ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2021
[Subgroup identification based on accelerated failure time model combined with adaptive elastic net].
Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- [A simulation study of the reliability and accuracy of Cox-TEL method for estimating hazard ratio and difference in proportions for long-term survival data containing cured patients].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- [Comparison of prediction ability of two extended Cox models in nonlinear survival data analysis].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2023Article
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6 authors.
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Abstract
objectiveTo solve the problem of identifying subgroup in a randomized clinical trial with respect to survival time, we present a strategy based on accelerated failure time model to identify the subgroup with an enhanced treatment effect.
objectiveWe fitted and compared univariate accelerated failure time (AFT) models and penalized AFT models regularized by adaptive elastic net to identify the candidate covariates. Based on these covariates, we utilized change-point algorithm to classify the patient subgroups. A two-stage adaptive design was adopted to verify the treatment effect in certain subgroups. Simulations were conducted across different scenarios to evaluate the performance of the models.
objectiveAs the correlation between covariates differed, the power of the models with an adaptive design was stable. In the two-stage adaptive design, the power of the models was the highest when the two significance levels (α
objectiveThe correlation between the covariates does not affect the performance of univariate AFT models and penalized AFT models. (0.035, 0.015) can be used as a reference for the significance level of an adaptive design. For small differences in the treatment effect between the responder and the non-responder, the penalized AFT model including the main effect of covariate (Penalized, Eq_in) outperforms the univariate AFT model excluding the main effect of covariate (Univariate, Eq_ex). Univariate, Eq_ex performs better when the covariate number to sample size ratio is less than 1, but is outperformed by Penalized, Eq_in when the ratio is above 1. The parameter distribution of survival time has a greater impact on the univariate models but a smaller impact on the penalized models.
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