Enhancing diagnostic precision in EBV-related HLH: a multifaceted approach using 18F-FDG PET/CT and nomogram integration.

IF 3.5 2区 医学 Q2 ONCOLOGY
Xu Yang, Xia Lu, Lijuan Feng, Wei Wang, Ying Kan, Shuxin Zhang, Xiang Li, Jigang Yang
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引用次数: 0

Abstract

Background: The hyperinflammatory condition and lymphoproliferation due to Epstein-Barr virus (EBV)-associated hemophagocytic lymphohistiocytosis (HLH) affect the detection of lymphomas by 18F-FDG PET/CT. We aimed to improve the diagnostic capabilities of 18F-FDG PET/CT by combining laboratory parameters.

Methods: This retrospective study involved 46 patients diagnosed with EBV-positive HLH, who underwent 18F-FDG PET/CT before beginning chemotherapy within a 4-year timeframe. These patients were categorized into two groups: EBV-associated HLH (EBV-HLH) (n = 31) and EBV-positive lymphoma-associated HLH (EBV + LA-HLH) (n = 15). We employed multivariable logistic regression and regression tree analysis to develop diagnostic models and assessed their efficacy in diagnosis and prognosis.

Results: A nomogram combining the SUVmax ratio, copies of plasma EBV-DNA, and IFN-γ reached 100% sensitivity and 81.8% specificity, with an AUC of 0.926 (95%CI, 0.779-0.988). Importantly, this nomogram also demonstrated predictive power for mortality in EBV-HLH patients, with a hazard ratio of 4.2 (95%CI, 1.1-16.5). The high-risk EBV-HLH patients identified by the nomogram had a similarly unfavorable prognosis as patients with lymphoma.

Conclusions: The study found that while 18F-FDG PET/CT alone has limitations in differentiating between lymphoma and EBV-HLH in patients with active EBV infection, the integration of a nomogram significantly improves the diagnostic accuracy and also exhibits a strong association with prognostic outcomes.

提高 EBV 相关 HLH 的诊断精确度:使用 18F-FDG PET/CT 和提名图整合的多元方法。
背景:爱泼斯坦-巴氏病毒(EBV)相关性嗜血细胞淋巴组织细胞增多症(HLH)导致的高炎症状态和淋巴细胞增生影响了18F-FDG PET/CT对淋巴瘤的检测。我们旨在通过结合实验室参数来提高 18F-FDG PET/CT 的诊断能力:这项回顾性研究涉及 46 例确诊为 EBV 阳性 HLH 的患者,他们在 4 年内开始化疗前接受了 18F-FDG PET/CT 检查。这些患者被分为两组:EBV相关性HLH(EBV-HLH)(n = 31)和EBV阳性淋巴瘤相关性HLH(EBV + LA-HLH)(n = 15)。我们采用多变量逻辑回归和回归树分析建立了诊断模型,并评估了这些模型在诊断和预后方面的有效性:结果:结合 SUVmax 比值、血浆 EBV-DNA 拷贝数和 IFN-γ 的提名图灵敏度为 100%,特异度为 81.8%,AUC 为 0.926(95%CI,0.779-0.988)。重要的是,该提名图还能预测 EBV-HLH 患者的死亡率,危险比为 4.2(95%CI,1.1-16.5)。该提名图确定的高危 EBV-HLH 患者的预后与淋巴瘤患者相似:研究发现,虽然单独使用 18F-FDG PET/CT 对活动性 EBV 感染患者区分淋巴瘤和 EBV-HLH 有一定的局限性,但结合提名图能显著提高诊断的准确性,而且与预后结果有密切关系。
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来源期刊
Cancer Imaging
Cancer Imaging ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
7.00
自引率
0.00%
发文量
66
审稿时长
>12 weeks
期刊介绍: Cancer Imaging is an open access, peer-reviewed journal publishing original articles, reviews and editorials written by expert international radiologists working in oncology. The journal encompasses CT, MR, PET, ultrasound, radionuclide and multimodal imaging in all kinds of malignant tumours, plus new developments, techniques and innovations. Topics of interest include: Breast Imaging Chest Complications of treatment Ear, Nose & Throat Gastrointestinal Hepatobiliary & Pancreatic Imaging biomarkers Interventional Lymphoma Measurement of tumour response Molecular functional imaging Musculoskeletal Neuro oncology Nuclear Medicine Paediatric.
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