Else Helene Ibfelt1, Susanne Oksbjerg Dalton2, Claus Høgdall3, Carsten Lindberg Fagö-Olsen4, Marianne Steding-Jessen2, Merete Osler5, Christoffer Johansen2, Kirsten Frederiksen2, Susanne K Kjær6. 1. Danish Cancer Society Research Center, Strandboulevarden 49, DK-2100 Copenhagen, Denmark; Research Centre for Prevention and Health, Glostrup University Hospital, Nordre Ringvej 57, DK-2600 Glostrup, Denmark. Electronic address: else.helene.ibfelt@regionh.dk. 2. Danish Cancer Society Research Center, Strandboulevarden 49, DK-2100 Copenhagen, Denmark. 3. The Gynecologic Clinic, The Juliane Marie Centre, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark. 4. Department of Obstetrics and Gynecology, Hillerød Hospital, Copenhagen University Hospital, Dyrehavevej 29, DK-3400 Hillerød, Denmark. 5. Research Centre for Prevention and Health, Glostrup University Hospital, Nordre Ringvej 57, DK-2600 Glostrup, Denmark. 6. Danish Cancer Society Research Center, Strandboulevarden 49, DK-2100 Copenhagen, Denmark; The Gynecologic Clinic, The Juliane Marie Centre, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark.
Abstract
AIMS: In order to reduce social inequality in cancer survival, knowledge is needed about where in the cancer trajectory disparities occur, and how social and health-related aspects may interact. We aimed to determine whether socioeconomic factors are related to cancer diagnosis stage, and whether socioeconomic disparities in survival after ovarian cancer can be explained by socioeconomic differences in cancer stage, comorbidity, treatment or lifestyle factors. METHODS: In the Danish Gynaecological Cancer Database we identified 2873 cases of ovarian cancer diagnosed between 2005 and 2010. From this data we retrieved information on prognostic factors, treatment information and lifestyle factors. Age, vital status, comorbidity, education, income and cohabitation status were ascertained from nationwide administrative registers. Associations were analyzed with logistic regression and Cox regression models. RESULTS: Educational level was weakly associated with cancer stage. Short education, lower income and living without a partner were related to poorer survival after ovarian cancer. Among women with early cancer stage, HR (95% CI) for death was 1.75 (1.20-2.54) in shorter compared to longer educated women. After adjustment for comorbid conditions, cancer stage, tumour histology, operation status and lifestyle factors, socioeconomic differences in survival persisted. CONCLUSIONS: Socioeconomic disparities in survival after ovarian cancer were to some extent, but not fully explained by differences in important prognostic factors, suggesting further investigations into this problem, however implying that socially less advantaged ovarian cancer patients should receive attention during cancer treatment and rehabilitation.
AIMS: In order to reduce social inequality in cancer survival, knowledge is needed about where in the cancer trajectory disparities occur, and how social and health-related aspects may interact. We aimed to determine whether socioeconomic factors are related to cancer diagnosis stage, and whether socioeconomic disparities in survival after ovarian cancer can be explained by socioeconomic differences in cancer stage, comorbidity, treatment or lifestyle factors. METHODS: In the Danish Gynaecological Cancer Database we identified 2873 cases of ovarian cancer diagnosed between 2005 and 2010. From this data we retrieved information on prognostic factors, treatment information and lifestyle factors. Age, vital status, comorbidity, education, income and cohabitation status were ascertained from nationwide administrative registers. Associations were analyzed with logistic regression and Cox regression models. RESULTS: Educational level was weakly associated with cancer stage. Short education, lower income and living without a partner were related to poorer survival after ovarian cancer. Among women with early cancer stage, HR (95% CI) for death was 1.75 (1.20-2.54) in shorter compared to longer educated women. After adjustment for comorbid conditions, cancer stage, tumour histology, operation status and lifestyle factors, socioeconomic differences in survival persisted. CONCLUSIONS: Socioeconomic disparities in survival after ovarian cancer were to some extent, but not fully explained by differences in important prognostic factors, suggesting further investigations into this problem, however implying that socially less advantaged ovarian cancerpatients should receive attention during cancer treatment and rehabilitation.
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