@article{Andersson:231772,
      recid = {231772},
      author = {Andersson, Therese M.-L. and Lambert, Paul C.},
      title = {Fitting and modeling cure in population-based cancer  studies within the framework of flexible parametric  survival models},
      journal = {Stata Journal},
      address = {2012},
      number = {199-2016-2789},
      pages = {18},
      year = {2012},
      abstract = {When the mortality among a cancer patient group returns to  the same level as in the general population, that is, when  the patients no longer experience excess mortality, the  patients still alive are considered “statistically cured”.  Cure models can be used to estimate the cure proportion as  well as the survival function of the “uncured”. One  limitation of parametric cure models is that the functional  form of the survival of the uncured has to be specified. It  can sometimes be hard to find a survival function flexible  enough to fit the observed data, for example, when there is  high excess hazard within a few months from diagnosis,  which is common among older age groups. This has led to the  exclusion of older age groups in population-based cancer  studies using cure models. Here we use flexible parametric  survival models that incorporate cure as a special case to  estimate the cure proportion and the survival of the  uncured. Flexible parametric survival models use splines to  model the underlying hazard function; therefore, no  parametric distribution has to be specified. We have  updated the stpm2 command for flexible parametric models to  enable cure modeling.},
      url = {http://ageconsearch.umn.edu/record/231772},
      doi = {https://doi.org/10.22004/ag.econ.231772},
}