组织学等级,瘤宽度和高血压预测儿科肉瘤的早期复发:LASSO规范化微群组研究
Alexander Fiedler1, Mehran Dadras2, Marius Drysch1
1Department of Plastic Surgery, BG University Hospital Bergmannsheil, Ruhr University Bochum, Bürkle-de-la-Camp Platz 1, 44789 Bochum, Germany.
Children (Basel, Switzerland)
|June 26, 2025
概括
用机器学习识别了儿科肉瘤复发的预测因素. 瘤等级,大小,高血压和四肢位置与儿童复发风险增加有关.
科学领域:
- 儿科瘤学 儿科瘤学
- 医疗信息学 医疗信息学
- 机器学习在医学中的应用
背景情况:
- 儿科瘤是多种多样的介质细胞瘤,尽管接受治疗,但其复发率很高.
- 早期复发的有限可靠预测因素阻碍了有效的患者管理.
- 这项研究探讨了预测儿科肉瘤患者第一次瘤复发的临床特征.
研究的目的:
- 确定与儿科肉瘤中第一次瘤复发相关的临床特征.
- 应用适用于低事件设置的机器学习方法.
- 调查传统和新型因素的预测相关性.
主要方法:
- 对23名儿科肉瘤患者进行了回顾性,单中心的队列研究.
- 提取了46个基线变量,包括临床,组织学和并发症数据.
- 用LOOCV开发了一个LASSO规范化的物流回归模型,使用PCA和SHAP值进行分析.
主要成果:
- 确定了四种可变的风险特征:组织学等级,瘤宽度,动脉高血压和四肢局部化.
- 增加瘤等级和宽度显著提高了复发几率 (ORs ~2.0-2.2).
- 高血压和四肢位置也显示出复发率增加 (ORs ~1.7-1.9),与适度的模型歧视力 (AUROC ~0.47).
结论:
- 经典的预后标记 (等级,大小) 仍然与儿科肉瘤复发相关.
- 动脉高血压已经成为一种新的,与复发相关的潜在可修改因素.
- 发现是产生假设的,需要在更大的前性研究中进行验证.
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