A single-index threshold Cox proportional hazard model for identifying a treatment-sensitive subset based on multiple biomarkers

作者：He, Ye; Lin, Huazhen^*; Tu, Dongsheng

来源：Statistics in Medicine, 2018, 37(23): 3267-3279.

DOI：10.1002/sim.7837

• penalized likelihood
• predictive biomarker
• single-index threshold Cox proportional hazard model
• smoothing
• variable selection

In this paper, we introduce a single-index threshold Cox proportional hazard model to select and combine biomarkers to identify patients who may be sensitive to a specific treatment. A penalized smoothed partial likelihood is proposed to estimate the parameters in the model. A simple, efficient, and unified algorithm is presented to maximize this likelihood function. The estimators based on this likelihood function are shown to be consistent and asymptotically normal. Under mild conditions, the proposed estimators also achieve the oracle property. The proposed approach is evaluated through simulation analyses and application to the analysis of data from two clinical trials, one involving patients with locally advanced or metastatic pancreatic cancer and one involving patients with resectable lung cancer.

• 出版日期2018-10-15
• 单位西南财经大学