一个模型来识别需要抗病毒治疗的慢性乙型肝炎灰色区域患者:一个多中心的回顾性研究
Xue-Yan Yang1,2,3, Xi-Dong Li4, Bai-Yun Wu1,2
1Department of Hepatology, Qilu Hospital of Shandong University, Jinan, China.
The Journal of infectious diseases
|February 17, 2025
概括
一种新的非侵入性模型有助于识别需要抗病毒治疗 (AVT) 的慢性乙型肝炎灰色区患者. 该工具有助于管理不清楚病期的患者,改善治疗决策.
科学领域:
- 肝病学 肝病学是一种肝病学.
- 病毒学 病毒学
- 临床医学 临床医学
背景情况:
- 慢性乙型肝炎 (CHB) 患者不适合特定的自然史阶段处于"灰色地带",使管理复杂化.
- 对这些灰色区CHB患者的最佳抗病毒疗法 (AVT) 决策仍然不清楚.
研究的目的:
- 开发和验证一种非侵入性预测模型,用于识别需要AVT的灰色区域CHB患者.
主要方法:
- 分析了200名灰色区CHB患者的回顾性数据.
- 患者被分为发展 (n=140) 和验证 (n=60) 队列.
- 回归分析确定了预测AVT需求的nomogram的变量,通过AUC,校准和决策曲线分析进行验证.
主要成果:
- 纳米图包括年龄,氨酸转移酶,淋巴细胞百分比,血小板数和国际正常化比率.
- 该模型表现出良好的区分能力 (AUC=0.755在开发中,0.707在验证中) 和校准.
- 分数>197表示高AVT概率,而分数≤132表示低概率.
结论:
- 开发的诺米图是有希望的非侵入性工具,用于识别需要AVT的灰色区域CHB患者.
- 准确识别这些患者可以指导适当的管理策略.
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