How much do tumor stage and treatment explain socioeconomic inequalities in breast cancer survival? Applying causal mediation analysis to population-based data.


Li, R; Daniel, R; Rachet, B; (2016) How much do tumor stage and treatment explain socioeconomic inequalities in breast cancer survival? Applying causal mediation analysis to population-based data. European journal of epidemiology, 31 (6). pp. 603-11. ISSN 0393-2990 DOI: 10.1007/s10654-016-0155-5

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Abstract

: Substantial socioeconomic inequalities in breast cancer survival persist in England, possibly due to more advanced cancer at diagnosis and differential access to treatment. We aim to disentangle the contributions of differential stage at diagnosis and differential treatment to the socioeconomic inequalities in cancer survival. Information on 36,793 women diagnosed with breast cancer during 2000-2007 was routinely collected by an English population-based cancer registry. Deprivation was determined for each patient according to her area of residence at the time of diagnosis. A parametric implementation of the mediation formula using Monte Carlo simulation was used to estimate the proportion of the effect of deprivation on survival mediated by stage and by treatment. One-third (35 % [23-48 %]) of the higher mortality experienced by most deprived patients at 6 months after diagnosis, and one tenth (14 % [-3 to 31 %]) at 5 years, was mediated by adverse stage distribution. We initially found no evidence of mediation via differential surgical treatment. However, sensitivity analyses testing some of our study limitations showed in particular that up to thirty per cent of the higher mortality in most deprived patients could be mediated by differential surgical treatment. This study illustrates the importance of using causal inference methods with routine medical data and the need for testing key assumptions through sensitivity analyses. Our results suggest that, although effort for earlier diagnosis is important, this would reduce the cancer survival inequalities only by a third. Because of data limitations, role of differential surgical treatment may have been under-estimated.<br/>

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology
Faculty of Epidemiology and Population Health > Dept of Medical Statistics
Research Centre: Cancer Survival Group
Centre for Global Non-Communicable Diseases (NCDs)
Centre for Statistical Methodology
PubMed ID: 27165500
URI: http://researchonline.lshtm.ac.uk/id/eprint/2549375

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