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Cure models with adaptive activation for modeling cancer survival.

Qi JiangSanjib Basu
Published in: Statistical methods in medical research (2024)
We propose a class of cure rate models motivated by analysis of colon cancer and triple-negative breast cancer survival data. This class is indexed by an adaptive activation parameter and a function. We establish that the class is stochastically ordered in the activation parameter and also establish two identifiability results for this class. The first- and last-activation models are members of this class whereas many cure rate models proposed in the literature are also part of this class. We illustrate that while first- and last-activation models may perform poorly under model misspecifications, the proposed model with adaptive activation provides appropriate inference in these cases. We apply the proposed approach to assess treatment-sex interaction on cure rate in a colon cancer study and to assess role of tumor heterogeneity and ethnic disparity in breast cancer.
Keyphrases
  • systematic review
  • single cell
  • electronic health record
  • machine learning
  • deep learning
  • big data
  • lymph node metastasis