title: Validation of death prediction after breast cancer relapses using joint models.
abstract: BACKGROUND
  Cancer relapses may be useful to predict the risk of death. To take into account relapse information, the Landmark approach is popular. As an alternative, we propose the joint frailty model for a recurrent event and a terminal event to derive dynamic predictions of the risk of death.
  
  
  METHODS
  The proposed prediction settings can account for relapse history or not. In this work, predictions developed on a French hospital series of patients with breast cancer are externally validated on UK and Netherlands registry data. The performances in terms of prediction error and calibration are compared to those from a Landmark Cox model.
  
  
  RESULTS
  The error of prediction was reduced when relapse information was taken into account. The prediction was well-calibrated, although it was developed and validated on very different populations. Joint modelling and Landmark approaches had similar performances.
  
  
  CONCLUSIONS
  When predicting the risk of death, accounting for relapses led to better prediction performance. Joint modelling appeared to be suitable for such prediction. Performance was similar to the landmark Cox model, while directly quantifying the correlation between relapses and death.
authors.affiliation: Biostatistic unit, INSERM U897, ISPED, Université de Bordeaux, 146 rue Léo Saignat, Bordeaux Cedex, 33076, France. audrey.mauguen@isped.u-bordeaux2.fr.|Cancer Research UK Cancer Survival Group, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT, London, UK. audrey.mauguen@isped.u-bordeaux2.fr.
authors.forename: Audrey
authors.initials: A
authors.lastname: Mauguen
authors.affiliation: Cancer Research UK Cancer Survival Group, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT, London, UK. Bernard.Rachet@lshtm.ac.uk.
authors.forename: Bernard
authors.initials: B
authors.lastname: Rachet
authors.affiliation: Clinical epidemiology and research, Institut Bergonié, 229 Cours de l'Argonne, Bordeaux, 33000, France. Simone.Mathoulin-Pelissier@isped.u-bordeaux2.fr.|INSERM CIC-EC7, ISPED, Université de Bordeaux, 146 rue Léo Saignat, Bordeaux Cedex, 33076, France. Simone.Mathoulin-Pelissier@isped.u-bordeaux2.fr.
authors.forename: Simone
authors.initials: S
authors.lastname: Mathoulin-Pélissier
authors.affiliation: West Midlands Cancer Intelligence Unit, 5, St Philip's Place, Birmingham, B3 2PW, UK. g.lawrence@nhs.net.
authors.forename: Gill M
authors.initials: GM
authors.lastname: Lawrence
authors.affiliation: Comprehensive Cancer Centre The Netherlands (IKNL), Godebaldkwartier 419 ingang Janssoenborch, Utrecht, 3511, The Netherlands. S.Siesling@iknl.nl.
authors.forename: Sabine
authors.initials: S
authors.lastname: Siesling
authors.affiliation: Clinical epidemiology and research, Institut Bergonié, 229 Cours de l'Argonne, Bordeaux, 33000, France. Macgrogan@bergonie.org.
authors.forename: Gaëtan
authors.initials: G
authors.lastname: MacGrogan
authors.affiliation: Biostatistic unit, INSERM U897, ISPED, Université de Bordeaux, 146 rue Léo Saignat, Bordeaux Cedex, 33076, France. Alexandre.Laurent@isped.u-bordeaux2.fr.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Laurent
authors.affiliation: Biostatistic unit, INSERM U897, ISPED, Université de Bordeaux, 146 rue Léo Saignat, Bordeaux Cedex, 33076, France. Virginie.Rondeau@isped.u-bordeaux2.fr.
authors.forename: Virginie
authors.initials: V
authors.lastname: Rondeau
mesh_terms: D000328:Adult; D001943:Breast Neoplasms / Q000401:mortality / Q000473:pathology*; D005260:Female; D006801:Humans; D008875:Middle Aged; D008962:Models, Theoretical; D009364:Neoplasm Recurrence, Local; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods* / Q000706:statistics & numerical data*; D012307:Risk Factors; D016019:Survival Analysis; D015996:Survival Rate