title: Cure models for estimating hospital-based breast cancer survival.
abstract: OBJECTIVE
  Research on cancer survival is enriched by development and application of innovative analytical approaches in relation to standard methods. The aim of the present paper is to document the utility of a mixture model to estimate the cure fraction and compare it with other approaches.
  
  
  METHODS
  The data were for 1,107 patients with locally advanced breast cancer, who completed the neo-adjuvant treatment protocol during 1990-99 at the Cancer Institute (WIA), Chennai, India. Tumour stage, post-operative pathological node (PN) and tumour residue (TR) status were studied. Event free survival probability was estimated using the Kaplan-Meier method. Cure models under proportional and non-proportional hazard assumptions following log normal distribution for survival time were used to estimate both the cure fraction and the survival function for the uncured.
  
  
  RESULTS
  Event free survival at 5 and 10 years were 64.2% and 52.6% respectively and cure fraction was 47.5% for all cases together. Follow up ranged between 0-15 years and survival probabilities showed minimal changes after 7 years of follow up. TR and PN emerged as independent prognostic factors using Cox and proportional hazard (PH) cure models. Proportionality condition was violated when tumour stage was considered and it was statistically significant only under PH and not under non PH cure models. However, TR and PN continued to be independent prognostic factors after adjusting for tumour stage using the non PH cure model. A consistent ordering of cure fractions with respect to factors of PN and TR was forthcoming across tumour stages using PH and non PH cure models, but perceptible differences in survival were observed between the two.
  
  
  CONCLUSIONS
  If PH conditions are violated, analysis using a non PH model is advocated and mixture cure models are useful in estimating the cure fraction and constructing survival curves for non-cures.
authors.affiliation: Department of Epidemiology, Biostatistics and Cancer Registry, Cancer Institute (WIA), India.
authors.forename: Ranganathan
authors.initials: R
authors.lastname: Rama
authors.forename: Rajaraman
authors.initials: R
authors.lastname: Swaminathan
authors.forename: Perumal
authors.initials: P
authors.lastname: Venkatesan
mesh_terms: D001943:Breast Neoplasms / Q000401:mortality* / Q000628:therapy; D005260:Female; D006761:Hospitals; D006801:Humans; D007194:India; D008207:Lymphatic Metastasis; D015233:Models, Statistical; D009367:Neoplasm Staging; D011379:Prognosis; D015996:Survival Rate