一个基于深度学习的模型 (DeepMPM) 帮助预测患有恶性多叶半瘤的患者的生存率
Wei Li1, Minghang Zhang1, Siyu Cai2
1Department of Thoracic Surgery, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.
Translational cancer research
|November 16, 2023
概括
一个新的深度学习模型准确地预测了恶性多间皮瘤 (MPM) 患者的存活率. 组合疗法,包括手术,放射治疗和化疗,对这种罕见的癌症显示出最显著的生存益处.
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:
- 恶性多叶层层层瘤 (MPM) 是一种罕见的癌症,治疗选择有限,预后不佳.
- 准确预测MPM患者的生存率对于临床决策至关重要,但目前缺乏可靠的方法.
研究的目的:
- 开发和验证一种基于深度学习的预测模型,用于恶性多间皮瘤患者的生存.
- 确定影响MPM患者生存的关键风险和保护因素.
主要方法:
- 一项基于人口的队列研究,利用监测,流行病学和最终结果 (SEER) 数据库.
- 数据分为培训 (2010-2016) 和测试 (2017-2019) 队列,以开发和验证基于DeepSurv的深度学习模型.
- 考克斯比例风险回归和卡普兰-梅尔曲线用于分析临床特征和确定生存因素.
主要成果:
- 这项研究包括3130例MPM病例. 深度学习模型在训练队列中实现了0.7037的AUC,在测试队列中达到0.7076.
- 已确定的生存风险因素包括年龄较大,男性性别,类甲状腺瘤和晚期 (T4,N2,M1).
- 保护性因素包括表皮层性间皮瘤,手术,放射治疗和化疗. 综合模式治疗,特别是与放射治疗相结合的手术,产生了最长的平均总生存期.
结论:
- 一个深度学习模型可以准确地预测患有恶性多叶膜间皮瘤的患者的生存结果.
- 多模式组合疗法,整合手术,放射治疗和化疗,为MPM患者提供显著的生存益处.
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