基于SEER数据库开发和验证肺癌患者自杀风险的名录图
Wenhui Li1, Hao Lu2, Heyuan Tang3
1Department of Radiation Oncology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Discover oncology
|December 16, 2025
概括
这项研究确定了肺癌患者自杀的关键预测因素,并开发了一种动态的诺米图,用于个性化风险评估. 这种工具有助于在高风险人群中早期识别和预防.
科学领域:
- 在瘤学瘤学.
- 精神病学是一个精神病学.
- 生物统计学 生物统计学
背景情况:
- 肺癌患者面临更高的自杀风险.
- 早期识别有风险的个体对于干预至关重要.
研究的目的:
- 确定肺癌患者自杀的独立预测因素.
- 为预测自杀风险,开发一个动态名录.
- 为高风险人群提供早期识别和预防策略.
主要方法:
- 从SEER数据库 (2004-2015) 中分析了188,147例肺癌病例.
- 多因素考克斯回归分析以确定预测因素.
- 使用培训和验证队伍开发和验证动态名ogram.
- 使用C指数,ROC曲线和校准图表评估模型性能.
主要成果:
- 年龄,种族,性别,年级和婚姻状况被确定为自杀的独立预测因素.
- 开发的名图表在培训和验证集上都表现出可接受的预测准确性.
- 校准图表证实了包含这些因素的诺米图的强大预测准确性.
结论:
- 开发了一种动态的诺姆图,为肺癌患者提供个性化的自杀风险预测.
- 这种工具为早期检测和干预提供了比静态风险尺度更好的替代方案.
- 基于网络的视觉工具可方便实时评估风险,改善以患者为中心的护理和心理结果.
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