The identification of valid surrogate markers of disease or disease progression has the potential to decrease the length and costs of future studies. Most available methods that assess the value of a surrogate marker ignore the fact that surrogates are often measured with error. Failing to adjust for measurement error can erroneously identify a useful surrogate marker as not useful or vice versa. We investigate and propose robust methods to correct for the effect of measurement error when evaluating a surrogate marker using multiple estimators developed for parametric and nonparametric estimates of the proportion of treatment effect explained by the surrogate marker. In addition, we quantify the attenuation bias induced by measurement error and develop inference procedures to allow for variance and confidence interval estimation. Through a simulation study, we show that our proposed estimators correct for measurement error in the surrogate marker and that our inference procedures perform well in finite samples. We illustrate these methods by examining a potential surrogate marker that is measured with error, hemoglobin A1c, using data from the Diabetes Prevention Program clinical trial.

中文翻译：

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在评估替代标记时校正测量误差的稳健方法

鉴定疾病或疾病进展的有效替代标志物有可能减少未来研究的时间和成本。大多数评估替代标记值的可用方法都忽略了替代标记经常被测量错误的事实。未能针对测量误差进行调整可能会错误地将有用的替代标记识别为无用，反之亦然。我们研究并提出了稳健的方法来纠正测量误差的影响，该方法使用为替代标记解释的治疗效果比例的参数和非参数估计开发的多个估计器来评估替代标记。此外，我们量化了由测量误差引起的衰减偏差，并开发了推理程序以允许方差和置信区间估计。通过模拟研究，我们表明我们提出的估计器可以纠正替代标记中的测量误差，并且我们的推理程序在有限样本中表现良好。我们通过使用来自糖尿病预防计划临床试验的数据检查一个潜在的替代标记来说明这些方法，该标记被错误地测量，血红蛋白 A1c。