Rural disadvantage in breast cancer health-care service use and outcomes: quantifying the effects of individual risk factors and health service risk factors
Bibliographic record
Abstract
Background: Breast cancer is the most prevalent cancer worldwide. Fortunately, survival rates are high. However, inequalities in survival rates have been observed in sub-populations. Existing evidence indicates that women with breast cancer living in rural areas have a lower survival rate than their urban counterparts. However, the reason behind the rural disadvantage in breast cancer survival remains unclear. Health service provision in rural and urban areas differ across countries, therefore results based on observations from other countries may not be used for the basis of health policy and decision making in the Australian setting. While a significant proportion of Australia consists of rural areas, existing studies on breast cancer health-care service use and outcomes are largely based on an urban sample. The thesis provides an epidemiological investigation to address the lack of research on rural and urban differences in risk factors that can affect breast cancer health-care service use and outcomes in Australia. Methods: This thesis is comprised of systematic review studies and secondary analysis research studies. Systematic reviews studies were conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Secondary analysis studies were conducted drawing data from the Australian Longitudinal Study on Women’s Health (ALSWH). Analysis was based on longitudinal data with a 14-year follow-up with 13,715 women aged 45 to 50 years in 1996. Linked data from the cancer registries were used in order to obtain information on the cancer characteristics of the participants. Area of residence was defined in accordance with the Accessibility Remoteness Index of Australia Plus. Results: Findings from a systematic review study conducted as part of this thesis revealed that, internationally, the rural populations were less likely to have mammography breast screening. It was found that all studies were cross-sectional, and most of the studies were based in the United States or Canada, with only one Australian study that compared mammography in 1995. From this, it was evident that research based on more recent data was needed to compare the rural and urban populations on long-term engagement in breast screening behaviour in Australia. Using the ALSWH data, breast screening patterns over time were compared between women living in rural and urban Australia. Somewhat surprisingly, despite poorer access to mammography services, women residing in rural areas had similar mammography screening rates to their urban counterparts. Another systematic review study in this thesis revealed that people residing in rural areas were more likely to be diagnosed with more advanced breast cancer. As existing Australian studies used cancer registry data, factors that may act as a possible confound in the relationship between rurality of residence and the late stage of diagnosis were not available for statistical analysis. From this, it was evident that research was needed to compare rural and urban differences in stage of diagnosis, taking into consideration other individual characteristic factors. In a data linkage study that incorporated information on cancer characteristics from cancer registries, it was found that advanced breast cancer was diagnosed in 36% of women residing in urban areas and in 40% of women residing in rural areas. Obesity was found to be the strongest risk factor of an advanced stage at diagnosis, after adjusting for individual and socio-demographic variables including survey year, menopausal status, and country of birth, education, marital status, and rurality of residence. Lastly, using the ALSWH data, this thesis showed that physical and mental health-related quality of life (HRQOL) did not differ between women living in rural and urban samples, indicating no rural disadvantage in HRQOL after a breast cancer diagnosis. Conclusions: The thesis forms the first Australian epidemiological examination of rural and urban differences in area-level and individual-level factors that can affect breast cancer health-care service use and outcomes. The finding that there were no rural disadvantages in mammography rates implies that the breast screening service provision to rural areas in Australia has been successful. Finally, the thesis showed that despite common belief, rural women were not disadvantaged in terms of social support received, and there was no rural disadvantage in quality of life in breast cancer survivors living in rural areas. The work is significant because it contributes to an understanding of why rural women have worse breast cancer outcomes, and can thus help direct planning and allocation of breast cancer resources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".