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. 2020 Fall;10(1):61–83.

Disparities in Cervical Cancer Treatment Options between African American (Black) and White Women in Alabama

Isra Elhussin 1, David Nganwa 2, Ronald Peaster 3, Oyoyo Egiebor-Aiwan 4, Crystal M James 5, John Heath 6, Lecarde Webb 7, Ehsan Abdalla 8,*
PMCID: PMC8900975  NIHMSID: NIHMS1735917  PMID: 35261815

Abstract

There are disparities in cervical cancer treatment options between Black and White women in Alabama. This study design is to identify and assess factors contributing to the prevailing inequalities in cervical cancer treatment options between Blacks and Whites, who are living in urban, Black Belt (BB), and other rural counties of Alabama. The data of our study population, which was comprised of 2,124 cases of cervical cancer in women 17 years and older, were extracted from the 2004 to 2013 dataset of the Alabama Department of Public Health (ADPH) Cancer Registry. Using SAS software for the analysis, frequency distributions, chi-square, and logistic regression tests were generated. Racial disparities in cervical cancer treatment options for Blacks living within the same counties as Whites still exist. The study analysis showed that younger Blacks living in urban counties with advanced stages of cervical cancer were more likely to receive radiation treatment but were less likely to undergo surgical treatment options (p-value <.0001). Younger Blacks living in the BB and other rural counties were mainly treated with radiation for the early stages of cervical cancer (p-value 0.001), while older ones received surgery (p-value <.0001), and combined therapy of surgery and radiation (p-value 0.05). When adjusted for age, stage of cancer, and county of residence, Blacks had 2.76 (95% CI 0.90–8.86) times the odds of receiving immunotherapy compared to Whites. Blacks had 0.74 times adjusted odds (95% CI 0.58–0.95) of undergoing less surgery compared to Whites. Our study findings suggest that cervical cancer treatment options and control interventions targeted towards disadvantaged women, particularly Blacks living in the BB and other rural counties have the potential to reduce and/or eradicate this preventable disease.

Keywords: Cervical cancer, disparities, Alabama counties, Blacks, Whites, SAS software

Introduction

Cancer is a significant public health problem worldwide and is the second leading cause of death in the U.S. Cervical cancer affects the cells of the cervix in the lower part of the uterus that connects to the vagina distally. The majority of cervical cancer cases are caused by various strains of the human papillomavirus (HPV), primarily type 16 and 18. HPV proteins, E6 and E7, are consistently expressed in tumor cells (Borysiewicz et al., 1996). HPV infection is the most common sexually transmitted infection in the U.S, usually; however, when the body is exposed to HPV, the immune system is activated and prevents the virus from infecting the person. Unfortunately, the virus can survive for years and initiate the transformation of some cells on the surface of the cervix into cancerous cells. On the other hand, oral contraceptive pills, genetic, epigenetic, and environmental factors can increase the risk of developing cervical cancer.

Cervical cancer is the second leading cause of death due to cancer in women between 20 to 39 years old, underscoring the need to improve screening rates in this age group, as well as increasing the acceptance of and access to human papillomavirus vaccination (Siegel, Miller, & Jemal, 2017). There are three U.S. Food and Drug Administration (FDA) approved vaccines (Gardasil®, Gardasil-9®, and Cervarix®) that prevent HPV infection and therefore prevent the primary cause of cervical cancer (“U.S. Cancer Statistics Working Group. U.S. Cancer Statistics Data Visualizations Tool, based on November 2017 submission data (1999–2015): U.S. Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute;,” 2018). Therapeutic cancer vaccines, treat preexisting disease and are quite different from preventive vaccines that require the generation of T cell-mediated immunity, instead of the generation of neutralizing antibodies (Welters et al., 2008), (Su et al., 2010).

Cervical cancer is usually a slow-growing cancer, with no overt clinical signs in its early stages. In the advanced stages of the disease, the most common signs and symptoms are vaginal bleeding, vaginal discharge and pelvic pain (“Cervical cancer symptoms”, 2018). Classification of cancers is a crucial step in determining the best treatment plan. The International Federation of Gynecology and Obstetrics (FIGO) system (“Cervical Cancer Stages ( FIGO (International Federation of Gynecology and Obstetrics) staging system),” 2019) and the American Joint Committee on Cancer (AJCC) have developed systems to stage cervical cancer. Both systems are based on the tumor extent, spread to any lymph nodes, and distant metastasis. The stages are classified as a range from 0 to IV, with many subcategories within each numerical stage. If abnormal cells are detected on the Pap smear, a colposcopy procedure is then performed. A colposcopy uses a light microscope to examine the external surface of the cervix during a pelvic examination. A biopsy from the affected area undergoes a histopathologic examination to determine whether the changes are precancerous or are cancerous. Treatment options may include surgical treatments such as conization, hysterectomy or radical hysterectomy, radiation therapy, combined therapy of both surgery and radiation and/or chemotherapy (Chuang et al., 2016).

Recently, new treatment options which are immune-based cancer treatments have been introduced. To treat cervical cancer that has spread or recurred, immunotherapy is used. The occurrence of HPV-induced cancer is strongly associated with several factors. These include among others: failure to mount a robust HPV-specific type 1 T-helper and CTL responses; the lack of CD8+ T cells migrating into the tumor; the induction of HPV16-specific regulatory T cells; and the influx of regulatory T cells into the tumor (Welters et al., 2008). Monoclonal antibodies (mAbs) are outstanding treatment options for many cancers. Researchers have developed newer forms of mAbs, by attaching them to other therapeutic substances to enhance their effectiveness (“Immunotherapy and Immuno-oncology”, 2018). The U.S. Food and Drug Administration (FDA) recently approved the first Checkpoint Immunotherapy pembrolizumab (Keytruda®, Merck). It targets the PD-1 immune checkpoint, in patients with advanced, treatment-resistant cervical cancer that expresses PD-L1 (“How is Immunotherapy Changing the Outlook for Patients with Cervical Cancer?,” 2018). Pembrolizumab is prescribed to women whose cervical cancer metastasizes or recurs after chemotherapy. Immunotherapy, also called biologic therapy, is a new treatment option designed to boost the body’s natural defenses to fight the cervical cancer. It uses materials made either by the body or in a laboratory to improve, target, or restore immune system function. The immune checkpoint inhibitor pembrolizumab (Keytruda) is used to treat cervical cancer that has recurred or spread to other parts of the body during or after treatment with chemotherapy. Different types of immunotherapy can cause different side effects. Common side effects include skin reactions, flu-like symptoms, diarrhea, and weight changes (Cancer.Net., 2019).

In 2020, an estimated 13,800 cases of invasive cervical cancer are expected to be diagnosed, and 4,290 deaths are estimated to occur from cervical cancer (American Cancer Society, 2020). In the past 40 years, the number of cases of cervical cancer and the number of deaths from cervical cancer have decreased significantly. This decline largely is due to many women getting regular Pap tests for early detection (“National Institutes of Health (NIH) Cervical cancer: NIH Consensus Development Conference Statement,” 1996). Cervical cancer incidence rates declined by half between 1975 and 2014 from 14.8 per 100,000 to 6.9 per 100,000 respectively due to the widespread uptake of screening, primarily with the Pap test but the declines have slowed in recent years.

In Alabama, there were 1,148 new cases of cervical cancer from 2011 to 2015. For every 100,000 women, nine cervical cancer cases were reported. Over those years, 488 women died from cervical cancer. For every 100,000 women in Alabama, four died from cervical cancer (“U.S. Cancer Statistics Working Group. U.S. Cancer Statistics Data Visualizations Tool, based on November 2017 submission data (1999–2015): U.S. Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute;,” 2018). The 5-year relative survival rate for cervical cancer is 69% for White women and 56% for Black women. The five-year survival rate is 92% for the 46% of patients diagnosed when the cervical cancer is still in the early stages but falls to 17% for women diagnosed with late-stage disease (“Cancer Facts & Figures 2018, American Cancer Society,” 2018).

Materials and Methods

The data for our study population, was comprised of 2,124 cases of cervical cancer in women who were 17 years and older, were extracted from the 2004 to 2013 dataset of the Alabama Department of Public Health (ADPH) Cancer Registry. The percentage of patients receiving treatment combinations were compared between race (Black and White), age group (17–39 years, 40–49 years, and 50 years and older), and cervical cancer stages (stage I, II, III and IV). We conducted a series of analyses to determine whether disparities exist in CerCancer treatment options between the two races in the three groups of counties (urban, rural Black Belt (BB) and other rural counties of Alabama)). For the analysis, to generate frequency distributions, chi-square (Mantel-Haenszel), and Fisher exact test to assess multivariate predictors and to determine the frequency and association of receiving any treatment or lack of it between sets of independent and dependent variables the SAS software was used. Adjusted analysis using logistic regression accounted for the effects of confounding variables, yielding odds ratios of the independent effects of race on undergoing of a specific treatment. Potential confounders were chosen for the regression model via backward selection, with a likelihood ratio p-value of <0.05 which was considered sufficient for inclusion into the model. Inversely, in the frequency distributions and Chi-Square (χ2) tests, we stratified the counties of Alabama into two groups (urban and other rural counties) due to small sample size or no data in some of the rural counties, especially in the rural BBC. The logistic regression analysis takes into account the small sample size or no data in Alabama counties. Therefore, Alabama’s counties were stratified into three groups [(urban, rural BB and other rural counties) Figure 1) (Abdalla E, 2017)].

Figure 1.

Figure 1

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Urban, rural Black Belt and other rural counties of Alabama (Abdalla E, 2017).

In this study, the Surveillance, Epidemiology and End Results (SEER) staging system, and is which is based on the FIGO classification system was used. The classification of cervical cancer was into four stages. Stage I (IA1,IA2,IB) represents the localized stage (cancer is confined to the original organ); Stage II (IIA, IIB) and Stage III (IIIA, IIIB) represent the regional stage (cancer spreads to regional lymph nodes and/or spreads to immediately adjacent organs/tissues); Stage IV(IVA, IVB) represent distant stage (cancer metastasizes to distant organs/tissues). Age was stratified into three groups (17–39 years, 40–49 years, and 50 years and older). Percentages represent the frequency of receiving or not receiving any cervical cancer treatment options among Black and White women stratified by the three age groups and four stages of cervical cancer. Using graphical software, plotted along the y-axis were the percentages while on the x-axis were plotted the treatment types based on Cervical Cancer stage and race. The statistical analyses were conducted using SAS software (Version 9.4, SAS Institute Inc., Cary, NC, USA). All P-values were two-sided with a significance threshold of P<0.05.

Results

The detailed results of this study are presented in Tables 1 to 3 and Figures 2 to 11. Our analysis was comprised of 2,124 cases of cervical cancer, of these only 2,081 cases were the final sample size used for analysis comprised of 651 Blacks, and 1,430 Whites. Our results show subsequent analysis of the relationship between race, age group, geographical location, stage of cervical cancer, and selected treatment options of cervical cancer in Black and White women, living in urban, rural BB and other rural counties of Alabama from 2004 to 2013. The tables and figures summarized the comparison of treatment options stratified by race, age group, geographical location and stage of cervical cancer.

Table 1.

Comparison between treatment options among Black and White patients who were living in urban counties of Alabama and were diagnosed with cervical cancer from 2004–2013.

Treatment by Stage Blacks Whites
Age groups (in years) Age groups (in years)
17–39 *P value 40–49 *P value 50 & older *P value 17–39 *P value 40–49 *P value 50 & older *P value *p-value (interaction)
Y (%) N (%) Y (%) N (%) Y (%) N (%) Y (%) N (%) Y (%) N (%) Y (%) N (%)
Surgery
Stage I 73.91 24.24 * <.0001 74.07 13.04 * <.0001 56.72 17.74 * <.0001 74.65 20.69 * <.0001 77.12 22.81 * <.0001 59.66 19.48 * <.0001 * <.0001
Stage II 8.70 30.30 7.41 17.39 16.42 21.77 5.63 17.24 8.47 24.56 9.24 22.73
Stage III 13.04 42.42 16.67 41.30 20.90 33.87 17.61 46.55 11.86 35.09 26.89 28.57
Stage IV 4.35 3.03 1.85 28.26 5.97 26.61 2.11 15.52 2.54 17.54 4.20 29.22
Radiation
Stage I 27.91 83.33 * <.0001 27.12 73.17 * <.0001 23.77 44.93 0.0004 21.11 90.00 * <.0001 29.89 88.64 ** <.0001 22.29 63.27 * <.0001 * <.0001
Stage II 23.26 11.11 20.34 0.00 25.41 10.14 15.56 3.64 22.99 4.55 24.57 3.06
Stage III 41.86 5.56 35.59 17.07 35.25 18.84 51.11 5.45 35.63 3.41 37.14 11.22
Stage IV 6.98 0.00 16.95 9.76 15.57 26.09 12.22 0.91 11.49 3.41 16.00 22.45
Surgery & Radiation Sequence
Stage I 56.45 41.18 0.23 45.57 47.62 0.12 30.67 35.71 * 0.01 65.45 28.57 * 0.0002 63.70 45.00 0.14 38.71 30.36 * 0.01 * <.0001
Stage II 17.74 17.65 10.13 19.05 19.02 25.00 8.48 11.43 12.59 17.50 16.13 19.64
Stage III 24.19 29.41 26.58 33.33 27.61 39.29 20.00 54.29 16.30 16.30 23.96 42.86
Stage IV 1.61 11.76 17.72 0.00 22.70 0.00 6.06 5.71 7.41 7.50 21.20 7.14
Immunotherapy
Stage I 0.00 55.26 0.19 0.00 46.94 0.13 0.00 31.75 0.57 0.00 59.30 0.41 0.00 59.77 0.21 37.00 ^ ^ * 0.004
Stage II 33.33 17.11 50.00 11.22 50.00 19.58 0.00 9.05 100.00 13.22 16.85 ^
Stage III 66.67 23.68 50.00 27.55 50.00 29.10 100.00 25.63 0.00 19.54 27.84 ^
Stage IV 0.00 3.95 0.00 14.29 0.00 19.58 0.00 6.03 0.00 7.47 18.32 ^
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P* statistically significant difference (Mantel-Haenszel chi-square tests P-value <0.05).

Column percentages exclude those with missing data. Non-missing categories add up to 100%, except those due to rounding.

Percentage (%) = column Percentage %; Y= Yes received treatment; N= No treatment received.

^

Statistic not displayed due to fewer than 15 cases.

Table 2.

Comparison between treatment options among Black and White patients who were living in rural counties of Alabama and were diagnosed with cervical cancer from 2004–2013.

Treatment by Stage Blacks Whites
Age groups (in years) Age groups (in years)
17–39 *P value 40–49 *P value 50 & older *P value 17–39 *P value 40–49 *P value 50 & older *P value *p-value (interaction)
Y (%) N (%) Y (%) N (%) Y (%) N (%) Y (%) N (%) Y (%) N (%) Y (%) N (%)
Surgery
Stage I 70.37 20.00 * 0.003 64.29 12.00 * 0.01 71.11 17.39 * <.0001 77.61 27.78 * <.0001 76.27 14.29 * <.0001 69.47 24.71 * <.0001 * <.0001
Stage II 7.41 46.67 7.14 32.00 13.33 26.09 3.73 22.22 8.47 21.43 11.58 32.76
Stage III 14.81 13.33 21.43 40.00 8.89 31.88 16.42 38.89 12.71 33.93 12.63 22.99
Stage IV 20.00 7.41 7.14 16.00 6.67 24.64 2.24 11.11 2.54 30.36 6.32 19.54
Radiation
Stage I 21.05 78.26 * 0.001 20.00 50.00 0.06 28.00 58.97 * 0.0003 25.32 90.83 * <.0001 24.32 80.00 * <.0001 30.99 57.14 * <.0001 * <.0001
Stage II 36.84 8.70 32.00 7.14 25.33 12.82 20.25 0.92 22.97 5.00 33.92 10.20
Stage III 26.32 4.35 40.00 21.43 32.00 5.13 45.57 6.42 39.19 5.00 22.22 14.29
Stage IV 15.79 8.70 8.00 21.43 14.67 23.08 8.86 1.83 13.51 10.00 12.87 18.37
Surgery & Radiation Sequence
Stage I 22.22 60.61 * 0.02 40.00 29.41 0.85 63.64 32.61 * 0.05 27.27 70.97 * <.0001 37.93 60.00 * 0.03 57.50 37.55 0.08 * 0.002
Stage II 22.22 21.21 20.00 23.53 13.64 22.83 12.12 8.39 17.24 11.72 15.00 27.07
Stage III 44.44 6.06 20.00 35.29 18.18 23.91 51.52 16.77 37.93 15.86 20.00 19.21
Stage IV 11.11 12.12 20.00 11.76 4.55 20.65 9.09 3.87 6.90 12.41 7.50 16.16
Immunotherapy
Stage I 0.00 53.66 0.12 ^ 30.77 ^ ^ 38.60 ^ 0.00 63.64 0.37 0.00 56.65 0.11 50.00 40.45 1.00 0.21
Stage II 0.00 21.95 ^ 23.08 ^ 21.05 0.00 9.09 0.00 12.72 50.00 25.09
Stage III 0.00 14.63 ^ 33.33 ^ 22.81 100.00 22.46 0.00 19.65 0.00 19.05
Stage IV 100.00 9.76 ^ 12.82 ^ 17.54 0.00 4.81 100.00 10.98 0.00 14.98
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P* statistically significant difference (Mantel-Haenszel chi-square tests P-value <0.05).

Column percentages exclude those with missing data. Non-missing categories add up to 100%, except those due to rounding.

Percentage (%) = column Percentage %; Y= Yes received treatment; N= No treatment received.

^

Statistic not displayed due to fewer than 15 cases.

Table 3.

Comparison between treatment options among Black and White patients who were living in urban counties of Alabama and were diagnosed with cervical cancer from 2004–2013.

Characteristic N Surgery Radiation Surgery & Radiation Sequence Immunotherapy
Total 1844 53.09% 55.26% 18.17% 0.76%
979/1844 1019/1844 335/1844 14/1844
Age group in years, OR (95% CI) 17–39 509 Reference Reference Reference Reference
40–49 488 0.867 1.179 1.102 0.578
0.641–1.173 0.883–1.576 0.799–1.521 0.145–2.070
50 & older 847 0.381 1.707 0.918 0.244
0.291–0.498 1.311–2.224 0.683–1.238 0.061–0.884
Race, OR (95% CI) Whites 1279 Reference Reference Reference Reference
Blacks 565 0.738* 1.068 0.899 2.757*
0.575–0.945 0.836–1.363 0.681–1.180 0.901–8.856
Stage, OR (95% CI) Stage 1 875 Reference Reference Reference Reference
Stage 2 301 0.108 11.918 1.346 16.857
0.079–0.146 8.488–17.068 0.945–1.900 2.648–326.297
Stage 3 440 0.146 11.194 2.189 12.593
0.112 0.189 8.415–15.060 1.652–2.901 2.121–239.062
Stage 4 228 0.055 3.024 0.618 9.875
0.036–0.081 2.224–4.127 0.372–0.983 0.917–216.545
County, OR (95% CI) Urban 1018 Reference Reference Reference Reference
Other Rural 725 0.838 0.880 0.801 0.783
0.662–1.059 0.701–1.105 0.616–1.039 0.205–2.520
Rural BBC 101 0.951 1.211 1.243 0.907
0.577–1.561 0.737–2.003 0.729–2.047 0.048–5.262
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Logistic regression models included variables for age group, race, stage of cervical cancer and county of residence. A separate regression model was developed for each treatment option. Those missing particular treatment data were excluded from the relevant regression models.

OR (95% CI): odds ratio (95% confidence interval).

*

Odds ratio shows statistically significant effect (p<0.05 via logistic regression).

Figure 2.

Figure 2

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Frequency distributions among Black and White patients living in urban counties of Alabama, diagnosed with stage I, II, III and IV of cervical cancer and had received surgery treatment from 2004 to 2013.

Figure 3.

Figure 3

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Frequency distributions among Black and White patients living in urban counties of Alabama, diagnosed with stage I, II, III and IV of cervical cancer and had received radiation treatment from 2004 to 2013.

Figure 4.

Figure 4

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Frequency distributions among Black and White patients living in urban counties of Alabama, diagnosed with stage I, II, III and IV of cervical cancer and had received surgery and radiation sequence treatment from 2004 to 2013.

Figure 5.

Figure 5

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Frequency distributions among Black and White patients living in urban counties of Alabama, diagnosed with stage I, II, III and IV of cervical cancer and had received immunotherapy treatment from 2004 to 2013.

Figure 6.

Figure 6

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Frequency distributions among Black and White patients living in rural counties of Alabama, diagnosed with stage I, II, III and IV of cervical cancer and had received surgery treatment from 2004 to 2013.

Figure 7.

Figure 7

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Frequency distributions among Black and White patients living in rural counties of Alabama, diagnosed with stage I, II, III and IV of cervical cancer and had received radiation treatment from 2004 to 2013.

Figure 8.

Figure 8

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Frequency distributions among Black and White patients living in rural counties of Alabama, diagnosed with stage I, II, III and IV of cervical cancer and had received surgery and radiation sequence treatment from 2004 to 2013.

Figure 9.

Figure 9

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Frequency distributions among Black and White patients living in rural counties of Alabama, diagnosed with stages I, II, III and IV of cervical cancer and had received immunotherapy treatment from 2004 to 2014.

Figure 10.

Figure 10

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Adjusted odds ratios for receiving immunotherapy treatment option, among White and Black patients who were diagnosed with cervical cancer from 2004 to 2013.

Figure 11.

Figure 11

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Adjusted odds ratios for receiving surgery treatment option, among White and Black patients who were diagnosed with cervical cancer from 2004 to 2013.

In urban counties, as presented in Table 1 and Figure 2, 77.12% of Whites 40 to 49 years old living and diagnosed with stage I of cervical cancer were significantly the most likely to receive surgery treatment option with a p-value of <0.0001. On the other hand, 1.85% of Blacks 17 to 39 years old and diagnosed with stage IV of cervical cancer were significantly the least likely to receive surgery treatment option with a p-value of <0.0001. In Table 1 and Figure 3, 51.11% of Whites 17 to 39 years old living in urban counties and diagnosed with stage III of cervical cancer were significantly the most likely to receive radiation treatment option with a p-value of <0.0001. While 6.98% of Blacks 17 to 39 years old and diagnosed with stage IV were significantly the least likely to receive radiation treatment option with a p-value of <0.0001. As shown in Table 1 and Figure 4, in urban counties, 65.45% of Whites 17 to 39 years old and diagnosed with stage I of cervical cancer were significantly the most likely to receive surgery-radiation sequence treatment option with a p-value of <0.0001. Whereas, 1.61% of Blacks in the same age group and diagnosed with stage IV were significantly the least likely to receive the same form of treatment with a p-value of <0.0001. Table 1 and Figure 5 show that 100% of Whites 17 to 39 and 40 to 49 years old living in urban counties and diagnosed with stage III and stage II of cervical cancer respectively were significantly the most likely to receive immunotherapy treatment options with a p-value of 0.004. Blacks in age groups 17 to 39, 40 to 49 and 50 years and older and diagnosed with stage I and stage IV of cervical cancer never received immunotherapy treatment options. While, in Whites in all age groups, except for those 50 years old diagnosed with stages I, III and IV never received the same treatment option.

In rural counties, as shown in Table 2 and Figure 6, 77.61% of Whites 17 to 39 years old and diagnosed with stage I of cervical cancer were significantly the most likely to receive surgery treatment option with a p-value of <0.0001. On the other hand, 2.24% of Whites in the same age group and diagnosed with stage IV were significantly the least likely to receive the same form of treatment with a p-value <0.0001. In Table 2 and Figure 7, in rural counties, 45.57% of Whites 17 to 39 years old and diagnosed with stage III of cervical cancer were significantly the most likely to receive radiation treatment option with a p-value of <0.0001. While 8.00% of Blacks 40 to 49 years old and diagnosed with stage IV were significantly the least likely to receive radiation treatment option with a p-value of <0.0001. As presented in Table 2 and Figure 8, 63.64% of Blacks 50 years and older living in rural counties and diagnosed with stage I of cervical cancer were significantly the most likely to receive surgery-radiation sequence treatment option with a p-value of 0.002. Whereas, 4.55% of Blacks in the same age group and diagnosed with stage IV were significantly the least likely to receive the same form of treatment with a p-value of 0.002. Regarding immunotherapy treatment option, Table 2 and Figure 9 indicate that there were no significant differences between Blacks and Whites diagnosed with cervical cancer stratified by the three age groups and the four cancer stages.

In this study, a series of logistic regression models were developed using variables for age group, race, cervical cancer stage and counties of residence (urban, rural BB and other rural) (Table 3 and Figures 10 to 11). Adjusted for age, stage and county of residence, Blacks had 2.76 (95% CI 0.90–8.86) times adjusted odds of receiving more immunotherapy treatment option, also Blacks had 0.74 (95% CI 0.58–0.95) times adjusted odds of receiving less surgery treatment option, compared to their White counterparts. Both Blacks and Whites 50 years and older and diagnosed with cervical cancer had 0.244 (95% CI 0.061–0.884) times adjusted odds of receiving less immunotherapy treatment option, compared to those 17 to 39 years old. Additionally, both Blacks and Whites 50 years and older had 1.707 (95% CI 1.311–2.224) times adjusted odds of receiving more radiation treatment option, compared to those 17 to 39 years old. Our results show that Blacks living in urban counties regardless of their age whether in early or advanced stages of the disease, they are likely to receive immunotherapy treatment option. In addition, Black women were more likely to receive radiation and less likely to receive surgery compared to their White counterparts.

Discussion

In this study we examined the racial differences in cervical cancer treatment options in urban, rural BB and other rural counties of Alabama between 2004 and 2013, controlling for age groups and cervical cancer stages. Previous studies in the U.S show higher mortality rates from cervical cancer in Blacks compared to Whites (Howell, Chen, & Concato, 1999). This disparity can be explained primarily by the fact that Blacks are most likely to be diagnosed for the first time when cervical cancer is already in more advanced clinical stages. Lack of access to screening services and barriers to care have been suggested as explanations for the more advanced stages at presentation and consequently the higher mortality rates in Blacks due to cervical cancer (Chen, Trapido, & Davis, 1994; Howell et al., 1999; Shelton, Paturzo, Flannery, & Gregorio, 1992). More importantly, our study suggests that the higher mortality rates among Blacks with cervical cancer could be due to the less aggressiveness and inappropriate treatment options in this minority population. We advocate that equivalent treatment options are made available to Black and White patients with cervical cancer in Alabama counties. Black women are usually presented with more advanced stages of the disease which lead to higher mortality rate among them. Differences in care and treatment options availability may contribute to the racial disparities in outcomes for women with cervical cancer. These differences in outcomes may be emanating from the unequal access to healthcare or from biologic distinctions between women of different racial and ethnic backgrounds. They may also arise from variations in comorbidities that usually accompany a cancer diagnosis (Fleming, Schluterman, Tracy, & Temkin, 2014). Although lower educational attainment, older age, obesity, smoking, and neighborhood poverty have been found to be independently related to a decreased likelihood of recent Pap smear screening. Previous studies, however, demonstrate that Pap smear screening rates have become quite similar between Black and White women (Fleming et al., 2014; Harlan, Bernstein, & Kessler, 1991).

In this study, 100% of Whites 17 to 39 and 40 to 49 years old living in urban counties and diagnosed with stages III and II of the disease respectively were significantly the most likely to receive immunotherapy treatment option. Even though, Blacks never received 100% of this treatment option, there were the most likely to receive the same treatment option in stages II and III in all of their age groups. Whereas, their White counterparts 50 years and older were the only ones to receive immunotherapy treatment option in all stages of cervical cancer. In rural counties, 100% of both Blacks 17 to 39 years old diagnosed with advanced stage IV of cervical cancer and Whites 17 to 39 and 40 to 49 years old diagnosed with advanced stages III and IV of the disease respectively. These three age groups of Blacks and Whites were the most likely to receive immunotherapy treatment option compared to the other three treatment options (surgery, radiation and, surgery and radiation sequence). However, there were no significant differences between Blacks and Whites diagnosed with cervical cancer stratified by the three age groups and the four cancer stages. Our logistic regression results showed that when adjusted for age, stage and county of residence, then the immunotherapy treatment option is the most likely to be offered to Blacks living in urban counties regardless of their age whether in early or advanced stages of the disease. In addition, Black women were more likely to receive radiation treatment option and less likely to receive surgery treatment option compared to their White counterparts.

Surgery is the most common treatment option for stage I cervical cancer in both Blacks and Whites. In urban counties, Whites compared to Blacks in all age groups diagnosed with this stage of disease were the most likely to receive this treatment option. Although, in urban counties, both Blacks and Whites of all age groups and with all stages of cervical cancer, the trends for receiving radiation as the treatment option were of an undulating nature. The trend ranged from a highest of 51.11% in Whites 17 to 39 years and diagnosed with stage III of the disease to a lowest of 6.98% in Blacks in the same age group but diagnosed with stage IV of the disease. In rural counties like in urban counties, surgery is also the most common treatment option in both Blacks and Whites. However, in rural counties, Whites compared to Blacks in all age groups diagnosed with stage IV of the disease were the most likely to receive this treatment option, expect in Blacks 50 years and older who were the most likely to receive this treatment option than their White counterparts in the same age group. Similarly, as in urban counties, both Blacks and Whites living in rural counties in all age groups and with all stages of cervical cancer, the trends for receiving radiation as the treatment option were of an undulating nature. The trend ranged from a highest of 45.57% in Whites 17 to 39 years old, diagnosed with stage III of the disease to a lowest of 8% in Blacks 40 to 49 years old, and diagnosed with stage IV of the disease. In contrast to our findings regarding surgery and radiation treatment options by race, age, stage and county, a previous study shows that among women diagnosed with early stage of cervical cancer, non-Hispanic Black women were more likely to receive radiation treatment option and less likely to receive surgery treatment option, which is the standard treatment of care. Similarly, in the same study, it stated that in the late stages of cervical cancer, non-Hispanic Black women were less likely to receive the surgery treatment option. The percentages receiving radiation treatment option across races were similar for late stage disease. In both late and early stage disease, the proportion of Hispanic women receiving radiation and surgery was similar to non-Hispanic White women (Markt et al., 2018). Additionally, previous studies showed that Black patients were less likely to receive surgical therapy and more likely to receive radiotherapy compared with their White counterparts (Fleming, S. et al 2014, Rauh-Hain JA et al. 2013). Our study confirmed their statement that Blacks received different treatment options than Whites even when adjusted for stage at diagnosis.

As for Blacks and Whites of all age groups, living in urban counties diagnosed with all stages of cervical cancer, the trends for receiving surgery and radiation sequence as the treatment option were also of an undulating nature. The trend ranged from a highest of 65.45% in Whites 17 to 39 years and diagnosed with stage I of the disease to a lowest of 1.61% in Blacks in the same age group but diagnosed with stage IV of the disease. In Blacks and Whites of all age groups, living in rural counties diagnosed with all stages of cervical cancer, the trends for receiving surgery and radiation sequence as the treatment option were also of an undulating nature. The trend ranged from a highest of 63.64% in Blacks 50 years and older and diagnosed with stage I of the disease to a lowest of 4.55% in Blacks in the same age group but diagnosed with stage IV of the disease. Overall, in urban counties, Whites 17 to 39 years and diagnosed with stage I of cervical cancer were the most likely to receive surgery and radiation sequence treatment option, whereas in rural counties Blacks 50 years and older and diagnosed with stage IV of the disease were the most likely to receive the same treatment option.

Our analysis, however, has some limitations. Although several prognostic factors are included in the analysis, not all of them are considered. Information on life-style or other individual factors such as screening access and use, socioeconomic status and comorbidities were not available from the Alabama Department of Public Health (ADPH) Cancer Registry dataset or accessible from the SEER database. Therefore, in this analysis, those factors are not considered. In addition, there was no demographic data for example, income, education and employment link to the cervical cancer treatments in Alabama. Some cervical cancer data regarding treatments especially the immunotherapy treatment option were missing for patients living in urban, rural BB and other rural counties. Contrariwise, in the frequency distributions and χ2 tests, the counties of Alabama are in only two groups, urban and rural counties. This is because some of the data was not possible to calculate due to the small number of cases or no data in some of the rural counties, especially in the BBC.

Conclusion

In this study, our results using chi-square test showed that patterns of racial disparity and inequality, all contribute to an environment in which Black women living in urban, rural BB and other rural counties of Alabama were less likely to receive the four cervical cancer treatment options (surgery, radiation, surgery and radiation sequence and immunotherapy). In some treatment options, Blacks diagnosed with different stages and age groups living in different counties were the most likelky to receive cervical cancer treatment options, compared to their White countraparts. In urban and rural counties, it is only in the immunotherapy treatment option that both Blacks and Whites received 100% treatment in some stages and age groups, compared to the three other treatment options. Our logistic regression results showed that immunotherapy treatment option is in most cases likely to be for Blacks living in urban counties, compared to those living in rural BB and other rural counties, regardless of their age whether in early or advanced stages of the disease. In addition, Black women were less likely to receive surgery treatment option and more likely to receive radiation treatment option, compared to their White counterparts. These disparities may be due to lack of consistent health insurance coverage as a significant barrier to treatment and care. Without consistent and reliable health insurance, many low-income women are obliged to postpone or forget treatment, including routine Pap smears and follow up screening for abnormal results. Early detection matters and gaps in health insurance coverage can mean that warning signs, which could help in detection and prevent progression of the cervical cancer, before missing the signs.

We recommend that in order to improve treatment of cervical cancer with immunotherapy treatment option in minorities, more clinical research is needed in three major area:. First, identify scientifically rational combinations that are likely to work better together than alone, then, learn how to create personalized immunotherapy or combination treatment regimens based on each patient’s unique cancer and immune response. Finally, discover new cancer markers that will allow early prediction about the treatments that are most likely to be safe and effective for a specific patient. We suggest that minority participation in clinical trials should be increased and also to include samples and genomic data from diverse populations to help in edge cutting research which will lead eventually to improved minority outcomes in cervical cancer treatments.

Footnotes

Author Contributions

Isra Elhussin, MD, MS, Integrative Bioscience (IBS) PhD Fellow: Is the first author and major conceiver and designer of the manuscript. Participated and made major contributions to the analysis, interpretation of the data and writing of the manuscript. Critically reviewed manuscript and approved the final version.

Ehsan Abdalla, DVM, MSc (Hons) (Vet PATH), MSc & PhD (Epidemiology and Risk Analysis): Is the corresponding author, has given significant intellectual inputs and supervised the work, participated in the conceiving and designing of the manuscript. Made major contributions to analysis, interpretation of the data and writing of the manuscript. Critically reviewed manuscript and approved the final version.

David Nganwa, DVM, MPH: Participated in designing of the manuscript. Made substantial contributions to analysis, interpretation of the data and writing of the manuscript. Critically reviewed manuscript and approved the final version.

Ronald Peaster, MS, Integrative Bioscience (IBS) PhD Fellow: Made substantial contributions to analysis and interpretation of the data. Critically reviewed manuscript and approved the final version.

Oyoyo Egiebor-Aiwan, MD, MPH: Made substantial contributions to analysis and interpretation of the data. Critically reviewed manuscript and approved the final version.

Crystal M. James, JD. MPH: Participated in the writing of the manuscript and critically reviewed manuscript and approved the final version.

John Heath, MS, PhD: Participated in the writing of the manuscript and critically reviewed manuscript and approved the final version.

Lecarde Webb, MPH, PMP, Integrative Bioscience (IBS) PhD Fellow: Made substantial contributions to analysis and interpretation of the data. Critically reviewed manuscript and approved the final version.

Authors’ Note

The authors would like to acknowledge Mr. Justin T. George of the Cancer Epidemiology/Cancer Prevention and Control Division, of the Alabama Department of Public Health, Alabama, USA, for providing us with the data used in this study. This study was funded by the Tuskegee University Center for Biomedical Research/Research Centers in Minority Institutions (TU CBR/RCMI) Program at the National Institute of Health (NIH) with a CBR/RCMI U54 grant, with grant number MD007585. The authors have no competing interests to disclose.

References

  1. Abdalla E. PhD. Tuskegee University; 2017. Excessive Cervical Cancer Mortality Among African American Women: A Comparative Study. [Google Scholar]
  2. AmericanCancerSociety. Cancer Facts & Figures 2020. 2020. Retrieved from https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2020/cancer-facts-and-figures-2020.pdf.
  3. Borysiewicz L, Fiander A, Nimako M, Man S, Wilkinson GWG, Westmoreland D, Boursnell M. A recombinant vaccinia virus encoding human papillomavirus types 16 and 18, E6 and E7 proteins as immunotherapy for cervical cancer. The Lancet. 1996;347(9014):1523–1527. doi: 10.1016/s0140-6736(96)90674-1. [DOI] [PubMed] [Google Scholar]
  4. Cancer Facts & Figure s 2018. American Cancer Society; 2018. Retrieved from https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2018/cancer-facts-and-figures-2018.pdf. [Google Scholar]
  5. Cancer.Net. Cervical Cancer: Types of Treatment. 2019. Retrieved from https://www.cancer.net/cancer-types/cervical-cancer/types-treatment.
  6. Cervical Cancer Stages ( FIGO (International Federation of Gynecology and Obstetrics) staging system) 2019. Retrieved from https://www.cancer.org/cancer/cervical-cancer/detection-diagnosis-staging/staged.html.
  7. Cervical cancer symptoms. 2018. Retrieved from https://www.mayoclinic.org/diseases-conditions/cervical-cancer/symptoms-causes/syc-20352501.
  8. Chen F, Trapido EJ, Davis K. Differences in stage at presentation of breast and gynecologic cancers among whites, blacks, and Hispanics. Cancer. 1994;73(11):2838–2842. doi: 10.1002/1097-0142(19940601)73:11<2838::aid-cncr2820731129>3.0.co;2-a. [DOI] [PubMed] [Google Scholar]
  9. Chuang LT, Temin S, Camacho R, Dueñas-Gonzalez A, Feldman S, Gultekin M, Kidd EA. Management and care of women with invasive cervical cancer: American Society of Clinical Oncology resource-stratified clinical practice guideline. Journal of Global Oncology. 2016;2(5):311–340. doi: 10.1200/JGO.2016.003954. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Fleming S, Schluterman NH, Tracy JK, Temkin SM. Black and White Women in Maryland Receive Different Treatment for Cervical Cancer. PLOS ONE. 2014;9(8):e104344. doi: 10.1371/journal.pone.0104344. doi: 10.1371/journal.pone.0104344. Retrieved from . [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Harlan LC, Bernstein AB, Kessler LG. Cervical cancer screening: who is not screened and why? Am J Public Health. 1991;81(7):885–890. doi: 10.2105/ajph.81.7.885. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. How is Immunotherapy Changing the Outlook for Patients with Cervical Cancer? 2018. Retrieved from https://www.cancerresearch.org/immunotherapy/cancer-types/cervical-cancer.
  13. Howell EA, Chen Y-T, Concato J. Differences in cervical cancer mortality among black and white women1. Obstetrics & Gynecology. 1999;94(4):509–515. doi: 10.1016/s0029-7844(99)00334-8. [DOI] [PubMed] [Google Scholar]
  14. Immunotherapy and Immuno-oncology. 2018. Retrieved from https://www.cancerresearch.org/scientists/clinical-accelerator/mission.
  15. Markt SC, Tang T, Cronin AM, Katz IT, Howitt BE, Horowitz NS, Wright AA. Insurance status and cancer treatment mediate the association between race/ethnicity and cervical cancer survival. PloS one. 2018;13(2):e0193047. doi: 10.1371/journal.pone.0193047. doi: [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. National Institutes of Health (NIH) Cervical cancer: NIH Consensus Development Conference Statement. 1996. Retrieved from http://consensus.nih.gov/1996/1996CervicalCancer102html.htm.
  17. Shelton D, Paturzo D, Flannery J, Gregorio D. Race, stage of disease, and survival with cervical cancer. Ethnicity & Disease. 1992;2(1):47–54. [PubMed] [Google Scholar]
  18. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA: A Cancer Journal for Clinicians. 2017;67(1):7–30. doi: 10.3322/caac.21387. Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.3322/caac.21387. [DOI] [PubMed] [Google Scholar]
  19. Su J-H, Wu A, Scotney E, Ma B, Monie A, Hung C-F, Wu T-C. Immunotherapy for cervical cancer. BioDrugs. 2010;24(2):109–129. doi: 10.2165/11532810-000000000-00000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. U.S. Cancer Statistics Working Group. U.S. Cancer Statistics Data Visualizations Tool, based on November 2017 submission data (1999–2015) U.S. Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute; 2018. Retrieved from www.cdc.gov/cancer/dataviz. [Google Scholar]
  21. Welters MJP, Kenter GG, Piersma SJ, Vloon APG, Löwik MJG, Berends-van der Meer DMA, van der Burg SH. Induction of Tumor-Specific CD4+ and CD8+ T-Cell Immunity in Cervical Cancer Patients by a Human Papillomavirus Type 16 E6 and E7 Long Peptides Vaccine. Clinical Cancer Research. 2008;14(1):178–187. doi: 10.1158/1078-0432.ccr-07-1880. Retrieved from http://clincancerres.aacrjournals.org/content/clincanres/14/1/178.full.pdf. [DOI] [PubMed] [Google Scholar]

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