开发和验证Nomograms来预测初级上腺淋巴瘤的存活率:一个基于人口的回顾性研究
Shiwei Sun1, Yue Wang1, Wei Yao1
1Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, 030032, China.
Scientific reports
|September 2, 2023
概括
研究人员开发了新的预测模型,以评估原发性上腺淋巴瘤 (PAL) 患者的生存率. 这些模型有助于预测整体生存率 (OS) 和疾病特异性生存率 (DSS),有助于治疗选择和预后.
科学领域:
- 在瘤学瘤学.
- 医学统计 医学统计
背景情况:
- 初级上腺淋巴瘤 (PAL) 的准确预后至关重要,但缺乏有效的预测模型.
- 现有的方法难以可靠地评估PAL患者的整体存活率 (OS) 和疾病特异性存活率 (DSS).
研究的目的:
- 在PAL患者中开发和验证OS和DSS的稳定和有效的预测模型.
- 确定PAL中生存的关键影响因素.
主要方法:
- 利用了来自SEER计划的5448名上腺质量患者的数据.
- 采用最小绝对收缩和选择操作员回归 (LASSO) 和精细和灰色模型 (FGM) 来选择影响因素.
- 使用接收机运行特征 (ROC) 曲线和启动方法构建并验证它们的nomograms.
主要成果:
- 开发了三个不同的生存预测模型:OS,DSS和FGS (DSS的FGM).
- 拉索和FGM确定了PAL生存的独立影响因素.
- 经过验证的模型显示出良好的区分和一致性,而FGS模型显示出更高的短期准确性.
结论:
- 开发的模型为预测PAL患者的OS和DSS提供了有效的工具.
- 这些模型可以帮助临床医生选择PAL的治疗方式和生存评估.
- 在PAL中,FGS模型为短期生存预测提供了更高的准确性.
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