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Latent class modelling of the association between socioeconomic background and breast cancer survival status at 5 years incorporating stage of disease
  1. Amy Downing1,
  2. Wendy J Harrison2,3,
  3. Robert M West2,4,
  4. David Forman1,5,
  5. Mark S Gilthorpe2
  1. 1Cancer Epidemiology Group, Centre for Epidemiology and Biostatistics, University of Leeds, Leeds, UK
  2. 2Division of Biostatistics, Centre for Epidemiology and Biostatistics, University of Leeds, Leeds, UK
  3. 3School of Healthcare, University of Leeds, Leeds, UK
  4. 4Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
  5. 5Northern and Yorkshire Cancer Registry and Information Service, St James's Institute of Oncology, Leeds, UK
  1. Correspondence to Prof Mark S Gilthorpe, Level 8, Worsley Building, Clarendon Way, Leeds, LS2 9JT, UK; m.s.gilthorpe{at}leeds.ac.uk

Abstract

Background Stage of disease and socioeconomic background (SEB) are often used to ‘explain’ differences in breast cancer outcomes. There are challenges for all types of analysis (eg, survival analysis, logistic regression), including missing data, measurement error and the ‘reversal paradox’. This study investigates the association between SEB and survival status within 5 years of breast cancer diagnosis using (1) logistic regression with and without adjustment for stage and (2) logistic latent class analysis (LCA) excluding stage as a covariate but with and without stage as a latent class predictor.

Methods Women diagnosed with invasive breast cancer between 1998 and 2000 in one UK region were identified (n=11 781). Multilevel logistic regression was performed using standard regression and LCA. Models included SEB (2001 Townsend Index), age and stage (‘missing’ stage (8.0%) modelled as a separate category). The association of SEB with stage was also assessed.

Results Using standard regression, there was a substantial association between SEB and death within 5 years, with and without adjustment for stage. Using LCA, patients were assigned to a large good prognosis group and a small poor prognosis group. The association between SEB and survival was substantive in both classes for the model without stage, but only in the larger class for the model with stage. Increasing deprivation was associated with more advanced stage at diagnosis.

Conclusions LCA categorises patients into prognostic groups according to patient and tumour characteristics, providing an alternative strategy to the usual statistical adjustment for stage.

  • Breast cancer
  • survival
  • socioeconomic background
  • stage of disease
  • latent class analysis
  • cancer: survival
  • methodology me
  • social-economic

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Footnotes

  • Funding This work was supported by Cancer Research UK (AD), HEFCE (WJH, RMW, MSG) and the NHS (DF).

  • Competing interests None.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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