基于乳腺癌的临床指标,开发和验证一个预后性名录
Mengni Wu1, Xianqiu Xiao1, Fang Li1
1Department of Thyroid and Breast Surgery, The 904th Hospital of the Joint Logistics Support Force of the Chinese People's Liberation Army, Wuxi, China.
Gland surgery
|March 11, 2026
概括
一个新的名图可以使用常见的临床因素,如高血压和AJCC阶段来预测乳腺癌的生存率. 这种可访问的工具有助于个性化预后评估和乳腺癌患者的临床决策.
科学领域:
- 在瘤学瘤学.
- 生物统计学 生物统计学
背景情况:
- 乳腺癌 (BC) 是一种普遍存在的全球性恶性瘤,结果各不相同.
- 目前的预后模型通常需要专门的生物标志物,限制了它们的常规临床使用.
- 个性化预后评估对于有效的乳腺癌管理至关重要.
研究的目的:
- 开发和内部验证用于预测乳腺癌患者的整体存活率 (OS) 的预后名录.
- 利用现有的临床指标进行预后评估.
- 为常规临床实践创建一个可访问的工具.
主要方法:
- 对217名乳腺癌患者的数据进行了回顾性分析.
- 使用LASSO回归用于预后因素选择.
- 采用单变量和多变量考克斯回归,并使用C指数和AUC进行名录构造和验证.
主要成果:
- 确定的高血压,AJCC阶段,转移,Ki-67,内分泌疗法和红细胞计数作为独立的预后因素.
- 该名ogram表现出极好的歧视,其C指数为0.898.8.
- 在训练 (0.89-0.93) 和验证 (0.85-0.98) 队列中,高AUC值显示出强大的预测准确性.
结论:
- 基于可访问的临床指标开发并验证了一种基于可访问的临床指标的新型名谱,用于预测乳腺癌总体存活率.
- 诺米图显示了临床决策和患者结果评估的重大潜力.
- 这种可访问的模型可以在常规乳腺癌护理中增强个性化预后评估.
更多相关视频
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
979
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
842
相关概念视频
01:21Cancer Survival Analysis
808
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...
808
01:23Dosage Regimen Designs: Nomograms and Tabulations
274
Nomograms and tabulations are vital tools used by clinicians to design accurate and individualized dosage regimens. These instruments provide a straightforward method for adjusting dosages based on individual patient characteristics, including age, weight, and physiological condition. The foundation of a drug's nomogram is population pharmacokinetic data collected and analyzed using specific models. This data simplifies complex equations, presenting them diagrammatically or tabularly for easy...
274
01:25Formulating and Validating Nursing Diagnosis II
4.2K
Nursing diagnoses represent a problem validated by major defining characteristics. There are four categories of nursing diagnoses: problem-focused, risk, health promotion or wellness, and syndrome. The anatomy of a nursing diagnosis includes three components: problem statement or diagnostic label, defining characteristics, and related factors.
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
4.2K