Cure model analysis in cancer: an application to data from the Children's Cancer Group.

@article{Sposto2002CureMA,
  title={Cure model analysis in cancer: an application to data from the Children's Cancer Group.},
  author={Richard Sposto},
  journal={Statistics in medicine},
  year={2002},
  volume={21 2},
  pages={293-312}
}
The most commonly used statistical methods for evaluating treatment or prognostic effects on cancer outcome--the logrank test and Cox regression analysis--rely on the proportional hazards (PH) assumption in that they have maximal power in this circumstance. Implicitly, these methods emphasize covariate effects on failure times rather than their effects on the proportion of long-term survivors ('cures'), which may be of equal or primary interest. In paediatric cancer, treatment has progressed… CONTINUE READING

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