Are socio-economic inequalities in breast cancer survival explained by peri-diagnostic factors?

Autor: Krishnan Bhaskaran, Laura M. Woods, Michel P Coleman, Bernard Rachet, Melanie Morris
Jazyk: angličtina
Rok vydání: 2021
Předmět:
0301 basic medicine
Cancer Research
Databases
Factual
medicine.medical_treatment
Health Status
Comorbidity
0302 clinical medicine
Surgical oncology
Poverty Areas
Medicine
Registries
RC254-282
Primary health care
Aged
80 and over
Peri-diagnostic period
Hazard ratio
Smoking
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Middle Aged
Early diagnosis
Oncology
England
030220 oncology & carcinogenesis
Female
Research Article
Adult
Adolescent
Alcohol Drinking
Breast surgery
Socioeconomic factors
Time-to-Treatment
03 medical and health sciences
Young Adult
Breast cancer
Genetics
Humans
Survival analysis
Aged
Proportional Hazards Models
Retrospective Studies
Health Services Needs and Demand
business.industry
Retrospective cohort study
medicine.disease
Cancer registry
030104 developmental biology
Breast neoplasms
business
Demography
Zdroj: BMC Cancer, Vol 21, Iss 1, Pp 1-15 (2021)
BMC Cancer
ISSN: 1471-2407
Popis: Background Patients living in more deprived localities have lower cancer survival in England, but the role of individual health status at diagnosis and the utilisation of primary health care in explaining these differentials has not been widely considered. We set out to evaluate whether pre-existing individual health status at diagnosis and primary care consultation history (peri-diagnostic factors) could explain socio-economic differentials in survival amongst women diagnosed with breast cancer. Methods We conducted a retrospective cohort study of women aged 15–99 years diagnosed in England using linked routine data. Ecologically-derived measures of income deprivation were combined with individually-linked data from the English National Cancer Registry, Clinical Practice Research Datalink (CPRD) and Hospital Episodes Statistics (HES) databases. Smoking status, alcohol consumption, BMI, comorbidity, and consultation histories were derived for all patients. Time to breast surgery was derived for women diagnosed after 2005. We estimated net survival and modelled the excess hazard ratio of breast cancer death using flexible parametric models. We accounted for missing data using multiple imputation. Results Net survival was lower amongst more deprived women, with a single unit increase in deprivation quintile inferring a 4.4% (95% CI 1.4–8.8) increase in excess mortality. Peri-diagnostic co-variables varied by deprivation but did not explain the differentials in multivariable analyses. Conclusions These data show that socio-economic inequalities in survival cannot be explained by consultation history or by pre-existing individual health status, as measured in primary care. Differentials in the effectiveness of treatment, beyond those measuring the inclusion of breast surgery and the timing of surgery, should be considered as part of the wider effort to reduce inequalities in premature mortality.
Databáze: OpenAIRE
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