Abstract

BackgroundDescribing the relationship between socioeconomic inequalities and cancer survival is important but methodologically challenging. We propose guidelines for addressing these challenges and illustrate their implementation on French population-based data.MethodsWe analyzed 17 cancers. Socioeconomic deprivation was measured by an ecological measure, the European Deprivation Index (EDI). The Excess Mortality Hazard (EMH), ie, the mortality hazard among cancer patients after accounting for other causes of death, was modeled using a flexible parametric model, allowing for nonlinear and/or time-dependent association between the EDI and the EMH. The model included a cluster-specific random effect to deal with the hierarchical structure of the data.ResultsWe reported the conventional age-standardized net survival (ASNS) and described the changes of the EMH over the time since diagnosis at different levels of deprivation. We illustrated nonlinear and/or time-dependent associations between the EDI and the EMH by plotting the excess hazard ratio according to EDI values at different times after diagnosis. The median excess hazard ratio quantified the general contextual effect. Lip–oral cavity–pharynx cancer in men showed the widest deprivation gap, with 5-year ASNS at 41% and 29% for deprivation quintiles 1 and 5, respectively, and we found a nonlinear association between the EDI and the EMH. The EDI accounted for a substantial part of the general contextual effect on the EMH. The association between the EDI and the EMH was time dependent in stomach and pancreas cancers in men and in cervix cancer.ConclusionThe methodological guidelines proved efficient in describing the way socioeconomic inequalities influence cancer survival. Their use would allow comparisons between different health care systems.

Highlights

  • Assessing the relationship between socioeconomic deprivation and cancer survival is important as socioeconomic differences in cancer survival are still observed even in countries with universal health care coverages.1–6 Describing this relationship at the population level calls for population-based cancer registry data, but the way of performing the analysis is challenging

  • We used a strategy able to deal with specific methodological requirements: the use of a relevant measure of deprivation and a relevant mortality indicator estimated using a flexible regression model able to deal with nonlinear and time-dependent associations

  • We applied this approach to 17 solid tumors diagnosed in a specific area of France and followed up over 10 years after diagnosis to investigate the change over time of the excess mortality by age and socioeconomic level

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Summary

Background

Describing the relationship between socioeconomic inequalities and cancer survival is important but methodologically challenging. The Excess Mortality Hazard (EMH), ie, the mortality hazard among cancer patients after accounting for other causes of death, was modeled using a flexible parametric model, allowing for nonlinear and/or time-dependent association between the EDI and the EMH. We illustrated nonlinear and/or time-dependent associations between the EDI and the EMH by plotting the excess hazard ratio according to EDI values at different times after diagnosis. Conclusion: The methodological guidelines proved efficient in describing the way socioeconomic inequalities influence cancer survival. Their use would allow comparisons between different health care systems.

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Materials and methods
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