通过整合超出癌症阶段的因素来改善默克尔细胞癌复发风险估计:一个多变量模型和基于网络的计算器
Aubriana M McEvoy1, Daniel S Hippe2, Kristina Lachance3
1Department of Dermatology, University of Washington, Seattle, Washington; Division of Dermatology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri.
Journal of the American Academy of Dermatology
|November 20, 2023
概括
默克尔细胞癌 (MCC) 的复发是常见的. 一个新的模型整合了阶段,免疫抑制,性别和原发性瘤状况,可以比单独的阶段更好地预测风险,有助于患者监测.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 生物统计学 生物统计学
背景情况:
- 默克尔细胞癌 (MCC) 的复发率很高,影响到40%的患者.
- 复发风险受癌症阶段以外的因素的影响,包括患者的性别,免疫抑制,原发性瘤状况,年龄,瘤部位和诊断后的时间.
研究的目的:
- 开发一个多变量模型来预测MCC复发风险.
- 创建一个基于网络的计算器,用于可访问的风险评估,改进仅基于阶段的预测.
主要方法:
- 采用了与之竞争的风险回归模型,使用了前队列中618名患者的数据.
- 该模型结合了美国癌症联合委员会 (American Joint Committee on Cancer) 的癌症阶段以及其他已识别的风险因素.
主要成果:
- MCC复发的关键预测因素包括AJCC阶段,免疫抑制,男性性别和未知的原发性瘤状况.
- 多变量模型显示出更好的预后准确性 (仅仅阶段的一致性指数为0.70而不是0.66),并且可以将5年风险估计变化高达四倍.
结论:
- 准确的默克尔细胞癌复发风险预测需要整合临床阶段以外的多个因素.
- 结合自诊断以来的时间的在线计算器为优化患者监测策略提供了改进的数据.
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