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Ratio of lymphocyte to monocyte area under the curve as a novel predictive factor for severe infection in multiple sclerosis
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 warrant...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9972680/ https://www.ncbi.nlm.nih.gov/pubmed/36865535 http://dx.doi.org/10.3389/fimmu.2023.1133444 |
Sumario: | 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, p = 0.010) and lower ratio of L_AUC/t to M_AUC/t (OR 0.766, 95%CI 0.591–0.993, p = 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. |
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