Li Xiaotong, Jiang Wencan, Li Guoge, Ding Yaowei, Li Haoran, Sun Jialu, Chen Yuxin, Wang Siqi, Zhang Guojun
Department of Clinical Diagnosis, Laboratory of Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China.
National Engineering Research Centre for Beijing Biochip Technology, Beijing, People's Republic of China.
J Inflamm Res. 2024 Nov 29;17:10065-10078. doi: 10.2147/JIR.S489502. eCollection 2024.
Inflammation and nutritional markers have recently gained recognition for their roles in the fabrication of cognitive control centers demyelinating illnesses. Inflammatory indices such as the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), and systemic inflammatory response index (SIRI), along with nutritional markers like albumin (ALB), hemoglobin (HB), and body mass index (BMI), may predict disease occurrence. However, their potential in evaluating diseases such as multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) remains unexplored.
We retrospectively evaluated 249 NMOSD patients, 244 MS patients, and 249 healthy controls (HC), calculating MLR, NLR, PLR, SII, and SIRI, and measuring ALB, HB, and BMI levels. Logistic regression and ROC curves were used to develop and validate models for diagnosing and differentiating MS and NMOSD. Further, 35 MS patients, 38 NMOSD patients, and 85 matched HC were recruited for validation, and marker changes were monitored over six months.
Comparing MS and NMOSD groups with HC, MLR, NLR, SII, and SIRI were significantly greater, while ALB levels were lower (P<0.05). NMOSD patients exhibited higher MLR, NLR, SII, and SIRI, and lower HB and ALB levels contrasted with MS patients (P<0.05). These markers correlated negatively with total T lymphocytes and positively with C-reactive protein, the Expanded Disability Status Scale (EDSS), and MRI T2 lesion count. Following remission, NLR, SII, and SIRI decreased, while ALB increased over six months (P<0.05). Diagnostic models based on these markers showed AUCs of 0.840 (95% CI:0.806-0.875) for MS and 0.905 (95% CI:0.877-0.933) for NMOSD. Differential diagnosis between MS and NMOSD showed an AUC of 0.806 (95% CI: 0.750-0.863).
Inflammatory and nutritional markers are promising for assessing disease activity in MS and NMOSD. Diagnostic models based on these markers enhance the accuracy and clinical value of differentiating between the two conditions.
炎症和营养标志物最近因其在认知控制中心脱髓鞘疾病形成中的作用而受到关注。中性粒细胞与淋巴细胞比值（NLR）、单核细胞与淋巴细胞比值（MLR）、血小板与淋巴细胞比值（PLR）、全身免疫炎症指数（SII）和全身炎症反应指数（SIRI）等炎症指标，以及白蛋白（ALB）、血红蛋白（HB）和体重指数（BMI）等营养标志物，可能预测疾病的发生。然而，它们在评估多发性硬化症（MS）和视神经脊髓炎谱系障碍（NMOSD）等疾病方面的潜力仍未得到探索。
我们回顾性评估了249例NMOSD患者、244例MS患者和249例健康对照者（HC），计算MLR、NLR、PLR、SII和SIRI，并测量ALB、HB和BMI水平。采用逻辑回归和ROC曲线建立并验证诊断和鉴别MS与NMOSD的模型。此外，招募了35例MS患者、38例NMOSD患者和85例匹配的HC进行验证，并在6个月内监测标志物变化。
与HC组相比，MS组和NMOSD组的MLR、NLR、SII和SIRI显著更高，而ALB水平更低（P<0.05）。与MS患者相比，NMOSD患者的MLR、NLR、SII和SIRI更高，而HB和ALB水平更低（P<0.05）。这些标志物与总T淋巴细胞呈负相关，与C反应蛋白、扩展残疾状态量表（EDSS）和MRI T2病灶计数呈正相关。缓解后，NLR、SII和SIRI在6个月内下降，而ALB升高（P<0.05）。基于这些标志物的诊断模型显示，MS的AUC为0.840（95%CI：0.806-0.875），NMOSD的AUC为0.905（95%CI：0.877-0.933）。MS和NMOSD之间的鉴别诊断AUC为0.806（95%CI：0.750-0.863）。
炎症和营养标志物有望用于评估MS和NMOSD的疾病活动。基于这些标志物的诊断模型提高了鉴别这两种疾病的准确性和临床价值。
