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诺莫格拉姆预测了头部和部皮肤黑色素瘤的预后因素:基于人口的分析

Chenjing Ma¹, Ruihao Qin¹, Yong Cao¹

¹Department of Biostatistics, School of Public Health, Harbin Medical University, Harbin, China.

World neurosurgery

|May 10, 2024

概括

这项研究开发了一种预测头部和部皮肤黑色素瘤 (HNCM) 存活率的诺米图. 该模型准确地预测HNCM患者的整体生存率 (OS) 和疾病特异性生存率 (DSS).

科学领域:

在瘤学瘤学.
皮肤病学皮肤病学
生物统计学生物统计学

背景情况:

头部和部皮肤黑色素瘤 (HNCM) 占新的黑色素瘤诊断的20%.
对HNCM存活的预测模型未得到充分探索.
这项研究解决了在HNCM中可靠的生存预测的需求.

研究的目的:

开发和验证HNCM患者的整体存活率 (OS) 和疾病特异性存活率 (DSS) 的预测性名谱.
确定影响HNCM患者结果的独立预后因素.

主要方法:

从监测,流行病学和最终结果数据库中分析HNCM患者数据 (2004-2014).
整合单变Cox回归,随机生存森林和LASSO回归用于因子识别.
使用已识别的预后因素开发和验证名录.

主要成果:

确定了独立的预后因素:年龄,阶段,,厚度,化疗,淋巴结转移和辐射.
在训练队列中,名图显示出强大的预测性能,C指数为0.824 (DSS) 和0.757 (OS),在验证队列中为0.827 (DSS) 和0.749 (OS).
在两个队列中,对于3年,5年和8年的OS和DSS,曲线下的高面积 (AUC) 表示强大的预测准确性.

结论:

建立并验证了HNCM患者的预测名录.
开发的诺姆图表表现出对患者生存的强大预测性能.
这些工具可以帮助HNCM的临床决策和患者管理.

关键词:

头部和部皮肤黑色素瘤拉索·拉索 (Lasso) 是一个这个名字叫做Nomogram.随机生存森林是随机生存的森林.

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