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在早期胃癌中构建和验证基于多变量分析的围神经侵入风险预测模型,以多变量分析为基础
Guangxu Zhu1,2, Shengjie Zhou1,2, Jianjun Qu1,2
1Weifang People's Hospital, Weifang, Shandong, China.
BMC cancer
|January 19, 2026
概括
这项研究确定了年龄,CEA水平,瘤厚度和淋巴血管入侵作为早期胃癌 (EGC) 中围神经入侵 (PNI) 的关键预测因素. 为个性化PNI风险评估开发了一种新型名录,显示出强大的预测准确性.
科学领域:
- 胃肠病学 胃肠病学
- 手术瘤学手术瘤学
- 瘤成像学成像学
背景情况:
- 周围神经侵入 (PNI) 是早期胃癌 (EGC) 的关键预后因素.
- 确定PNI的独立风险因素对于EGC患者的准确风险分层和治疗规划至关重要.
研究的目的:
- 确定早期胃癌 (EGC) 中围神经侵入 (PNI) 的独立风险因素.
- 开发和验证用于预测EGC中的PNI风险的第一个个性化名录.
主要方法:
- 从416名EGC患者的临床病理学数据的回顾性分析.
- 拉索回归和多变量逻辑回归用于识别独立的风险因素.
- 内部验证使用30%的保留集,评估歧视 (AUC),校准和临床实用性 (DCA).
主要成果:
- 年龄,CEA水平,最大瘤厚度和淋巴血管侵入被确定为EGC中PNI的独立风险因素.
- 开发的名图表显示出强大的区分能力 (AUC训练:0.895,AUC验证:0.783) 和良好的校准.
- 决策曲线分析表明,在个性化风险评估中,名谱具有相当大的临床实用性.
结论:
- 年龄,CEA水平,最大瘤厚度和淋巴血管入侵是EGC中PNI的重要独立预测因素.
- 开发的名录图为EGC中个性化PNI风险评估提供了可靠的工具.
- 建议进行进一步的多中心验证,以提高这个名图的临床适用性.
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