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基于套索逻辑回归的儿童噬血细胞性淋巴组织细胞增生症的临床特征及预后分析

Clinical characteristics and prognostic analysis of pediatric hemophagocytic lymphohistiocytosis using lasso-logistic regression.

作者信息

Luo Nandu, Yang Guangli, Li Baoli, Zhang Pingping, Ma Jinhua, Chen Yan, Du Zuochen, Huang Pei

机构信息

Department of Pediatrics, Affiliated Hospital of Zunyi Medical University, Zunyi, China.

Guizhou Children's Hospital, Zunyi, China.

出版信息

Ann Hematol. 2024 Dec;103(12):5191-5200. doi: 10.1007/s00277-024-06061-8. Epub 2024 Oct 29.

Abstract

This study aims to evaluate and predict mortality risks among pediatric patients with hemophagocytic lymphohistiocytosis (HLH). We conducted a retrospective analysis of pediatric patients with HLH diagnosed at the Affiliated Hospital of Zunyi Medical University between January 2012 and April 2023. Patients were divided into a death group and a survival group based on their outcomes. Risk factors for mortality were analyzed using a lasso-logistic regression model. This study included 142 pediatric patients with HLH, with a median age of 40.5 (14.75-84) months, of whom 78 (54.93%) were male. The overall mortality rate was 34.51%. Through lasso-logistic regression analysis, five independent prognostic factors were identified: concurrent central nervous system involvement, multiple organ dysfunction syndrome involving three or more organs, platelet count ≤ 42.5 × 10/L, activated partial thromboplastin time ≥ 54.05 s, and the utilization of blood purification in conjunction with the HLH-94/2004 treatment protocol. The predictive value of the lasso-logistic regression model is better than that of the traditional logistic regression model (AUC: 0.906 vs 0.811, P = 0.001). Subsequently, a lasso-logistic regression-based predictive model incorporating these identified risk factors was developed. Our lasso-logistic regression-based prediction model may help to identify high-risk patients with HLH early, thereby enabling the timely initiation of appropriate treatment interventions.

摘要

本研究旨在评估和预测噬血细胞性淋巴组织细胞增生症(HLH)患儿的死亡风险。我们对2012年1月至2023年4月在遵义医科大学附属医院确诊的HLH患儿进行了回顾性分析。根据患儿的结局将其分为死亡组和生存组。使用套索逻辑回归模型分析死亡的危险因素。本研究纳入了142例HLH患儿,中位年龄为40.5(14.75 - 84)个月,其中78例(54.93%)为男性。总死亡率为34.51%。通过套索逻辑回归分析,确定了五个独立的预后因素:并发中枢神经系统受累、涉及三个或更多器官的多器官功能障碍综合征、血小板计数≤42.5×10⁹/L、活化部分凝血活酶时间≥54.05秒以及结合HLH - 94/2004治疗方案使用血液净化。套索逻辑回归模型的预测价值优于传统逻辑回归模型(AUC:0.906对0.811,P = 0.001)。随后,开发了一个基于套索逻辑回归的预测模型,纳入这些确定的危险因素。我们基于套索逻辑回归的预测模型可能有助于早期识别HLH高危患者,从而能够及时启动适当的治疗干预措施。

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