Validation of death prediction after breast cancer relapses using joint models

BMC Medical Research Methodology

Virginie Rondeau³  Alexandre Laurent³  Gaëtan MacGrogan⁴  Sabine Siesling⁶  Gill M Lawrence¹  Simone Mathoulin-Pélissier²  Bernard Rachet⁵  Audrey Mauguen⁵ 

[1] West Midlands Cancer Intelligence Unit, 5, St Philip’s Place, Birmingham B3 2PW, UK;INSERM CIC-EC7, ISPED, Université de Bordeaux, 146 rue Léo Saignat, Bordeaux Cedex 33076, France;Biostatistic unit, INSERM U897, ISPED, Université de Bordeaux, 146 rue Léo Saignat, Bordeaux Cedex 33076, France;Clinical epidemiology and research, Institut Bergonié, 229 Cours de l’Argonne, Bordeaux 33000, France;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;Comprehensive Cancer Centre The Netherlands (IKNL), Godebaldkwartier 419 ingang Janssoenborch, Utrecht 3511, The Netherlands

关键词: Survival;    Relapse history;    Prediction;    Landmark;    Joint frailty model;    Breast cancer;   

Others  :  1177564
DOI  :  10.1186/s12874-015-0018-x

 received in 2014-07-25, accepted in 2015-03-17,  发布年份 2015

【 摘 要 】

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.

【 授权许可】

   
2015 Mauguen et al.; licensee BioMed Central.

【 图 表 】

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