生审查时，所提出的估计量的偏差也很小。一项卵巢癌研究提供。
Estimation of the average total cost for treating patients with a particular disease is often complicated by the fact that the survival times are censored on some study subjects and their subsequent costs are unknown. The naive sample average of the observed costs from all study subjects or from the uncensored cases only can be severely biased, and the standard survival analysis techniques are not applicable. To minimize the bias induced by censoring, we partition the entire time period of interest into a number of small intervals and estimate the average total cost either by the sum of the Kaplan-Meier estimator for the probability of dying in each interval multiplied by the sample mean of the total costs from the observed deaths in that interval or by the sum of the Kaplan-Meier estimator for the probability of being alive at the start of each interval multiplied by an appropriate estimator for the average cost over the interval conditional on surviving to the start of the interval; The resultant estimators are consistent if censoring occurs solely at the boundaries of the intervals. In addition, the estimators are asymptotically normal with easily estimated variances. Extensive numerical studies show that the asymptotic approximations are adequate for practical use and the biases of the proposed estimators are small even when censoring may occur in the interiors of the intervals. An ovarian cancer study is provided.