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ORIGINAL RESEARCH article

Front. Immunol.
Sec. Viral Immunology
Volume 15 - 2024 | doi: 10.3389/fimmu.2024.1503118

A predictive model for Epstein-Barr virus-associated hemophagocytic lymphohistiocytosis Running head: A predictive model for EBV-HLH

Provisionally accepted
Rui Huang Rui Huang 1,2*Dan Wu Dan Wu 1,2*Ling Wang Ling Wang 1,2*Ping Liu Ping Liu 1,2*Xiaoru Zhu Xiaoru Zhu 1,2*Leqiu Huang Leqiu Huang 1,2*Mengmeng Chen Mengmeng Chen 1,2*Xin Lv Xin Lv 1,2*
  • 1 Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, Shandong Province, China
  • 2 Clinical Laboratory, Jinan Children's Hospital, Jinan, China

The final, formatted version of the article will be published soon.

    Background: Epstein-Barr virus-associated hemophagocytic lymphohistiocytosis (EBV-HLH) is a severe hyperinflammatory disorder induced by overactivation of macrophages and T cells. This study aims to identify the risk factors for the progression from infectious mononucleosis (EBV-IM) to EBV-HLH, by analyzing the laboratory parameters of patients with EBV-IM and EBV-HLH and constructing a clinical prediction model. The outcome of this study carries important clinical value for early diagnosis and treatment of EBV-HLH. Methods: A retrospective analysis was conducted on 60 patients diagnosed with EBV-HLH and 221 patients diagnosed with EBV-IM at our hospital between November 2018 and January 2024. Participants were randomly assigned to derivation and internal validation cohorts in a 7:3 ratio. LASSO regression and logistic regression analyses were employed to identify risk factors and construct the nomogram. Results: Ferritin (OR, 213.139; 95% CI, 8.604-5279.703; P=0.001), CD3 - CD16 + CD56 + % (OR, 0.011; 95% CI, 0-0.467; P=0.011), anti-EBV-NA-IgG (OR, 57.370; 95%CI, 2.976-1106.049; P=0.007), IL-6 (OR, 71.505; 95%CI, 2.118-2414.288; P=0.017), IL-10 (OR, 213.139; 95% CI, 8.604-5279.703; P=0.001) were identified as independent predictors of EBV-HLH. The prediction model demonstrated excellent discriminatory capability evidenced by an AUC of 0.997 (95% CI,0.993-1.000). When visualized using a nomogram, the ROC curves for the derivation and validation cohorts exhibited AUCs of 0.997 and 0.993, respectively. These results suggested that the model was highly stable and accurate. Furthermore, calibration curves and clinical decision curves indicated that the model possessed good calibration and offered significant clinical benefits. Conclusions: The nomogram, which was based on these five predictors, exhibited robust predictive value and stability, thereby can be used to aid clinicians in the early detection of EBV-HLH.

    Keywords: Epstein-Barr Virus Infections, Lymphohistiocytosis, Hemophagocytic, Infectious Mononucleosis, Pediatrics, Nomograms

    Received: 28 Sep 2024; Accepted: 20 Nov 2024.

    Copyright: © 2024 Huang, Wu, Wang, Liu, Zhu, Huang, Chen and Lv. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Rui Huang, Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, Shandong Province, China
    Dan Wu, Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, Shandong Province, China
    Ling Wang, Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, Shandong Province, China
    Ping Liu, Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, Shandong Province, China
    Xiaoru Zhu, Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, Shandong Province, China
    Leqiu Huang, Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, Shandong Province, China
    Mengmeng Chen, Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, Shandong Province, China
    Xin Lv, Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, Shandong Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.