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The Application of Gail Model to Predict the Risk of Developing Breast Cancer among Jordanian Women

机译:Gail模型在约旦女性中预测发育乳腺癌风险的应用

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Background and Objectives. Breast cancer has been the most common cancer affecting women in Jordan. In the process of implementing breast cancer prevention and early detection programs, individualized risk assessment can add to the cost-effectiveness of such interventions. Gail model is a widely used tool to stratify patients into different risk categories. However, concerns about its applicability across different ethnic groups do exist. In this study, we report our experience with the application of a modified version of this model among Jordanian women. Methods. The Gail risk assessment model (RAM) was modified and used to calculate the 5-year and lifetime risk for breast cancer. Patients with known breast cancer were used to test this model. Medical records and hospital database were utilized to collect information on known risk factors. The mean calculated risk score for women tested was 0.65. This number, which corresponds to the Gail original score of 1.66, was used as a cutoff point to categorize patients as high risk. Results. A total of 1786 breast cancer patients with a mean age of 50 (range: 19–93) years were included. The modified version of the Gail RAM was applied on 1213 patients aged 35–59.9 years. The mean estimated risk for developing invasive breast cancer over the following five years was 0.54 (95% CI: 0.52, 0.56), and the lifetime risk was 3.42 (95% CI: 3.30, 3.53). Only 210 (17.3%) women had a risk score 0.65 and thus categorized as high risk. First-degree family history of breast cancer was identified among 120 (57.1%) patients in this high-risk group. Conclusions. Among a group of patients with an established diagnosis of breast cancer, a modified Gail risk assessment model would have been able to stratify only 17% into the high-risk category. The family history of breast cancer contributed the most to the risk score.
机译:背景和目标。乳腺癌一直是影响妇女在约旦的癌症中最常见的癌症。在实施乳腺癌预防和早期检测计划的过程中,个性化风险评估可以增加此类干预措施的成本效益。 Gail模型是一种广泛使用的工具,将患者分成不同的风险类别。但是,对不同族裔群体的适用性确实存在担忧。在这项研究中,我们在约旦女性中举行了这种模型的修改版本的经验。方法。修改了Gail风险评估模型(RAM),用于计算乳腺癌的5年和寿命风险。患有已知乳腺癌的患者用于测试该模型。医疗记录和医院数据库用于收集有关已知风险因素的信息。测试的女性的平均计算风险分数为0.65。该号码对应于Gail原始得分为1.66,用作截止点,以将患者分类为高风险。结果。共有1786名乳腺癌患者,平均年龄为50(范围:19-93)岁。 Gail RAM的修改版应用于35-59.9岁的1213名患者。在以下五年内发生侵入性乳腺癌的平均估计风险为0.54(95%CI:0.52,0.56),寿命风险为3.42(95%CI:3.30,3.53)。只有210名(17.3%)妇女的风险得分> 0.65,因此分类为高风险。在该高风险群体中的120例(57.1%)患者中鉴定了乳腺癌的一级家族史。结论。在一组患有患者诊断的乳腺癌诊断中,改良的鳄碍风险评估模型将能够分层只有17%的高风险类别。乳腺癌的家族史对风险得分贡献了最多。

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