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基于UF-5000的新型检测,整合炎症参数,用于尿癌

Kazuhiro Okada¹, Yoshiki Naito², Saori Irie²

¹Department of Clinical Laboratory Medicine, Kurume University Hospital, Kurume, Japan; okada_kazuhiro@kurume-u.ac.jp.

Anticancer research

|August 1, 2025

概括

在UF-5000分析仪.

科学领域:

尿癌 (UC) 研究研究
发展诊断生物标志物的发展.
自动化尿液分析技术

背景情况:

尿道癌 (UC) 是一种常见的膀癌.
目前的尿细胞学对低级UC的敏感性有限.
需要新的诊断标记物来改善UC检测.

研究的目的:

为了评估UF-5000用于UC检测的"Atyp.C"参数的诊断准确性.
评估"Atyp.C"和中性粒细胞与淋巴细胞比率 (NLR) 的联合诊断实用性.
探索用于UC诊断的AI驱动的算法.

主要方法:

分析了159名患者 (57名非侵入性UC,41名侵入性UC,61名非侵入性UC) 的尿样.
使用的UF-5000自动化尿液颗粒分析仪用于"Atyp.C"测量.
雇佣的接收器操作特征 (ROC) 曲线分析和一个集成NLR的AI平台 (DataRobot).

主要成果:

单独的"Atyp.C"显示了侵入性UC的中度准确性 (AUC=0.824),但对于非侵入性UC的准确性较低.
将"Atyp.C"与NLR结合起来显著改善了侵入性UC检测 (AUC=0.892,灵敏度75.0%,特异性100%).
中性粒细胞与淋巴细胞的比率 (NLR) 成为UC检测算法中最有影响力的因素.

结论:

UF-5000的"Atyp.C"参数显示了UC检测的希望.
将UF-5000数据与NLR数据结合起来,可以提高尿癌的诊断准确度.
这种综合方法可能会导致更有效的膀癌查策略.

关键词:

在UF-5000中使用.中性粒细胞与淋巴细胞的比率.尿路细胞癌是什么意思

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