Elkefi Safa, Choudhury Avishek
School of Nursing, Columbia University, New York, NY, USA.
Department of Industrial and Management Systems Engineering, West Virginia University, Morgantown, WV, USA.
J Cancer Educ. 2025 Feb 3. doi: 10.1007/s13187-025-02570-w.
This study aims to explore disparities in cancer treatment decision-making and the factors associated with the decision to pursue treatment. We used Behavioral Risk Factor Surveillance System (BRFSS) data collected between 2017 and 2022. We employed the PRECEDE-PROCEED model to guide our analysis of factors associated with treatment decisions. Descriptive statistics and multivariable logistic regression analysis were conducted to assess the association between treatment decision-making and the predisposing, enabling, and reinforcing factors (following the PRECEDE-PROCEED model). All analyses were weighted and adjusted for the demographic characteristics of the participants. Our sample included N = 19,388 cancer patients, 20.98% of whom refused treatment. American Indians, younger adults, and breast cancer patients were more likely to decide to go for treatment. Patients who had private insurance (OR = 1.25, P = .037) and those who did not have problems affording care (OR = 1.22, P = .02) were more likely to decide to get treatment. The more patients had regular doctors, the more they decided to continue to pursue treatment for cancer (Only one doctor: OR = 1.20, P = .042; More than one: OR = 1.28, P = .007). Finally, the more days patients experienced a bad health situation, the more they decided to have cancer treatment (for 14 + days with bad health: OR = 1.20, P < .001). The results suggest the need for enhanced patient education to improve cancer treatment adherence and informed decision-making. It highlights the importance of culturally tailored educational programs, age-related concerns, addressing financial barriers, and emphasizing the importance of regular healthcare visits for cancer patients.
本研究旨在探讨癌症治疗决策中的差异以及与寻求治疗决策相关的因素。我们使用了2017年至2022年期间收集的行为风险因素监测系统（BRFSS）数据。我们采用了PRECEDE-PROCEED模型来指导我们对与治疗决策相关因素的分析。进行了描述性统计和多变量逻辑回归分析，以评估治疗决策与 predisposing、 enabling和reinforcing因素（遵循PRECEDE-PROCEED模型）之间的关联。所有分析都进行了加权，并针对参与者的人口统计学特征进行了调整。我们的样本包括N = 19388名癌症患者，其中20.98%的患者拒绝治疗。美国印第安人、年轻人和乳腺癌患者更有可能决定接受治疗。拥有私人保险的患者（OR = 1.25，P = 0.037）和那些没有支付医疗费用问题的患者（OR = 1.22，P = 0.02）更有可能决定接受治疗。患者拥有的常规医生越多，他们就越有可能决定继续接受癌症治疗（只有一名医生：OR = 1.20，P = 0.042；不止一名医生：OR = 1.28，P = 0.007）。最后，患者经历健康状况不佳的天数越多，他们就越有可能决定接受癌症治疗（健康状况不佳14天及以上：OR = 1.20，P < 0.001）。结果表明需要加强患者教育，以提高癌症治疗的依从性和知情决策。它强调了文化定制教育项目、与年龄相关的问题、解决经济障碍以及强调癌症患者定期就医的重要性。
