title: Estimation and prediction in a multi-state model for breast cancer.
abstract: An important aim in clinical studies in oncology is to study how treatment and prognostic factors influence the course of disease of a patient. Typically in these trials, besides overall survival, also other endpoints such as locoregional recurrence or distant metastasis are of interest. Most commonly in these situations, Cox regression models are applied for each of these endpoints separately or to composite endpoints such as disease-free survival. These approaches however fail to give insight into what happens to a patient after a first event. We re-analyzed data of 2795 patients from a breast cancer trial (EORTC 10854) by applying a multi-state model, with local recurrence, distant metastasis, and both local recurrence and distant metastasis as transient states and death as absorbing state. We used an approach where the clock is reset on entry of a new state. The influence of prognostic factors on each of the transition rates is studied, as well as the influence of the time at which intermediate events occur. The estimated transition rates between the states in the model are used to obtain predictions for patients with a given history. Formulas are developed and illustrated for these prediction probabilities for the clock reset approach.
authors.affiliation: Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, The Netherlands. h.putter@lumc.nl
authors.forename: Hein
authors.initials: H
authors.lastname: Putter
authors.forename: Jos
authors.initials: J
authors.lastname: van der Hage
authors.forename: Geertruida H
authors.initials: GH
authors.lastname: de Bock
authors.forename: Rachid
authors.initials: R
authors.lastname: Elgalta
authors.forename: Cornelis J H
authors.initials: CJ
authors.lastname: van de Velde
mesh_terms: D001699:Biometry / Q000379:methods; D001943:Breast Neoplasms / Q000175:diagnosis / Q000401:mortality*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D009364:Neoplasm Recurrence, Local / Q000175:diagnosis / Q000401:mortality*; D015995:Prevalence; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012680:Sensitivity and Specificity; D016019:Survival Analysis