Adrian Kahn MD, PhD , Gabriela Luque BSc , Eduardo Cuestas MD, PhD , Ana Basquiera MD, PhD , Brenda Ricchi BSc , Klaus Schmitz-Abe PhD , Louis-Marie Charbonnier MD , Mehdi Benamar PhD , Ruben Dario Motrich PhD , Talal A. Chatila MD, PhD , Virginia E. Rivero PhD
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A genetic cause can be identified only in approximately 30% of patients.</p></div><div><h3>Objective</h3><p>We sought to develop a mortality predictive score on the basis of the immunophenotypes and genotypes of patients with CVID.</p></div><div><h3>Methods</h3><p>Twenty-one patients diagnosed with CVID in Córdoba, Argentina, were analyzed for clinical and laboratory data. Immunophenotyping was done by flow cytometry. CVID-associated mutations were identified by whole-exome sequencing.</p></div><div><h3>Results</h3><p>Alive (15) and deceased (6) patients were compared. Univariate analysis showed significant differences in CD4<sup>+</sup> T cells (<em>P</em> = .002), natural killer (NK) cells (<em>P</em> = .001), and memory switched B cells (<em>P</em> = .001) between groups. Logistic regression analysis showed a negative correlation between CD4<sup>+</sup>, NK, and memory switched B<em>-</em>cell counts and probability of survival over a 10-year period (CD4<sup>+</sup> T cells: odds ratio [OR], 1.01; 95% CI, 1.001-1.020; NK cells: OR, 1.07; 95% CI, 1.02-1.17; and memory switched B cells: OR, 26.23; 95% CI, 2.06-2651.96). Receiver-operating characteristic curve analysis identified a survival cutoff point for each parameter (CD4<sup>+</sup> T cells: 546 cells/mL; AUC, 0.87; sensitivity, 60%; specificity, 100%; memory switched B cells: 0.84 cells/mL; AUC, 0.92; sensitivity, 100%; specificity, 85%; and NK cells: 45 cells/mL; AUC, 0.92; sensitivity, 83%; specificity, 100%). Genetic analysis on 14 (9 female and 5 male) patients from the cohort revealed mutations associated with inborn errors of immunity in 6 patients.</p></div><div><h3>Conclusions</h3><p>A score to predict mortality is proposed on the basis of CD4<sup>+</sup> T, NK, and memory switched B-cell counts in patients with CVID.</p></div>","PeriodicalId":75041,"journal":{"name":"The journal of allergy and clinical immunology. 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Univariate analysis showed significant differences in CD4<sup>+</sup> T cells (<em>P</em> = .002), natural killer (NK) cells (<em>P</em> = .001), and memory switched B cells (<em>P</em> = .001) between groups. Logistic regression analysis showed a negative correlation between CD4<sup>+</sup>, NK, and memory switched B<em>-</em>cell counts and probability of survival over a 10-year period (CD4<sup>+</sup> T cells: odds ratio [OR], 1.01; 95% CI, 1.001-1.020; NK cells: OR, 1.07; 95% CI, 1.02-1.17; and memory switched B cells: OR, 26.23; 95% CI, 2.06-2651.96). Receiver-operating characteristic curve analysis identified a survival cutoff point for each parameter (CD4<sup>+</sup> T cells: 546 cells/mL; AUC, 0.87; sensitivity, 60%; specificity, 100%; memory switched B cells: 0.84 cells/mL; AUC, 0.92; sensitivity, 100%; specificity, 85%; and NK cells: 45 cells/mL; AUC, 0.92; sensitivity, 83%; specificity, 100%). 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引用次数: 0
摘要
背景常见可变免疫缺陷病(CVID)是先天性免疫错误中最常见的症状综合征。虽然 CVID 免疫病理的几个方面已被阐明,但死亡率的预测因素尚未完全确定。我们试图根据 CVID 患者的免疫表型和基因型制定死亡率预测评分。方法对阿根廷科尔多瓦确诊的 21 名 CVID 患者的临床和实验室数据进行了分析。免疫分型是通过流式细胞术进行的。结果比较了存活患者(15 例)和死亡患者(6 例)。单变量分析显示,不同组间的 CD4+ T 细胞(P = .002)、自然杀伤(NK)细胞(P = .001)和记忆转换 B 细胞(P = .001)存在显著差异。逻辑回归分析表明,CD4+、NK 和记忆转换 B 细胞计数与 10 年生存概率呈负相关(CD4+ T 细胞:几率比 [OR],1.01;95% CI,1.001-1.020;NK 细胞:几率比 [OR],1.07;95% CI,1.001-1.020):OR,1.07;95% CI,1.02-1.17;记忆转换 B 细胞:OR,26.23;95% CI,2.06-2651.96)。接收者工作特征曲线分析确定了每个参数的生存临界点(CD4+ T 细胞:546 个细胞/毫升;AUC,0.87;灵敏度,60%;特异度,100%;记忆转换 B 细胞:0.84 个细胞/毫升;AUC,0.92;灵敏度,100%;特异度,85%;NK 细胞:45 个细胞/毫升;AUC,0.92;灵敏度,83%;特异度,100%)。结论 根据 CD4+ T、NK 和记忆转换 B 细胞计数,提出了预测 CVID 患者死亡率的评分方法。
Immunological biomarkers associated with survival in a cohort of Argentinian patients with common variable immunodeficiency
Background
Common variable immunodeficiency (CVID) is the most common symptomatic syndrome among inborn errors of immunity. Although several aspects of CVID immunopathology have been elucidated, predictive factors for mortality are incompletely defined. A genetic cause can be identified only in approximately 30% of patients.
Objective
We sought to develop a mortality predictive score on the basis of the immunophenotypes and genotypes of patients with CVID.
Methods
Twenty-one patients diagnosed with CVID in Córdoba, Argentina, were analyzed for clinical and laboratory data. Immunophenotyping was done by flow cytometry. CVID-associated mutations were identified by whole-exome sequencing.
Results
Alive (15) and deceased (6) patients were compared. Univariate analysis showed significant differences in CD4+ T cells (P = .002), natural killer (NK) cells (P = .001), and memory switched B cells (P = .001) between groups. Logistic regression analysis showed a negative correlation between CD4+, NK, and memory switched B-cell counts and probability of survival over a 10-year period (CD4+ T cells: odds ratio [OR], 1.01; 95% CI, 1.001-1.020; NK cells: OR, 1.07; 95% CI, 1.02-1.17; and memory switched B cells: OR, 26.23; 95% CI, 2.06-2651.96). Receiver-operating characteristic curve analysis identified a survival cutoff point for each parameter (CD4+ T cells: 546 cells/mL; AUC, 0.87; sensitivity, 60%; specificity, 100%; memory switched B cells: 0.84 cells/mL; AUC, 0.92; sensitivity, 100%; specificity, 85%; and NK cells: 45 cells/mL; AUC, 0.92; sensitivity, 83%; specificity, 100%). Genetic analysis on 14 (9 female and 5 male) patients from the cohort revealed mutations associated with inborn errors of immunity in 6 patients.
Conclusions
A score to predict mortality is proposed on the basis of CD4+ T, NK, and memory switched B-cell counts in patients with CVID.