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BMC Medical Research Methodology
Published in: BMC Medical Research Methodology 1/2019

Open Access 01-12-2019 | Research article

Comparison of model-building strategies for excess hazard regression models in the context of cancer epidemiology

Authors: Camille Maringe, Aurélien Belot, Francisco Javier Rubio, Bernard Rachet

Published in: BMC Medical Research Methodology | Issue 1/2019

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Abstract

Background

Large and complex population-based cancer data are becoming broadly available, thanks to purposeful linkage between cancer registry data and health electronic records. Aiming at understanding the explanatory power of factors on cancer survival, the modelling and selection of variables need to be understood and exploited properly for improving model-based estimates of cancer survival.

Method

We assess the performances of well-known model selection strategies developed by Royston and Sauerbrei and Wynant and Abrahamowicz that we adapt to the relative survival data setting and to test for interaction terms.

Results

We apply these to all male patients diagnosed with lung cancer in England in 2012 (N = 15,688), and followed-up until 31/12/2015. We model the effects of age at diagnosis, tumour stage, deprivation, comorbidity and emergency presentation, as well as interactions between age and all of the above. Given the size of the dataset, all model selection strategies favoured virtually the same model, except for a non-linear effect of age at diagnosis selected by the backward-based selection strategies (versus a linear effect selected otherwise).

Conclusion

The results from extensive simulations evaluating varying model complexity and sample sizes provide guidelines on a model selection strategy in the context of excess hazard modelling.
Appendix
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Metadata
Title
Comparison of model-building strategies for excess hazard regression models in the context of cancer epidemiology
Authors
Camille Maringe
Aurélien Belot
Francisco Javier Rubio
Bernard Rachet
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2019
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/s12874-019-0830-9

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