基于临床变量的诺米图的应用,用于预测乳腺恶性乳腺瘤的整体存活率
Wei Li1, Kun Fang2, Jiaren Chen1
1Department of Breast and Thyroid Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China.
Frontiers in genetics
|June 16, 2023
概括
这项研究确定了乳腺恶性乳腺瘤 (PTs) 的关键预后因素. 一种名谱模型准确地预测了生存率,有助于为乳腺PT患者提供个性化治疗.
科学领域:
- 在瘤学瘤学.
- 手术病理学手术病理学
- 生物统计学 生物统计学
背景情况:
- 乳腺的恶性乳腺瘤 (PTs) 是罕见的,需要确定预后因素.
- 准确的生存预测对于有效的患者管理至关重要.
研究的目的:
- 探索恶性乳腺PT的预后风险因素.
- 开发和验证这些患者的生存预测模型.
主要方法:
- 使用了监测,流行病学和最终结果 (SEER) 数据库 (2004-2015).
- 采用考克斯回归分析来确定独立的风险因素.
- 使用培训和验证队列构建并验证了一个名ogram预测模型.
主要成果:
- 确定年龄,瘤大小,阶段,淋巴结转移,远程转移和等级作为独立的风险因素.
- 诺米图表显示出良好的预测性能,C指数为0.845 (训练) 和0.784 (验证).
- 校准曲线和决策曲线分析证实了名图的预测准确性.
结论:
- 开发的诺莫格拉姆模型有效地预测了恶性乳腺PT患者的生存率.
- 这种工具可以帮助个性化临床管理和治疗策略.
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