在接受放射化疗的肺癌患者中预测肺部感染风险的预测性诺米克:发展和绩效评估
1Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430079, Hubei, China.
American journal of cancer research
|March 14, 2025
概括
一种新的诺莫格拉姆模型准确地预测了接受放射化疗的肺癌患者的肺部感染风险. 这种工具有助于临床医生在高风险个体的早期识别和干预.
科学领域:
- 在瘤学瘤学.
- 肺部病理学 肺部病理学
- 医疗信息学 医疗信息学
背景情况:
- 肺部感染是接受放射化疗的肺癌患者的重要并发症.
- 早期识别高风险患者对于及时干预和改善结果至关重要.
研究的目的:
- 开发和验证接受放射化疗的肺癌患者肺部感染风险的准确预测模型.
- 确定与肺部感染相关的关键临床和实验室因素.
主要方法:
- 544名肺癌患者的回顾性分析,对100名患者进行外部验证.
- 机器学习算法 (Lasso,随机森林,XGBoost,SVM) 用于特征选择和模型开发.
- 用ROC曲线,校准曲线和决策曲线分析来评估模型性能.
主要成果:
- 确定了关键预测因素:糖尿病,COPD,化疗强度/周期,抗生素使用,年龄,KPS,SII,PNI和CRP.
- 一个名ogram模型在培训,验证和外部队列中实现了高预测准确性 (AUC 0.889-0.897).
- 该模型表现出强大的分类能力和稳定性.
结论:
- 开发了结合八个关键因素的强大的诺莫格拉姆模型,以预测肺部感染风险.
- 这种工具可以帮助临床医生在肺癌患者的早期风险分层.
- 基于模型预测的及时干预可能会改善患者的治疗结果和生活质量.
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