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淋巴细胞与单核细胞曲线下面积比值作为多发性硬化症严重感染的新预测因子。

Ratio of lymphocyte to monocyte area under the curve as a novel predictive factor for severe infection in multiple sclerosis.

机构信息

Department of Neurology, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.

Department of Immunology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.

出版信息

Front Immunol. 2023 Feb 14;14:1133444. doi: 10.3389/fimmu.2023.1133444. eCollection 2023.

DOI:10.3389/fimmu.2023.1133444
PMID:36865535
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9972680/
Abstract

BACKGROUND

Individuals with multiple sclerosis (MS) are vulnerable to all types of infection, because MS itself involves immunodeficiency, in addition to involving treatment with immunosuppressants. Simple predictive variables for infection that are easily assessed in daily examinations are warranted. Lymphocyte area under the curve (L_AUC), defined as the sum of serial absolute lymphocyte counts under the lymphocyte count-time curve, has been established as a predictive factor for several infections after allogenic hematopoietic stem cell transplantation. We assessed whether L_AUC could also be a useful factor for predicting severe infection in MS patients.

METHODS

From October 2010 to January 2022, MS patients, diagnosed based on the 2017 McDonald criteria, were retrospectively reviewed. We extracted patients with infection requiring hospitalization (IRH) from medical records and matched with controls in a 1:2 ratio. Variables including clinical severity and laboratory data were compared between the infection group and controls. L_AUC was calculated along with the AUC of total white blood cells (W_AUC), neutrophils (N_AUC), lymphocytes (L_AUC), and monocytes (M_AUC). To correct for different times of blood examination and extract mean values of AUC per time point, we divided the AUC by follow-up duration. For example, in evaluating lymphocyte counts, we defined the ratio of [L_AUC] to [follow-up duration] as [L_AUC/t]. Multivariate regression analysis was conducted to extract predictive factors associated with IRH. Also, discriminative analysis was conducted using candidate variables from multivariate analysis.

RESULTS

The total case-control sample included 177 patients of MS with IRH (n=59) and non-IRH (controls) (n=118). Adjusted odds ratios (OR) for the risk of serious infection in patients with MS with higher baseline expanded disability status scale (EDSS) (OR 1.340, 95% confidence interval [CI] 1.070-1.670, = 0.010) and lower ratio of L_AUC/t to M_AUC/t (OR 0.766, 95%CI 0.591-0.993, = 0.046) were significant. Notably, the kind of treatment, including glucocorticoids (GCs), disease-modifying drugs (DMDs) and other immunosuppressants agents, and dose of GCs were not significantly associated with serious infection after correlated with EDSS and ratio of L_AUC/t to M_AUC/t. In discriminative analysis, sensitivity was 88.1% (95%CI 76.5-94.7%) and specificity was 35.6% (95%CI 27.1-45.0%), using EDSS ≥ 6.0 or ratio of L_AUC/t to M_AUC/t ≤ 3.699, while sensitivity was 55.9% (95%CI 42.5-68.6%) and specificity was 83.9% (95%CI 75.7-89.8%), using both EDSS ≥ 6.0 and ratio of L_AUC/t to M_AUC/t ≤ 3.699.

CONCLUSION

Our study revealed the impact of the ratio L_AUC/t to M_AUC/t as a novel prognostic factor for IRH. Clinicians should pay more attention to laboratory data such as lymphocyte or monocyte counts itself, directly presenting individual immunodeficiency, rather than the kind of drug to prevent infection as a clinical manifestation.

摘要

背景

多发性硬化症(MS)患者易发生各类感染,这不仅与 MS 本身导致的免疫缺陷有关,还与免疫抑制剂的治疗有关。因此,需要寻找简单且易于在日常检查中评估的感染预测变量。淋巴细胞面积下面积(L_AUC),定义为淋巴细胞计数时间曲线下的连续绝对淋巴细胞计数之和,已被确立为异基因造血干细胞移植后多种感染的预测因子。我们评估了 L_AUC 是否也可以成为 MS 患者严重感染的有用预测因子。

方法

从 2010 年 10 月至 2022 年 1 月,回顾性分析了基于 2017 年 McDonald 标准诊断的 MS 患者。我们从病历中提取需要住院治疗的感染(IRH)患者,并按 1:2 的比例与对照组匹配。比较感染组和对照组之间的临床严重程度和实验室数据等变量。计算总白细胞(W_AUC)、中性粒细胞(N_AUC)、淋巴细胞(L_AUC)和单核细胞(M_AUC)的 AUC 以及 L_AUC。为了校正不同时间的血液检查并提取每个时间点的 AUC 平均值,我们将 AUC 除以随访时间。例如,在评估淋巴细胞计数时,我们将 [L_AUC] 与 [随访时间] 的比值定义为 [L_AUC/t]。进行多变量回归分析以提取与 IRH 相关的预测因子。此外,还使用多变量分析中的候选变量进行判别分析。

结果

总病例对照样本包括 177 例 MS 患者,其中 IRH(n=59)和非 IRH(对照组)(n=118)。基线扩展残疾状况量表(EDSS)较高(比值比[OR]1.340,95%置信区间[CI]1.070-1.670, = 0.010)和 L_AUC/t 与 M_AUC/t 的比值较低(OR 0.766,95%CI 0.591-0.993, = 0.046)的 MS 患者发生严重感染的风险更高。值得注意的是,包括糖皮质激素(GCs)、疾病修饰药物(DMDs)和其他免疫抑制剂在内的治疗类型以及 GCs 的剂量与 EDSS 和 L_AUC/t 与 M_AUC/t 的比值相关,但与严重感染无显著相关性。在判别分析中,使用 EDSS≥6.0 或 L_AUC/t 与 M_AUC/t 的比值≤3.699 时,灵敏度为 88.1%(95%CI 76.5-94.7%),特异性为 35.6%(95%CI 27.1-45.0%),而使用 EDSS≥6.0 和 L_AUC/t 与 M_AUC/t 的比值≤3.699 时,灵敏度为 55.9%(95%CI 42.5-68.6%),特异性为 83.9%(95%CI 75.7-89.8%)。

结论

我们的研究揭示了 L_AUC/t 与 M_AUC/t 的比值作为 IRH 的新预后因素的作用。临床医生应更加关注淋巴细胞或单核细胞计数等实验室数据,这些数据直接反映个体免疫缺陷,而不是将药物种类作为感染的临床表现来预防感染。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fa2/9972680/888005996c68/fimmu-14-1133444-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fa2/9972680/751713c6a03c/fimmu-14-1133444-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fa2/9972680/751713c6a03c/fimmu-14-1133444-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fa2/9972680/00e7ef66f432/fimmu-14-1133444-g002.jpg
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