Surgery Service, General University Hospital of Elda, Elda, Alicante, Spain.
Department of Clinical Medicine, Miguel Hernández University, San Juan de Alicante, Alicante, Spain.
Sci Rep. 2017 Mar 24;7(1):415. doi: 10.1038/s41598-017-00536-7.
Although predictive models exist for mortality in breast cancer (BC) (generally all cause-mortality), they are not applicable to all patients and their statistical methodology is not the most powerful to develop a predictive model. Consequently, we developed a predictive model specific for BC mortality at 5 and 10 years resolving the above issues. This cohort study included 287 patients diagnosed with BC in a Spanish region in 2003-2016.
time-to-BC death. Secondary variables: age, personal history of breast surgery, personal history of any cancer/BC, premenopause, postmenopause, grade, estrogen receptor, progesterone receptor, c-erbB2, TNM stage, multicentricity/multifocality, diagnosis and treatment. A points system was constructed to predict BC mortality at 5 and 10 years. The model was internally validated by bootstrapping. The points system was integrated into a mobile application for Android. Mean follow-up was 8.6 ± 3.5 years and 55 patients died of BC. The points system included age, personal history of BC, grade, TNM stage and multicentricity. Validation was satisfactory, in both discrimination and calibration. In conclusion, we constructed and internally validated a scoring system for predicting BC mortality at 5 and 10 years. External validation studies are needed for its use in other geographical areas.
虽然存在预测乳腺癌（BC）死亡率的模型（通常为全因死亡率），但它们并不适用于所有患者，并且其统计方法也不是开发预测模型的最有效方法。因此，我们开发了一种针对 BC 5 年和 10 年死亡率的预测模型，解决了上述问题。这项队列研究纳入了 2003 年至 2016 年在西班牙某地区诊断为 BC 的 287 名患者。
BC 死亡时间。次要变量：年龄、个人 BC 手术史、任何癌症/BC 个人史、绝经前、绝经后、分级、雌激素受体、孕激素受体、c-erbB2、TNM 分期、多灶性/多中心性、诊断和治疗。构建了一个预测 5 年和 10 年 BC 死亡率的评分系统。通过自举法对模型进行内部验证。该评分系统被集成到一个用于 Android 的移动应用程序中。平均随访时间为 8.6±3.5 年，有 55 名患者死于 BC。评分系统包括年龄、BC 个人史、分级、TNM 分期和多灶性。验证结果在判别和校准方面均令人满意。总之，我们构建并内部验证了一种预测 5 年和 10 年 BC 死亡率的评分系统。需要进行外部验证研究，以将其应用于其他地理区域。
