预测消化系统瘤患者的自杀风险:一项回顾性队列研究
Weibo Li1, Longjiang Chen2, Wei Wang3
1Zhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Wuhan, China.
Surgery
|January 8, 2025
概括
在消化系统瘤患者中确定了自杀风险因素. 开发了一种预测模型,以帮助临床决策和对这一弱势群体进行干预.
科学领域:
- 在瘤学瘤学.
- 精神病学是一个精神病学.
- 公共卫生 公共卫生
背景情况:
- 自杀是患有消化系统瘤的患者的一个担忧,但研究是有限的.
- 这项研究解决了更好地理解和预测这一群体中自杀风险的需要.
研究的目的:
- 为了确定影响消化系统瘤患者自杀的因素.
- 开发一种临床上适用的自杀风险预测模型,用于这个患者群体.
- 为临床干预提供参考.
主要方法:
- 利用了来自监测,流行病学和最终结果 (SEER) 数据库的173,804名被诊断为消化系统瘤的患者 (1998-2015) 的数据.
- 采用拉索和后勤回归来识别自杀预测因子,可视化使用名图.
- 通过ROC曲线,校准和决策曲线分析评估了诺莫格拉姆的准确性和临床实用性.
主要成果:
- 确定年龄,性别,瘤等级,分期,手术,化疗,婚姻状况和居住地作为独立的自杀预测因素.
- 开发了一个名图,AUC为0.78,显示出高预测准确度.
- 通过校准和决策曲线分析验证了nomogram的临床适用性.
结论:
- 确定了影响消化系统瘤患者自杀的关键因素.
- 开发了一个强大的预测模型来指导临床决策和干预.
更多相关视频
03:05Establishment and Evaluation of a Risk Prediction Model for Pathological Escalation of Gastric Low-Grade Intraepithelial Neoplasia
Published on: February 16, 2024
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
相关概念视频
01:17Assessment of the Gastrointestinal System I: Subjective Data
143
Assessing the gastrointestinal (GI) system is a complex process that begins with collecting subjective data. This data, collected through patient interviews, provides crucial insights into the patient's health history, perception patterns, and lifestyle habits, all contributing significantly to GI health.
Health History
The initial step in assessing the GI system is obtaining a comprehensive health history. This includes inquiring about the patient's history or presence of problems...
Health History
The initial step in assessing the GI system is obtaining a comprehensive health history. This includes inquiring about the patient's history or presence of problems...
143
01:21Cancer Survival Analysis
328
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
328