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Disparities in Breast Cancer Survival

Disparities in breast cancer treatment persist in the America based on socioeconomic status despite the Medicaid and Medicare systems. The disparities primarily depend on the race and the socioeconomic status (SES) of the patients, which has resulted in many questions about whether patients from minor races and of low socioeconomic status have access to the right treatment. A study by Jeffrey and his friends aimed at studying the logical contributors to the SES disparities in breast cancer survival. The research presented three matches that focused on the disparities experienced by low SES black, low SES non-Hispanic white, and low SES Hispanic white women. The three groups gave a better understanding of the reasons behind survival disparities in breast cancer in America. The study used tapered multivariate matching to determine the disparities in the three groups in Medicare.

Methods

The data used in the study was obtained from the SEER-Medicare database for patients with breast cancer from 1992 to 2010. Males were excluded from the data as well as female patients less than 66 years and diagnosed before 1992 (Silber et al., 2018). Patient characteristics were identified through the SEER race and ethnicity algorithm. The socioeconomic status was identified and defined by three measures. To be identified as a low SES required eligibility of both Medicare and Medicaid at the diagnosis time and be residing in a neighborhood with more than 20% occupants below poverty level, and over 20% with no high school diplomas. The control groups were not supposed to be dual-eligible and reside in neighborhoods with below 20% federal poverty inhabitants and more than 20% high school completion (Silber et al., 2018).

Statistical tests and outcomes

A test was carried out after matching to ensure balance. Standard deviation was calculated for every variable. The balance between the covariates was assessed using Fisher’s exact test and the Wilcoxon rank-sum test binary and continuous covariate, respectively. The achieved balance was then matched with the expected balance. P-values and standard errors for paired differences in Kaplan-Meier survival probabilities were obtained using the bootstrap method applied to matched pairs (Silber et al., 2018). Preventive care utilization measures were analyzed for LSES populations, and their matched NLSES controls to determine whether the patients had a usual source of primary care six to eighteen months before diagnosis with breast cancer (Silber et al., 2018).

Results

The study identified 723 Hispanic women, 1,824 black women, and 1,890 non-Hispanic white women with breast cancer between 1992 and 2010. The control group had 60,300 NLSES non-Hispanic white women (Silber et al., 2018). As demonstrated in Table 1, the characteristics of the SES were variant between the groups. For instance, despite the ethnicity and race, NLSES patients were from regions that had double the median income of the LSES patients. None of the control groups was Medicare and Medicaid eligible and had a median income of $63,000, with 90.2% high school diplomas and 6.4% below federal poverty (Silber et al., 2018). In contrast, the LSES non-Hispanic whites were Medicare-Medicaid eligible, 64.3% with high school completion, 24.1% below federal poverty, and a median income of $28,000. LSES Hispanic neighborhood had 52.3% high school completion, 28.0% below federal poverty level, and a median income of $27,005. LSES blacks had a median income of $27,768, 62.0% high school completion, and 26.0% below the federal poverty level (Silber et al., 2018).

Matches qualities

After the matching, the standard deviation of the covariates in the control group demographic and presentation matches met the balance criteria. All the standard differences in the treatment match (169 differences) met the balance criteria. Only two-variable had significant p-values after complete matching. Therefore, the total imbalanced covariates were lower than expected with a random trial of the total covariates.

Treatment and Presentation Differences by SES

The LSES patients had worse presentation factors compared to the NLSES non-Hispanic white patients. Similar presentation patterns were observed across the three groups except that it was smallest for Hispanics and the largest for blacks. NLSES patients had superior treatment than the LSES groups even after controlling the differences. The LSES groups also had less chemotherapy and radiation than the NLSES group. LSES blacks received inappropriate treatment and less surgery compared to the NLSES control group despite the same presentation characteristic.

Survival Results

The survival difference was big and significant between the two groups. NLSES group had a survival median of 126 months while LSES had 84 months matched for demography, corresponding to five-year survival rates of 74.9% versus 62.1%, respectively (Silber et al., 2018). Therefore, the treatment differences did not explain the observed survival disparity between the three groups and the control cohort. The survival curves for the treatment- and presentation-matched NLSES groups are very similar.

NLSES group had a survival median of 120 months, while LSES had 73 months, matching the five-year survival estimate of 57.1% for the black and 73.0% for the NLSES cohort (p < 0.0001) (Silber et al., 2018). The difference in survival between the two cohorts matched, implying that the treatment difference between the two groups contributed to the overall survival disparity experience by the low SES blacks.

NLSES group had a survival median of 145 months while LSES had 106 months matching five-year survival estimate of 69.2% for LSES compared to 78.9% for NLSES (Silber et al., 2018). Despite the apparent trend toward diverging survival three years after diagnosis, the difference in survival between the two groups matched from treatment and presentation.

Differences in survival

Besides the LSES groups verse the NLSES non-Hispanic white analysis, matches were carried out between each LSES group and their corresponding NLSES group. Stratified Cox models were then used to examine differences in survival. In general, the hazard ratio was higher in LSES than NLSES, implying that socioeconomic status was a significant determinant of the differences in breast cancer survival besides race and ethnicity.

Preventive Care Utilization by SES

After determining the Preventive Care Utilization by SES, there was a significant difference in utilization between NLSES controls and LSES populations, particularly in screening mammography. The LSES groups were had low chances of having had a primary care visit during the analysis period, with NLSES rates always above 89% and LSES rates below 84% despite the match (Silber et al., 2018).

Discussion

On ethical and racial grounds, low SES patients have low chances of surviving breast cancer. Comparing NLSES and LSES, the LSES groups had the worst health than the NLSES group. The three LSES had higher stage IV cancer rates than the control group. LSES black had 8.0% versus 4.0% for NLSES, LSES non-Hispanic whites had 6.4% verse 3.5%, while Hispanic had 5.5% verse 2.6% for the control group (Silber et al., 2018). The LSES groups also had higher comorbidities rates than the NSLES control group. About the diabetes history, LSES had relatively higher rates than the NLSES group.

In treatment and presentation survival disparities, the NLSES had high chances than the LSES groups. On average, the total survival months for the three LSES groups were below 100 months, while the NLSES group had higher than 100 months (Silber et al., 2018). Presentation factors explained the gap between the two groups. However, the black group had the worst and the greatest total disparity among the three groups.

Limitations

The study used women from only 17 SEER sites aged 66 years, while the median age for breast cancer is 61 years. This age bracket excluded young people diagnosed with aggressive tumors. Therefore, the generation might be inaccurate. The study also considered only patients in the Medicare system. Excluding patients without Medicare insurance might underestimate the extent of the SES survival disparity.

Conclusion

Socioeconomic status disparities were present and significant among older patients in Medicare. The primary cause of the disparities are presentation characteristics during diagnosis and not treatment disparities, although they also contribute. Although medical insurance is necessary for optimal breast cancer treatment services, it is not adequate to minimize the disparities associated with socioeconomic status, despite ethnicity or race.

References

Silber, J. H., Rosenbaum, P. R., Ross, R. N., Reiter, J. G., Niknam, B. A., Hill, A. S., … & Fox, K. R. (2018). Disparities in breast cancer survival by socioeconomic status despite Medicare and Medicaid insurance. The Milbank Quarterly96(4), 706-754.

 

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