Latent class modelling of the association between socioeconomic background and breast cancer survival status at 5 years incorporating stage of disease

• Published in: Journal of epidemiology and community health (1979) Vol. 64; no. 9; pp. 772 - 776
• Main Authors: Downing, Amy, Harrison, Wendy J, West, Robert M, Forman, David, Gilthorpe, Mark S
• Format: Journal Article
• Language: English
• Published: London BMJ Publishing Group Ltd 01.09.2010; BMJ Publishing Group; BMJ Publishing Group LTD
• Subjects: Adult; Age; Bias; Biological and medical sciences; Breast cancer; Breast Neoplasms - economics; Breast Neoplasms - mortality; Breast Neoplasms - pathology; cancer: survival; Confounding Factors (Epidemiology); Disease models; Epidemiology; Female; General aspects; Gynecology. Andrology. Obstetrics; Health outcomes; Humans; latent class analysis; Logistic Models; Mammary gland diseases; Medical prognosis; Medical sciences; methodology me; Middle Aged; Miscellaneous; Modeling; Models, Statistical; Multilevel Analysis; Multilevel models; Neoplasia; Neoplasm Staging; Odds Ratio; Poverty; Prognosis; Public health. Hygiene; Public health. Hygiene-occupational medicine; Regression analysis; Research report; social-economic; socioeconomic background; Socioeconomic Factors; Socioeconomics; stage of disease; Studies; Survival; Survival analysis; Survival Rate; Time Factors; Treatment Outcome; Tumors; United Kingdom - epidemiology; Womens health; Breast disease; Statistical analysis; Socioeconomic status; Disease; Socioeconomic study; Breast cancer; Malignant tumor; Latent class analysis; Modeling; Socioeconomics; Survival; Medicine; Mammary gland diseases; Association; Economic aspect; Mammary gland; Antecedent; Social aspect; Public health; Cancer
• ISSN: 0143-005X; 1470-2738
• DOI: 10.1136/jech.2008.085852

BackgroundStage 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.MethodsWomen 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.ResultsUsing 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.ConclusionsLCA categorises patients into prognostic groups according to patient and tumour characteristics, providing an alternative strategy to the usual statistical adjustment for stage.