Title : Population-based retrospective, observational cohort study on disparities in breast cancer treatment, and survival outcomes among immigrant women in Ontario, Canada.
Abstract:
Breast cancer is the most common cancer among Canadian women and a leading cause of cancer-related deaths. In Ontario, where incidence and mortality mirror national trends, immigrant women represent a large portion of the population. However, their experiences with breast cancer remain understudied. Evidence shows clear gaps in screening and incidence rates within immigrant groups, while findings on stage at diagnosis and diagnostic timeliness are less extensive and mixed, and treatment and survival are least developed.This study aims to compare breast cancer treatment and survival rates between immigrants and long-term residents in the province of Ontario, Canada. We will also explore the underlying factors contributing to any observed disparities, including social determinants of health, clinical variables, and other factors.We hypothesize that immigrant women in Ontario experience differences in treatment, and survival outcomes compared with long-term residents. These inequalities may arise from a combination of socioeconomic factors, and varying access to healthcare resources.We will conduct a population-based retrospective cohort study using linked ICES datasets. For instance, we will include the Ontario Cancer Registry (OCR) dataset for cancer diagnoses and outcomes and the Immigration, Refugees and Citizenship Canada (IRCC) Permanent Resident Database for identifying immigrant status, region of birth, and time in Canada. Additional ICES-linked administrative health databases will capture screening participation, health services use, treatments, and mortality. Subgroup analyses will examine variations by world region of birth, immigration class and duration of residence.We will compare baseline characteristics using Chi-Square and ANOVA tests. These will include an exhaustive set of demographic, clinical, and contextual variables such as age, sex, neighbourhood conditions, income quintile, stage at diagnosis, treatment type, treatment wait times, tumour characteristics, and primary care attachment, among others. Treatment differences will be assessed using appropriate regression models for binary, and continuous outcomes. Survival will be analyzed using cumulative incidence functions (CIFs), Gray-tests and multivariable Fine–Gray subdistribution hazard models.By studying immigrant women through each step of the later stages of the continuum and situating outcomes within social context, this study will identify where disparities are largest and which system and primary care interventions could yield the greatest equity gains.
