Maringe, C;
Belot, A;
Rubio, FJ;
Rachet, B;
(2019)
Comparison of model-building strategies for excess hazard regression models in the context of cancer epidemiology.
BMC Medical Research Methodology
, 19
(1)
p. 210.
10.1186/s12874-019-0830-9.
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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.
| Type: | Article |
|---|---|
| Title: | Comparison of model-building strategies for excess hazard regression models in the context of cancer epidemiology |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1186/s12874-019-0830-9 |
| Publisher version: | http://dx.doi.org/10.1016/j.scs.2020.102023 |
| Language: | English |
| Additional information: | © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
| Keywords: | Excess hazard models, Interactions, Non-linearity, Non-proportionality, Variable selection, Age Factors, Aged, Aged, 80 and over, Algorithms, England, Humans, Linear Models, Lung Neoplasms, Male, Middle Aged, Neoplasm Staging, Nonlinear Dynamics, Proportional Hazards Models, Survival Rate |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10126576 |
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