Veda N Giri1,2, Ayako Shimada3, Amy E Leader2. 1. Departments of Medical Oncology, Cancer Biology, and Urology, Cancer Risk Assessment and Clinical Cancer Genetics, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA. 2. Division of Population Science, Department of Medical Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA. 3. Division of Biostatistics, Department of Pharmacology and Experimental Therapeutics, Thomas Jefferson University, Philadelphia, PA.
Abstract
Racial and ethnic disparities in genetic awareness (GA) can diminish the impact of personalized cancer treatment and risk assessment. We assessed factors predictive of GA in a diverse population-based sample to inform awareness strategies and reduce disparities in genetic testing. METHODS: A cross-sectional study was conducted from July 2019 to August 2019, with the survey e-mailed to 7,575 adult residents in southeastern Pennsylvania and New Jersey. Constructs from National Cancer Institute Health Information and National Trends Survey assessed cancer attitudes or beliefs, health literacy, and numeracy. Characteristics were summarized with mean ± standard deviation for numeric variables and frequency counts and percentages for categorical variables. Comparison of factors by race or ethnicity (non-Hispanic White and non-Hispanic Black) and sex was conducted by t-tests, chi-square, or Fisher's exact tests. Multivariate logistic regression models were conducted to identify factors independently predictive of GA. RESULTS: Of 1,557 respondents, data from 940 respondents (the mean age was 45 ± 16.2 years, 35.5% males, and 23% non-Hispanic Blacks) were analyzed. Factors associated with higher GA included female gender (P < .001), non-Hispanic White (P < .001), college education (P < .001), middle-higher income (P < .001), stronger belief in genetic basis of cancer (P < .001), lower cancer fatalism (P = .004), motivation for cancer information (P < .001), and higher numeracy (P = .002). On multivariate analysis, college education (odds ratio [OR] 1.79; 95% CI, 1.22 to 2.63), higher motivation for cancer information (OR 1.56; 95% CI, 1.17 to 2.09), stronger belief in genetics of cancer (OR 2.21; 95% CI, 1.48 to 3.30), and higher medical literacy (OR 2.21; 95% CI, 1.34 to 3.65) predicted greater GA. CONCLUSION: This population-based study conducted in the precision medicine era identified novel modifiable factors, importantly perceptions of cancer genetics and medical literacy, as predictive of GA, which informs strategies to promote equitable engagement in genetically based cancer care.
Racial and ethnic disparities in genetic awareness (GA) can diminish the impact of personalized cancer treatment and risk assessment. We assessed factors predictive of GA in a diverse population-based sample to inform awareness strategies and reduce disparities in genetic testing. METHODS: A cross-sectional study was conducted from July 2019 to August 2019, with the survey e-mailed to 7,575 adult residents in southeastern Pennsylvania and New Jersey. Constructs from National Cancer Institute Health Information and National Trends Survey assessed cancer attitudes or beliefs, health literacy, and numeracy. Characteristics were summarized with mean ± standard deviation for numeric variables and frequency counts and percentages for categorical variables. Comparison of factors by race or ethnicity (non-Hispanic White and non-Hispanic Black) and sex was conducted by t-tests, chi-square, or Fisher's exact tests. Multivariate logistic regression models were conducted to identify factors independently predictive of GA. RESULTS: Of 1,557 respondents, data from 940 respondents (the mean age was 45 ± 16.2 years, 35.5% males, and 23% non-Hispanic Blacks) were analyzed. Factors associated with higher GA included female gender (P < .001), non-Hispanic White (P < .001), college education (P < .001), middle-higher income (P < .001), stronger belief in genetic basis of cancer (P < .001), lower cancer fatalism (P = .004), motivation for cancer information (P < .001), and higher numeracy (P = .002). On multivariate analysis, college education (odds ratio [OR] 1.79; 95% CI, 1.22 to 2.63), higher motivation for cancer information (OR 1.56; 95% CI, 1.17 to 2.09), stronger belief in genetics of cancer (OR 2.21; 95% CI, 1.48 to 3.30), and higher medical literacy (OR 2.21; 95% CI, 1.34 to 3.65) predicted greater GA. CONCLUSION: This population-based study conducted in the precision medicine era identified novel modifiable factors, importantly perceptions of cancer genetics and medical literacy, as predictive of GA, which informs strategies to promote equitable engagement in genetically based cancer care.
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