Bayesian Spatial Analysis for the Evaluation of Breast Cancer Detection Methods

Spatial variation and disparity in female breast cancer relative survival in the United States

BACKGROUND

Breast cancer is the most common cancer among women in the United States. However, data on spatial disparities in survival for breast cancer are limited in the country. This study estimated 5-year relative survival (RS) of female breast cancer and examined the spatial variations across the contiguous United States.

METHODS

Women newly diagnosed with breast cancer in 2003-2010 in the United States were identified from the National Cancer Database and followed up through 2016. The crude 5-year RS at the county level was estimated and adjusted for patients' key sociodemographic and clinical factors. To account for spatial effects, the RS estimates were smoothed using the Bayesian spatial survival model. A local spatial autocorrelation analysis with the Getis-Ord Gi* statistics was applied to identify geographic clusters of low or high RS.

RESULTS

Clusters of low RS were identified in more than 15 states covering 671 counties, mostly in the southeast and southwest regions, including Georgia, Alabama, Mississippi, Louisiana, Arkansas, Oklahoma, and Texas. Approximately 30% of these clusters can be explained by patients' characteristics: Race, insurance, and stage at diagnosis appeared to be the major attributable factors.

CONCLUSIONS

Significant spatial disparity in female breast cancer survival was found, with low RS clusters identified in Georgia, Alabama, Mississippi, Louisiana, Arkansas, Oklahoma, and Texas. Policies and interventions that focus on serving Black women, improvements in insurance coverage, and early detection in these areas could potentially mitigate the spatial disparities.

Understanding the effects of socioeconomic status along the breast cancer continuum in Australian women: a systematic review of evidence

Background

Globally, the provision of equitable outcomes for women with breast cancer is a priority for governments. However, there is growing evidence that a socioeconomic status (SES) gradient exists in outcomes across the breast cancer continuum – namely incidence, diagnosis, treatment, survival and mortality. This systematic review describes this evidence and, because of the importance of place in defining SES, findings are limited to the Australian experience.

Methods

An on-line search of PubMed and the Web of Science identified 44 studies published since 1995 which examined the influence of SES along the continuum. The critique of studies included the study design, the types and scales of SES variable measured, and the results in terms of direction and significance of the relationships found. To aid in the interpretation of results, the findings were discussed in the context of a systems dynamic feedback diagram.

Results

We found 67 findings which reported 107 relationships between SES within outcomes along the continuum. Results suggest no differences in the participation in screening by SES. Higher incidence was reported in women with higher SES whereas a negative association was reported between SES and diagnosis. Associations with treatment choice were specific to the treatment choice undertaken. Some evidence was found towards greater survival for women with higher SES, however, the evidence for a SES relationship with mortality was less conclusive.

Conclusions

In a universal health system such as that in Australia, evidence of an SES gradient exists, however, the strength and direction of this relationship varies along the continuum. This is a complex relationship and the heterogeneity in study design, the SES indicator selected and its representative scale further complicates our understanding of its influence. More complex multilevel studies are needed to better understand these relationships, the interactions between predictors and to reduce biases introduced by methodological issues.

Are international differences in breast cancer survival between Australia and the UK present amongst both screen-detected women and non-screen-detected women? survival estimates for women diagnosed in West Midlands and New South Wales 1997-2006

We examined survival in screened-detected and non-screen-detected women diagnosed in the West Midlands (UK) and New South Wales (Australia) in order to evaluate whether international differences in survival are related to early diagnosis, or to other factors relating to the healthcare women receive. Data for women aged 50 - 65 years who had been eligible for screening from 50 years were examined. Data for 5,628 women in West Midlands and 6,396 women in New South Wales were linked to screening service records (mean age at diagnosis 53.7 years). We estimated net survival and modelled the excess hazard ratio of breast cancer death by screening status. Survival was lower for women in the West Midlands than in New South Wales (5-year net survival 90.9% [95% CI 89.9%-91.7%] compared with 93.4% [95% CI 92.6%-94.1%], respectively). The difference was greater between the two populations of non-screen-detected women (4.9%) compared to between screen-detected women, (1.8% after adjustment for lead-time and over-diagnosis). The adjusted excess hazard ratio of breast cancer death for West Midlands compared with New South Wales was greater in the non-screen-detected group (EHR 2.00, 95% CI 1.70 - 2.31) but not significantly different to that for women whose cancer had been screen-detected (EHR 1.72, 95% CI 0.87 - 2.56). In this study more than one in three breast cancer deaths in the West Midlands would have been avoided if survival had been the same as in New South Wales. The possibility that women in the UK receive poorer treatment is an important potential explanation which should be examined with care.

Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location

An increasing number of studies have identified spatial differences in breast cancer survival. However little is known about whether the structure and dynamics of this spatial inequality are consistent across a region. This study aims to evaluate the spatially varying nature of predictors of spatial inequality in relative survival for women diagnosed with breast cancer across Queensland, Australia. All Queensland women aged less than 90 years diagnosed with invasive breast cancer from 1997 to 2007 and followed up to the end of 2008 were extracted from linked Queensland Cancer Registry and BreastScreen Queensland data. Bayesian relative survival models were fitted using various model structures (a spatial regression model, a varying coefficient model and a finite mixture of regressions model) to evaluate the relative excess risk of breast cancer, with the use of Markov chain Monte Carlo computation. The spatially varying coefficient models revealed that some covariate effects may not be constant across the geographic regions of the study. The overall spatial patterns showed lower survival among women living in more remote areas, and higher survival among the urbanised south-east corner. Notwithstanding this, the spatial survival pattern for younger women contrasted with that for older women as well as single women. This complex spatial interplay may be indicative of different factors impacting on survival patterns for these women.