Introduction: Whether social determinants of health (SDOH) affect US breast and colon cancer screening rates remains unclear. That said, in 2011 the CDC began recording a social vulnerability index (SVI) for all US counties. SVI was designed to capture four SDOH: socioeconomic status (SES), household composition and disability, minority status and language, and housing type and transportation. This retrospective study sought to determine the association of county-level SVI with breast and colon cancer screening rates. Methods: We used publicly available data from the CDC 2018 SVI database to collect SVI scores for every US county. SVI scores range from 0.1 to 1. A lower score indicates low vulnerability, while a higher score suggests high vulnerability. SVI scores were merged with publicly available data from the 2018 Behavioral Risk Factor Surveillance System (BRFSS) and National Health Interview Survey (NHIS) containing county modeled estimates for breast and colon cancer screening rates. Counties were then divided into < 50th percentile and >= 50th percentile for breast and colon cancer screening. SVI scores and their four SDOH were compared between groups. Statistical significance between groups was assessed at an alpha less than 0.5. Linear regression was used to identify the association between high county-level SVI and the probability of being >= 50th percentile in breast and colon cancer screening. Results: This study involved 3,109 counties. Compared to counties >= 50th percentile in breast cancer screening (n = 1543), those < 50th percentile (n = 1566) were significantly worse off in SES (0.60 ± 0.27 vs. 0.41 ± 0.27), household composition and disability (0.58 ± 0.28 vs. 0.42 ± 0.28), minority status and language (0.51 ± .30 vs. 0.49 ± .28), housing type and transportation (0.53 ± 0.29 vs. 0.46 ± 0.28), and overall SVI (0.58 ± 0.28 vs. 0.42 ± 0.27) (p < .0001). Likewise, compared to counties >= 50th percentile in colon cancer screening (n = 1548), those < 50th percentile (n = 1561) were also significantly worse off in SES (0.63 ± 0.27 vs. 0.38 ± 0.25), household composition and disability (0.59 ± 0.27 vs. 0.41 ± 0.27), minority status and language (0.54 ± .30 vs. 0.45 ± .27), housing type and transportation (0.54 ± 0.29 vs. 0.46 ± 0.28), and overall SVI (0.61 ± 0.28 vs. 0.39 ± 0.27) (p < .0001). High SVI counties compared with low SVI counties were significantly less likely to be >= 50th percentile in breast cancer and colon cancer screening, OR 0.24 (95% CI 0.20 - 0.29) and 0.14 (95% CI 0.12 - 0.18). Finally, county-level SVI percentile correlated negatively with breast and colon cancer screening rates, Pearson coefficient -0.35 and -0.46. Conclusions: This study highlights the significant impact of US county-level SVI on breast and colon cancer screening rates, signaling the need for more effective intervention strategies and allocation of resources to help improve SDOH for our country's most vulnerable citizens. Citation Format: Akhil Mehta, Eric Lau, Gayathri Nagaraj, Hamid Mirshahidi. Association of US county-level social vulnerability index (SVI) with breast and colon cancer screening rates [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3662.
Background: The impact of financial toxicity (FT) on cancer patients is significant in terms of lost productivity and poor quality of life (QoL). Past studies have reported negative influence of high FT on patients actively undergoing treatment for breast cancer. However, existing data largely comes from quaternary referral centers, and the populations surveyed may not be generalizable in terms of income and insurance status across the United States. There is also limited understanding regarding the relationship between FT measured throughout the continuum of cancer care, demographics, disease factors, and QoL indicators in breast cancer survivors, particularly those from underserved communities. Methods: Breast cancer survivors who received treatment between 2015 and 2019 at Loma Linda University Cancer Center located in San Bernardino County, CA were invited to complete an anonymous online survey assessing demographics, disease history, FT, and QoL. A modified version of the Comprehensive Score for Financial Toxicity (COST) survey was used to assess FT at baseline and after treatment. The patient-reported outcomes measurement information system (PROMIS) survey was used to assess QoL. Demographic data were summarized using descriptive statistics. Associations between disease factors and FT measured at baseline and after treatment were analyzed using multivariable linear regression. Positive COST score coefficients indicate lower FT, while negative COST score coefficients indicate higher FT. Correlations between FT and QoL were evaluated using the Pearson correlation. Results: A total of 407 surveys were sent to breast cancer survivors who met study criteria, of whom 16% responded. Amongst 65 patients included in this analysis, the median age was 64 (IQR 56, 70), 68% were white (n = 44), 18% were unemployed, 13% had a high school or lower level of education, and 16% had an annual income < $30,000. Mean COST score at baseline and after treatment were 21.6 ± 9.6 and 12.9 ± 7.8, respectively. During treatment, 21% of patients turned down or skipped treatment, 23% quit their job, and 15% reported family members quit their job. At baseline, lower FT was significantly associated with age > 80 (6.2 95% CI: 4.1 to 8.3), presence of a college (4.5 95% CI: 1.4 to 10.4) or graduate degree (5.2 95% CI: 4.7 to 6.2), current employment (2.7 95% CI: 2.0 to 3.4), retiree status (6.7 95% CI: 0.4 to 13.0), and household income > $30,000 (5.9 95% CI: 2.7 to 9.1) (p < 0.05), while higher FT was significantly associated with Hispanic ethnicity (-4.1 95% CI: -6.7 to -1.5), Medicare (-1.6 95% CI: -5.2 to -2.0), and Medicaid insurance (-6.9 95% CI: -12.5 to -1.2) (p < 0.05). After treatment, higher FT was significantly associated with receiving 3 or more combined modality treatments (-5.6 95% CI: -9.7 to -1.5) and having 5 or more treatment-related side effects (-6.0 95% CI: -10.4 to -1.6) (p < 0.05). Finally, FT after treatment overall correlated positively with physical and mental health (Pearson coefficient 0.63 and 0.60 respectively, p < 0.01). Conclusions: These findings suggest a significant association between FT, baseline demographics, treatment modalities, side effects, and quality of life in an underserved population of breast cancer survivors. In the future, FT should be assessed at baseline and throughout the continuum of breast cancer care to provide individualized assistance to patients facing financial strain, as it affects compliance to treatment which in turn can adversely affect cancer-related outcomes and QoL. Additional policies are needed to address the increasing cost of breast cancer care. Citation Format: Akhil Mehta, Jukes Namm, Ellen D'Errico, Eric Lau, Sharon Lum, Gayathri Nagaraj. Burden of financial toxicity in an underserved population of breast cancer survivors [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-11-25.
Compared to other ethnic groups, South Asians are at higher risk for cardiovascular disease and diabetes mellitus. Traditional risk factor assessment, developed mainly in a white European-descent populations, may underestimate the incidence of cardiovascular disease in South Asians. Our study examined the relationship between coronary calcification, a strong predictor of cardiovascular events, and other traditional cardiovascular risk factors in South Asians. We analyzed the association of coronary calcification with both traditional and emerging factors commonly used to predict cardiovascular risk. These factors include the lipid panel (total cholesterol, LDL-C, HDL-C, and triglycerides), fasting blood glucose, high-sensitivity CRP, family history of coronary artery disease and diabetes, and the ACC/AHA-recommended atherosclerotic cardiovascular disease (ASCVD) risk score. We found that fasting blood glucose, glycated hemoglobin, insulin, BMI, and personal history of hypertension, hypercholesterolemia, and diabetes mellitus were all significantly associated with a non-zero calcium score. High-sensitivity CRP, the conventional lipid panel, the ASCVD risk score, and family history of coronary artery disease and diabetes were not. Because the lipid panel was not predictive while the glucose dysmetabolism risk factors were, the evaluation of South Asians should include and focus on pre-diabetic risk factors, such as fasting blood glucose, insulin, and hemoglobin A1c, and measurements of obesity.
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