METHODS: The simulated survival data method based on Weibull distribution was used to simulate and generate the survival data with different cure rates, censored rates, and cure rate differences. The Cox-TEL method was used for analysis of the generated simulation data, and its performance was evaluated by calculating its type Ⅰ error and power.
RESULTS: Almost all the type Ⅰ error of the hazard ratios (HRs) obtained by the Cox-TEL method under different conditions were slightly greater than 0.05, and this method showed a good test power for estimating the HRs for data with a large sample size and a large difference in proportions (DPs). For the data of cured patients, the type Ⅰ error of the DPs obtained by the Cox-TEL method was well around 0.05, and its test power was robust in most of the scenarios.
CONCLUSIONS: The Cox-TEL method is effective for analyzing data of uncured patients and obtaining reliable HRs for most of the survival data with a sample size, a low censored rates, and a large difference in cure rates. The method is capable of accurately estimating the DPs regardless of the sample size, censored rates, or the cure rates.
方法:采用基于威布尔分布的模拟生存数据方法,模拟生成不同治愈率的生存数据,审查率,和治愈率差异。Cox-TEL方法用于分析生成的仿真数据,并通过计算其Ⅰ型误差和功率来评估其性能。
结果:Cox-TEL方法在不同条件下得到的风险比(HRs)的Ⅰ类误差几乎都略大于0.05,该方法对样本量大、比例差异(DPs)大的数据估计HRs具有良好的检验能力。对于治愈患者的数据,通过Cox-TEL方法获得的DPs的Ⅰ型误差在0.05左右,其测试能力在大多数情况下都是稳健的。
结论:Cox-TEL方法可有效分析未治愈患者的数据,并在样本量的情况下获得大多数生存数据的可靠HR,低审查率,治愈率差异很大。无论样本大小如何,该方法都能够准确估计DP,审查率,或治愈率。