Cécilia-Joseph Elsa, Auvert Bertran, Broët Philippe, Moreau Thierry
Inserm U1018, CESP Centre for Research in Epidemiology and Population Health, Villejuif, France; Faculté de Médecine, University Paris-Sud, Le Kremlin-Bicêtre, France.
Biom J. 2015 May;57(3):371-83. doi: 10.1002/bimj.201400046. Epub 2015 Jan 16.
In randomized clinical trials where the times to event of two treatment groups are compared under a proportional hazards assumption, it has been established that omitting prognostic factors from the model entails an underestimation of the hazards ratio. Heterogeneity due to unobserved covariates in cancer patient populations is a concern since genomic investigations have revealed molecular and clinical heterogeneity in these populations. In HIV prevention trials, heterogeneity is unavoidable and has been shown to decrease the treatment effect over time. This article assesses the influence of trial duration on the bias of the estimated hazards ratio resulting from omitting covariates from the Cox analysis. The true model is defined by including an unobserved random frailty term in the individual hazard that reflects the omitted covariate. Three frailty distributions are investigated: gamma, log-normal, and binary, and the asymptotic bias of the hazards ratio estimator is calculated. We show that the attenuation of the treatment effect resulting from unobserved heterogeneity strongly increases with trial duration, especially for continuous frailties that are likely to reflect omitted covariates, as they are often encountered in practice. The possibility of interpreting the long-term decrease in treatment effects as a bias induced by heterogeneity and trial duration is illustrated by a trial in oncology where adjuvant chemotherapy in stage 1B NSCLC was investigated.
在比例风险假设下比较两个治疗组事件发生时间的随机临床试验中，已经证实，在模型中忽略预后因素会导致风险比被低估。癌症患者群体中因未观察到的协变量导致的异质性是一个问题，因为基因组研究已经揭示了这些群体中的分子和临床异质性。在艾滋病预防试验中，异质性不可避免，并且已证明会随着时间的推移降低治疗效果。本文评估了试验持续时间对因在Cox分析中忽略协变量而导致的估计风险比偏差的影响。真实模型通过在个体风险中纳入一个反映被忽略协变量的未观察到的随机脆弱项来定义。研究了三种脆弱分布：伽马分布、对数正态分布和二元分布，并计算了风险比估计量的渐近偏差。我们表明，未观察到的异质性导致的治疗效果衰减会随着试验持续时间大幅增加，特别是对于可能反映被忽略协变量的连续脆弱性情况，因为它们在实际中经常遇到。在一项肿瘤学试验中，对IB期非小细胞肺癌辅助化疗进行了研究，这说明了将治疗效果的长期下降解释为由异质性和试验持续时间引起的偏差的可能性。
