Social inequalities in cancer survival in Belgium: A population-based cohort study
Menée à partir des données du registre belge des cancers portant sur 109 591 patients atteints d'un cancer diagnostiqué sur la période 2006-2013, cette étude de cohorte analyse les disparités socioéconomiques et démographiques dans la survie
Background: Socioeconomic status is an important factor in cancer survival, however results are heterogeneous and linked to characteristics of the study population and health care system. This population-based cohort study evaluates the association between individual-level socioeconomic and -demographic factors and cancer survival for the first time in Belgium. Methods: From the Belgian Cancer Registry, we identified 109 591 patients diagnosed between 2006-2013 with one of eight common cancer types. Information on treatment, socioeconomic parameters and vital status were retrieved from multiple data sources and linked using a unique personal identification number. The outcome was 5-year observed survival. Associations between survival and socioeconomic and -demographic factors, were assessed using multivariable Cox proportional-hazard regression models. Results: Lower income, unemployment and living alone were all associated with worse cancer survival. These associations were most pronounced for certain lifestyle-related cancer types (e.g. head and neck cancers) and those with good to moderate prognosis (e.g. colorectal and female breast cancer). Conclusions: These results indicate that, despite a comprehensive and nationwide health insurance program where equity in rights and access to healthcare are pursued, socioeconomic status is associated with disparities in cancer survival in Belgium. Impact: This population-based study with individual-level socioeconomic information of over 100.000 cancer patients identifies patient groups that may be at highest risk for socioeconomic disparities in cancer survival. Reasons behind the observed disparities are multiple and complex and should be further examined. Health policy interventions should consider the observed deprivation gap to plan targeted actions.