一种新的诺莫图谱,可以预测乳腺癌患者的病理完整反应,并识别可能放弃手术的候选人:一项大型队列研究
Kaining Ye1, Xuehong Liao2, Weiping Yang1
1Department of Pathology, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China.
Cancer medicine
|November 8, 2025
概括
这项研究开发了一种名谱,用于预测乳腺癌 (BC) 患者在新辅助疗法 (NAT) 后的病理完整反应 (pCR). 该工具有助于识别可能是非手术治疗方法的候选患者.
科学领域:
- 在瘤学瘤学.
- 医学统计 医学统计
- 临床研究 临床研究
背景情况:
- 新辅助疗法 (NAT) 是乳腺癌 (BC) 的标准治疗方法.
- 预测病理完整反应 (pCR) 对于治疗优化至关重要.
- 确定适合非手术治疗的患者可以改善治疗结果并减少治疗负担.
研究的目的:
- 开发和验证一个预测BC患者在NAT后BC患者的pCR的nomogram.
- 确定潜在符合非手术治疗条件的患者子组.
- 帮助制定针对乳腺癌的个性化治疗策略.
主要方法:
- 利用了SEER数据库 (2010-2015年),包括4402名BC患者.
- 外部验证了该模型,其中包括来自单一医院的339名BC患者.
- 使用后勤回归和倾向得分匹配 (PSM) 进行可靠的分析.
主要成果:
- 确定了PCR的关键预测因素:年龄,婚姻状况,T/N阶段,等级,HR/HER2状态和化疗.
- 获得的AUC为0.756 (训练),0.717 (内部) 和0.744 (外部) 的pCR预测.
- 将非手术患者分层分为风险组,具有明显的5年整体存活率 (OS),在PSM后显示出显著的差异.
结论:
- 在乳腺癌患者中成功建立了用于预测pCR的验证名录.
- 诺米图可以对患者进行分层,表明得分较高的个体是非手术治疗的潜在候选人.
- 进一步的研究是有必要的,以探索基于nomogram分数的非手术管理.
更多相关视频
相关概念视频
Dosage Regimen Designs: Nomograms and Tabulations
166
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...
166
Cancer Survival Analysis
634
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...
634
Kaplan-Meier Approach
547
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
547


