Objective To explore the applicable conditions of the Cox-TEL(Cox PH-Taylor expansion adjustment for long-term survival data)method for analysis of survival data that contain cured patients.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.Conclusion 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.

Objective To explore the applicable conditions of the Cox-TEL(Cox PH-Taylor expansion adjustment for long-term survival data)method for analysis of survival data that contain cured patients.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.Conclusion 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.