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Abstract
This paper reviews the effects of effects of breast cancer at a later stage among women living in the United States of America and its relation to factors such as ethnicity, race, geographic location, and availability of insurance, access to medical test facilities, and course of treatments, lifestyle and socio-economic factors and so on. A special focus has been laid on the racial and ethnic discrimination among women affected with breast cancer in regards to the surgical treatments being offered in health facilities in the United States of America. Many authors have proven the link between incidence of cancer, ethnicity, and race. Numerous studies have also shown that women from certain races are predisposed to certain type of cancers due to their genetic make-up. Disparities in treatments and survival rates also occur due to race and income inequalities. The research conducted in this paper seeks to test and analyze, in detail, the relationships that do/do not exist between the variables. The research was specifically conducted to understand the differences in treatment and outcomes, in late stage breast cancer patients among minority populations in the United States and the comparison to non-Hispanic White women.
Discussion
Breast cancer has been known as a vice among women in the world today, where its spread has been viewed to be quite uncontrollable among the medical practitioners and more so the cancer specialists. This research paper has placed its focus on the spread and effects of breast cancer at a later stage among women living in the United States of America, with the study carried out in a period of 8 years spanning from the year 2004 to the year 2012. This research paper goes ahead to investigate if there has been biasness in the treatment of breast cancer among women on the basis of their background and race. Given the fact that the women victims of breast cancer at a later stage have to undergo surgical treatment in a bid to control if not treat the vice due to its spread, the research paper gathered a control population of victims treated to find out if there existed any biasness among the medical practitioners in surgical treatment of the victims on the basis of ethnic background and race. The study having been carried out in 18 cities in the United States, 77 percent of the selected sample were above the age of 50 years whereas over 55 percent of the women were diagnosed with cancer after 2008. Due to the aim of this research paper, the sample size was divided into Hispanics and Non- Hispanics and further subdivided into the Non- Hispanic White (NH) and the Non- Hispanic (NH) Black.
The results indicated that out of the women of Non- Hispanic sample size, 62.3 percent of the Non- Hispanic White received surgical care as opposed to 57.2 percent of the Non- Hispanic Black that received surgical treatment in cancer treatment facilities in the 18 cities of the United States analyzed in this research study. The results indicated that majority of those who did not have insurance (58.8%) did not receive radiation therapy whereas 43.1% of those who were ‘uninsured’, received surgical treatment, compared to 61.7% of those who received surgical treatment from the ‘insured’ group. The results concluded by indicating that there was a high mortality rate among the victims of breast cancer that were of Non- Hispanic as compared to the Hispanic, and further, a high mortality rate among the Non- Hispanic Black as compared to the Non- Hispanic White. This was enough to conclude that there still exists high level of discrimination in the health centers on the basis of ethnic background and race.
In the literature review, Li et al. found racial and ethnic disparities exists in the management of breast cancer from diagnosis to treatment and survival (Li, Malone, & Daling, 2003). Race and ethnicity influence the treatment of breast cancer significantly. According to this study, diagnosis and treatment differ greatly among women of different ethnicities and races. Through an evaluation of different sub-groups of the major races, Li et al. shows a distinct correlation between breast cancer treatment and race/ethnicity. For example, Mexican and Puerto Rican patients with breast cancer were more likely to receive inappropriate treatment and care in comparison to non-Hispanic whites (Li, Malone, & Daling, 2003). However, Maskarinec et al. argue that Japanese, Korean, Vietnamese and Chinese women are more likely to receive appropriate care when compared Puerto Rican and Mexican women (Li, Malone, & Daling, 2003) (Maskarinec, Sen, Koga, & Conroy, 2011). While this is the case, David supports the report arguing that minority groups receive considerably lower and inappropriate care in the treatment of breast cancer. This is no different from the results indicated from this research study where it indicated that Hispanic women diagnosed with cancer at a later stage received better surgical treatment than the Non- Hispanic women with a significant level of difference in terms of the percentage analyzed in the result findings.
The importance of the findings indicated in this research study is so as to ensure that sanity is incorporated in the health care systems of the United States in a bid to eradicate the vices of racism and discrimination in general. Healthcare is one of the most fancied systems of operation among the population of the United States as every government is capped with the responsibility of ensuring that every citizen of the United States is guaranteed quality healthcare. On the issue of insurance, the government should ensure that it is made affordable to every citizen of the United States and that all employers provide medical insurance to their employees and families. This is so in the sense that healthcare is very expensive, and more so the treatment of cancer without insurance. Diagnosis tends to be quite expensive and unaffordable to the middle and low income families in the United States. It is evident that Hispanics have been granted quality education as compared to their Non- Hispanics counterparts in the United States, therefore they are earning higher than the Non- Hispanics making it hard for the Non- Hispanics to afford quality healthcare and insurance. The government is therefore put on the spotlight to ensure that they level up provision of medicare and that Obamacare is made a reality to all.
Summary of Results
The study was conducted in the 18 SEER regions of the United States, as described earlier. The period of study was 8 years - from 2004 to 2012 and involved women with late stage breast cancer. Demographically, the sample was divided based on many parameters. These were chosen and based on the core of the four research questions. The first Research question pertained to the receipt of treatment. The sub set questions further defined them as receipt of surgical treatment or radiotherapy. The second question, the research focused on, was on the differences in treatment due to the type of insurance – again differentiated by type of treatment and incidence of surgical treatment or radiotherapy. The third question that the research addressed was the association of race and ethnicity and insurance type. This was further divided into the type of treatment given. The fourth question was based on the disparities in the 5-year survival rates by race and ethnicity, in the SEER sample from 18 cities. In terms of the demographics of the sample selected, the majority of the women were married or never married or single/widowed. More than 77% of these women were above 50 years of age. In terms of the timing of diagnosis, majority (53.6%) of the cases were diagnosed in 2008 and after. The group was also divided by race and ethnicity, with the majority, being Non- Hispanic (NH) White followed by NH Black. The sample also was divided on the basis of insurance type and treatments given.
The findings on this research study were analyzed for statistical significance using the Chi Square Test and the fourth question was subjected to Cox Regression to test the relationship between variables. The first research question was to check if there is a link between race/ethnicity and the recommended treatment. The question was further divided based on surgical therapy or radio therapy.
Is there an association between race/ethnicity and receipt of surgical treatment among women diagnosed with late-stage breast cancer?
Is there an association between race/ethnicity and receipt of radiation treatment among women diagnosed with late-stage breast cancer?
The Chi-square test for independence (Pearson’s chi-square test) was run. The analysis showed that majority of NH White women (62.3%) received surgical treatment. This percentage was higher than the percentage for NH Black (57.2%) that received surgical treatment. Findings demonstrated evidence that race/ethnicity was significantly associated with surgical treatment.
Similarly, the test for radiation therapy revealed that 43.7% of the NH Whites received radiation treatment while 44.2% of the Hispanics received radiation. So there was a fundamental and statistically significant association, between racial/ethnic background and radiation therapy. So, in relation to Questions 1, 1a, 1b, the analysis shows a direct correlation and the Null Hypothesis can be rejected and we should accept the Alternative Hypothesis.
Now, we look at the results of the second question and its subsets. The second question pertained to the association between treatment and insurance type, further divided in to surgical treatment or radiation treatment. The study shows, that women who had an insurance cover were more likely to receive surgical treatment than those who did not. For instance, 43.1% of those who were ‘uninsured’, received surgical treatment, compared to 61.7% of those who received surgical treatment from the ‘insured’ group. This again proves that the receipt of surgical treatment was statistically significant based on insurance type. As far as the radiation therapy goes, the test shows that majority of those who did not have insurance (58.8%) did not receive radiation therapy. Here, too we reject the Null Hypothesis and accept the Alternative Hypothesis.
The fourth research question, related to the difference in survival rates and its relationship with race/ethnicity of women. Cox Regression was used to help get the values of the covariate variables. The two variables that were measured were status (occurrence of death) and time (survival time in months). Here again, there was a significant relationship between the variables and predictors. The results show that the occurrence of death for NH Black group was very high compared to NH Whites. NH Blacks, therefore, are identified as the highest risk group in cancer related deaths. They not only have a low survival rate, but also show an enhanced propensity to short survival time, after onset and diagnosis. In this case too, we reject the Null Hypothesis and accept the Alternative Hypothesis.
The foregoing results show that there is a great deal of association between race and ethnicity to the type of treatments, insurance type to type of treatments and also the wide disparity between races in terms of survival rate and time.
It is really evident from the study that the results concur with the opinion of various authors, in regard to the relationship between race or ethnicity and breast cancer. It is in agreement with Hershman et al., Bourjolly and Maskarinec et al., that racial inequality remains in the health care system and is evident in the diagnosis and treatment of women with breast cancer. The data in the study shows that NH Black group in the population is a high risk group compared to White women. There is a high likelihood of NH Black women to be diagnosed with late stage cancer.
The results of the study in some ways contradict the views of other authors like Kim et al., Maskarinec et al. and Yu, who argue that increasing awareness of breast cancer and the availability of facilities have seen a decrease in late stage cases of breast cancer. Increased efficiency in care has elevated the fight against cancer . The research shows us that, though the efficiency in care has improved the fight against cancer, the minorities are still not receiving timely diagnosis and treatment. Minority groups remain lower in the overall receipt of the right treatment and are forced to endure low survival rates compared to White women.
The study also concurs with views of Li et al., who also found racial and ethnic disparities in the management of breast cancer from diagnosis to treatment and survival . Li et al. specifically mention Mexican and Puerto Rican patients, who were more likely to receive inappropriate treatment and care in comparison to non-Hispanic whites . The contradiction to this view is that Japanese, Korean and Chinese women, though a minority in the United States, do receive proper treatment regimens for breast cancer.
Many of the researchers have expressed similar views in terms of the relationship between ethnicity and the treatment for breast cancer. Like the research shows, the incidence of late stage breast cancer among ethnic minorities stems from various factors. Primarily, it depends on the socio economic ladder. Like a number of studies have shown, the ethnic minorities also constitute, what can be defined as, the low income group in the U.S. These low income groups live on daily wages and are not capable of paying for huge insurance premiums. This is one of the fundamental reasons why low income earners, do not do monitoring and early diagnoses and do not receive treatment in time . With larger families and high cost of care, they are forced to take unwanted risks in the diagnosis of breast cancer. It is also seen, that many of the minorities are not highly educated. This is another cause for increased risk of late stage cancer in these groups.
We see that there are many factors affecting the incidence and course of late stage breast cancer in minority women groups. Many of these are racial and ethnic groups are underserved in many aspects, in our society. Low insurance coverage and social status is a direct cause that is linked to higher prevalence and incidence of late stage cancer. The living environment also plays a key role. Most of the racial and ethnic minorities are forced to live in lower class neighborhoods. Studies have shown that living in such environments and the exposure to many toxins makes these groups more susceptible to cancer. In addition, the lack of awareness, non availability of screening facilities and behavioral issues like smoking, alcoholism, drugs and obesity; contribute to the incidence of late stage breast cancer. Research also shows that ethnic minorities are more likely to suffer from late-stage diseases that could have been treated, with early diagnosis.
Limitations of the Study
The NCI SEER database is a good source of patient data that can be used in cancer research. The data helps in researching many types of cancers, second malignancies and also the differences that exist in patient demographics, all over the country. The database allows users to study many trends and analyze critical methods in the diagnosis, treatment and future course of many cancers. The data can be used to define Null and Alternative hypotheses on a wide range of parameters. The database, like any other, does come with its own set of limitations (Yu, 2009).
Coding limitations: The study had many demographic and clinical variables. Since SEER data does not have one variable called “race/ethnicity”, this variable was created from existing SEER variables of race recode variable (Black, White, Other) and Origin NHIA recode (Non-Spanish-Hispanic-Latino and Spanish-Hispanic-Latino). Under the race recode variable, other race represents both Asian/Pacific Islander and American Indian/Alaska Native. For this category, 328 (0.6%) AI/AN, and 3331 (6.5%) Asian/PI was represented in the study. Treatments of breast cancer available in the current data set were surgery and radiation therapy. This is a big limitation in the data. SEER only provides data on these two types of treatment individually. Insurance type was also re-coded to include three categories: insured, Medicaid, and Uninsured. More than half (51.7%) of the sample was classified as insured while 12.9% were grouped as having Medicaid. This bias will probably affect some of the results. Other factors that may add variability include characteristics such as year of diagnosis, age at diagnosis, and marital status. Description of the race and ethnical background on this sense was made quite difficult.
Sampling errors: The research data relies on a percentage mix of NH whites and NH Blacks among other groups. Although the results were statistically significant, the strength of the relationship between the variables remains low and therefore questionable. It is highly likely that the samples chosen really do not represent the occurrence in the population as a whole, thereby not being representative of the universe of late stage breast cancer patients.
Missing data: The SEER database is known to have many missing variables due to under-reporting of radiation therapy. One of the SEER states, California, is known to have under-reported many of the cancer cases. This is a problem that probably exists in all the 18 SEER regions since, most of the radio therapy sessions are recorded by hospitals as an out-patient therapy and are therefore likely to be missed in the cancer registries and databases. The lack of such data will consequently reduce the number of occurrences and types of radiation therapy, in large samples, leading to statistical errors (Yu, 2009).
The details about radiation therapy do not cover the scope, doses or reason for the recommendations. This impacts the overall prognoses and outcomes. Survivability also will differ, based on a similar set of patient and disease variables. There is no such standardization captured in the databases.
There is also a lack of information about hormonal therapy and chemotherapy. Co-morbidity is also not measured in the SEER database. That in turn influences rates of survivability.
Geographic migration: The SEER database does not take into account the migration of patients from one geographical location to another. This change will also affect the conditions of living environments and the course of the disease. Many of the tests and treatments may therefore, not get recorded in the representative sample. Second level malignancies and interventions may also be missed altogether, leading to erroneous recording of information and results.
Alternative therapies: The application and use of alternative therapy instead of radio therapy may lead to wrong conclusions. In many cases, since the SEER data does not measure adjuvant therapies, the rate of survivability or time of death may be wrongly attributed to the use of radiation therapy.
Selection bias: The study compares and contrasts the relationship between race and ethnicity with types of treatments. However, the SEER database has its own limitations in this respect. One of the limitations is selection bias. This occurs because the selection of patients to a particular course of treatment is not chosen at random. So, the possible benefits of a particular course of treatment in respect of a particular group may be biased. In many cases, the results of the treatments are assessed by individuals who are known to the patients. This also results in a bias. Often, the coding of the visits and medical events are directly related to administrative purposes - for payments or reimbursements and not tied to specific research objectives. This is another error that may be detrimental to any study.
Data collection for SEER databases is not done expressly for the purposes of research. Such general registries may have missing data or data that is not really representative of the real-world research objective. It may happen that the selection of groups for the study may include patients who are not really eligible for the study. This would again lead to multiple errors in research design and results. It is also important to note that Medicare data, does not include HMO participants, care given by Veteran’s Associations, miscellaneous expenditures and coverage by other policies. Medicare does not cover home care, nursing homes or routine checks. This leads to one more limiting factor and addition of bias in the SEER data (National Cancer Institute, n.d.).
Behavioral error: Patients may undergo changes in behavior over a course of time, besides experiencing the occurrence of co-morbid conditions. Many of the factors like smoking, alcohol, obesity are key factors that affect the incidence and outcome of breast cancer treatment. The behavioral aspects of patients after surgery or first round of radio therapy is not monitored. This may induce bias in the study.
Recurrence: There is no way to monitor and measure recurrence in the SEER data. In studies which require the onset of disease and timing parameters, the data really does not measure up. Recurrence data will only become available when the patient, uses Medicare for claims and goes in for treatment. Non availability of second recurrence data will surely lead to erroneous results in time variable studies.
Pre-Medicare information: Data on treatments and regimen before Medicare is not available. Diagnosis of cancers may have occurred before enrolling in to Medicare. Such important data is not captured in the SEER registry. Also, the reference years of diagnosis differ from state to state. The cut-off date for Connecticut, for example, is 1973, while that for New Jersey is 2000. This will also add bias to the samples chosen for the study.
Cultural biasedness: Data presented in the discussion solely compares disparities among various populations more than discussing a more effective manner of administering treatment and prevention of breast cancer.
Access: Access to different populations appears to be a relatively difficult issue since you can only gain access to those that are close to you. Getting to the minority population to get the real facts from the population becomes a problem. This makes issues such as racism predominant and evident among the larger population.
Sample sizes: After conducting a thoughtful research work and collecting the data that is quantified in the research work. It appears to me that the variables under scrutiny are relatively small compared to the issue of breast cancer that is quite a big thing especially in today’s world. The variables quantified were actually small for the research work.
Ideas and recommendations
It seems imperative therefore, to keep one set of control group for all the variables, in order to ameliorate such inherent data errors in SEER data. Regular audits of data will also help in minimizing errors and keeping the data in a form that can be used in research (Levine and Julian, 2008). Rapid advances in technology have increased the reach and type of treatments. More rigorous ways of patient monitoring are required to ensure that any and all treatments undertaken are recorded. The use of digital technology and big data analytics can help identify each study sample group with unique identifiers, which can be mapped over time. This will help circumvent the issues of effect of neighborhood environment and geo migration. Digital technology can also help in giving easy access to patients and researchers on information and treatment monitoring on a regular basis. Integration of insurance, Medicare and other databases also will remain a key factor. A single view of the patient under study will really help in removing any of the errors and biases which have been mentioned earlier. The era of big data and analytics has already arrived. The proper storage of relevant information will help in using the right sample cuts from the SEER data to ensure that errors are kept to a minimum and the results of any study remain unbiased and productive.
Conclusion
The recent years have witnessed much advancement in the diagnosis and treatment of breast cancer. Although the prevalence of breast cancer remains high, with more than 60,000 cases diagnosed in the United States in 2015, the survival rates among certain population groups have also shown encouraging growth. Lifestyle related factors such as diet, smoking, alcoholism, stress, are directly linked to the rise in the incidence of breast cancer. Genetic and physiological factors also contribute to the prevalence of cancer. The foregoing review, the research study and its results, show some alarming facts. In terms of the treatments given to breast cancer patients, we see a marked difference in surgical versus radiotherapy, proposed to NH Blacks as compared to White women. This is mainly due to the difference in socio economic conditions, rather than medical merits of the case. The causes for this level of discrimination, stemming solely from monetary or insurance considerations, needs to be reviewed at a policy level by the federal government. Collaborative effort needs to be initiated by government – with medical experts, insurers, patients and other stakeholders to make amends on how therapies are proposed, delivered and monitored. The paper also throws light on the clear association between the insurance type and the type of treatments. This needs to be reviewed and changed. We also notice that the disparities in survival rates are due to race and ethnic factors. This disparity needs to be addressed soon, by evolving a comprehensive, unifying healthcare policy that will bring the underserved and disadvantaged groups of the population in to the mainstream of efficient cancer care. Today, technology can change the way research studies are conducted and the SEER registries are maintained and updated. Minorities are the fastest growing group. Steps to bring in equality in the treatment and monitoring of breast cancer in ethnic minorities therefore, need to be taken on a war footing.
Future Research
More research work is required to gather information and findings related to early stages of breast cancer. Recent studies depict that a large population that was vitamin D deficient was likely to have their cancer disease continuously recur across various parts of the body. Furthermore, this population seems to have a very poor outlook. For this reason, more research work needs to be conducted to gather more information on whether Vitamin D would be such helpful solution towards the early treatment of cancer cases. Also, it would be very useful to test whether vitamin D levels are in the range of such kind of reasonable standards.
Moreover, since breast cancer is such a hard disease to treat. This gives a platform to other researchers to look into new drugs and ensure that more chemotherapy drugs are developed and are accessible even by the minority population. This would make it a real point towards fighting the war against breast cancer in women.
References
Bourjolly, J. N. (2013). Similarities in Coping Strategies but Differences in Sources of Support
Among African-American and White Women Coping with Breast Cancer. Journal of
Gynecologic Oncology, 19(2).
Bradley, C., Given, C., & and Roberts, C. (2002, April 3). Race, Socioeconomic Status, and
Breast Cancer Treatment and Survival. Journal of the National Cancer Institute, 94(7),
490-6.
Griggs, J., Culakova, E., Sorbero, S., Poniewierski, S., Wolff, A., Craford, D., . . . and Lyman, H.
(2007, June 20). Social and Racial Differences in Selection of Breast Cancer Adjuvant
Chemotherapy Regimens. Journal of Clinical Oncology, 25(18), 2522-27.
Hershman, D., McBride, R., Jacobson, J. S., Lamerato, L., Roberts, K., Grann, V. R., & Neugut,
A. I. (2005, September 20). Racial Disparities in Treatment and Survival Among Women
With Early-Stage Breast Cancer. Journal of Oncology, 23(27), 6639-6646.
Kim, S., Ferrante, J., Won, B. R., & Hameed, M. (2008, February 25). Barriers to adequate
follow-up during adjuvant therapy may be important factors in the worse outcome for
Black women after breast cancer treatment. World Journal of Surgical Oncology, 6(26).
Levine, M. and Julian, J., (2008). Registries that Show Efficacy: Good but not Good Enough.
Li, C., Malone, K., & Daling, J. (2003). Difference in breast cancer stage, treatment, and survival
Markossian, T. a. (2012). Disparities in late stage diagnosis, treatment, and breast cancer-related
death by race, age, and rural residence among women in Georgia. Women & Health,
52(4), 317-35.
Markossian, T., Hines, R., & and Bayakly, R. (2014, April). Geographic and Racial Disparities
in Breast Cancer-Related Outcomes in Georgia. Health Services Research, 49(2), 481-501.
Maskarinec, G., Sen, C., Koga, K., & Conroy, S. M. (2011, November). Ethnic Differences in
Breast Cancer Survival: Status and Determinants. Women’s Health (Lond Engl), 7(6),
677-687.
National Cancer Institute. (n.d.). Measures that are Limited or not Available in the Data. NCI.
Retrieved from: http://healthcaredelivery.cancer.gov/seermedicare/considerations/measures.html
Smith-Gagen, J., Carrillo, J., Ang, A., & and Perez-Stable, E. (2013, November). Practices that
Reduce the latina Survival Disparity after Breast Cancer. Journal of Women's Health,
22(11), 938-46.
Yu, X. Q. (2009). Socioeconomic disparities in breast cancer survival: relation to stage at
diagnosis, treatment and race. BMC Cancer, 9(364).
