使用数据驱动方法预测结直肠癌手术后的30天,90天和1年的死亡率
Karoline Bendix Bräuner1, Andi Tsouchnika2, Maliha Mashkoor2
1Center for Surgical Science, Zealand University Hospital, Køge, Lykkebækvej 1, 4600, Køge, Denmark. karob@regionsjaelland.dk.
International journal of colorectal disease
|February 29, 2024
概括
用丹麦健康数据库开发了结直肠癌手术死亡风险的预测模型. 所有患者的单一模型的表现优于特定子组的模型,在短期死亡率预测方面表现出很好的准确性.
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:
- 结肠直肠癌手术具有显著的短期死亡风险.
- 准确的风险评估对于患者管理和资源分配至关重要.
- 现有的预测模型可能无法完全捕捉到各种手术场景的复杂性.
研究的目的:
- 开发和验证结直肠癌手术后短期死亡风险的可靠预测模型.
- 用手术前数据评估模型的性能.
- 为了比较统一模型与特定子组模型的有效性.
主要方法:
- 来自丹麦四个健康数据库的统一数据,使用观察医疗结果伙伴关系共同数据模型.
- 开发了30天,90天和1年的死亡率预测模型,使用最小绝对收缩和选择操作员后勤回归.
- 评估的模型歧视 (AUC-ROC,AUC-PR) 和校准 (斜坡,拦截,CAL).
- 在治愈性,息性,选择性和紧急手术子组中评估模型性能.
主要成果:
- 总共有57,521名患者被分析 (51.1%是男性,中位数年龄为72岁).
- 模型表现出强烈的歧视 (AUC-ROC:0.88为30天,0.878为90天,0.861为1年) 和出色的校准.
- 总的死亡率为4.48% (30天),6.64% (90天) 和12.8% (1年).
- 一个单一的队列模型比子组特定的模型表现更好.
结论:
- 成功开发了对结直肠癌手术进行精确校准和高度区分的短期死亡率预测模型.
- 涵盖所有手术类型的统一预测模型优于特定子组的模型.
- 这些模型可以帮助准确地分层分层对接受结直肠癌手术的患者的风险.
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