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首页> 外文期刊>Journal of neurology >A multifactorial prognostic index in multiple sclerosis. Cerebrospinal fluid IgM oligoclonal bands and clinical features to predict the evolution of the disease.
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A multifactorial prognostic index in multiple sclerosis. Cerebrospinal fluid IgM oligoclonal bands and clinical features to predict the evolution of the disease.

机译：多发性硬化症的多因素预后指标。脑脊液IgM寡克隆带和临床特征可预测疾病的发展。

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BACKGROUND: The ability to predict the future progression of MS represents a key issue for the neurologist. The aim of the study was to create a multifactorial prognostic index (MPI) providing the probability of a severe MS course at diagnosis based on clinical and immunological CSF parameters. METHODS: 64 clinically definite relapsing-remitting (RR)MS patients (38 benign, 26 severe MS) followed up for at least 10 years were included. Clinical and demographic details, EDSS after 5 and 10 years, progression index, relapse number and rate, time to a second relapse were assessed. CSF and serum samples collected at diagnosis were examined for CSF IgM and IgG oligoclonal bands (OB) and quantitative IgM and IgG determination. RESULTS: Kaplan-Meier analysis showed that the probability of reaching an EDSS score of 3 or 4 was significantly influenced by the presence of IgMOB (p<0.01 and p<0.01, log-rank test) and by the symptoms at onset (p=0.04 and p=0.03, log-rank test). These results were confirmed at multivariate analysis (Cox model). Univariate logistic analysis showed that IgMOB presence predicted a severe MS course (OR=9.33, CI=2.92- 29.88), whereas sensory symptoms at onset predicted a benign MS course (OR=0.12, CI=0.02-0.56). Using multivariate logistic regression the factors found to be significant were: presence/absence of IgMOB (p<0.01), onset with sensory (p<0.01) and pyramidal symptoms (p=0.01), and first inter-attack interval (p=0.03). The individual probability of a severe evolution was thus estimated by a simple formula comprising clinical and biological markers of prognosis available at diagnosis (pyramidal and sensory symptoms, months to the 2nd episode, and IgMOB presence/absence), giving the probability of developing a severe MS course. Applied to the same patient cohort this formula showed a global error of 6/64 (9.37%). We then used another independent series of 65 RRMS patients to validate this model. In this second patient cohort, 4/45 BMS and 4/20 SMS patients were found to have beenincorrectly classified (based on the formula), with a global error of 8/65 (12.31%). CONCLUSION: For the first time we created a MPI, using clinical and biological markers to predict the clinical course of MS at diagnosis. This index can support the clinician in patient counselling, therapeutic choices, as well as in patient selection criteria for clinical trials.
机译：背景：预测MS未来进展的能力是神经科医生的关键问题。这项研究的目的是创建一个多因素预后指数（MPI），以临床和免疫CSF参数为基础，提供诊断时严重MS病程的可能性。方法：包括64例临床确诊的复发-缓解（RR）MS患者（38例良性，26例严重MS），随访至少10年。评估临床和人口统计学细节，5年和10年后的EDSS，进展指数，复发次数和发生率，至第二次复发的时间。检查诊断时收集的CSF和血清样品的CSF IgM和IgG寡克隆带（OB）以及定量IgM和IgG测定。结果：Kaplan-Meier分析显示，EDg得分达到3或4的可能性受IgMOB的存在（p <0.01和p <0.01，对数秩检验）和发病症状的显着影响（p = 0.04和p = 0.03，对数秩检验）。这些结果在多变量分析（Cox模型）中得到了证实。单因素逻辑分析表明，IgMOB的存在预示着严重的MS病程（OR = 9.33，CI = 2.92-29.88），而感官症状发作时预示着良性的MS病程（OR = 0.12，CI = 0.02-0.56）。使用多元逻辑回归分析，发现重要的因素是：IgMOB的存在与否（p <0.01），感觉上的发作（p <0.01）和金字塔状症状（p = 0.01）以及首次发作间隔（p = 0.03） ）。因此，可以通过一个简单的公式来估算个体发生严重进化的可能性，该简单公式包括诊断时可用的临床和生物学预后标志物（锥体和感官症状，至第二次发作的月数以及IgMOB的存在/不存在），从而给出发生严重疾病的可能性。 MS课程。应用于同一患者队列，该公式显示出6/64（9.37％）的整体误差。然后，我们使用了65个RRMS患者的另一个独立系列来验证该模型。在第二个患者队列中，发现4/45 BMS和4/20 SMS患者被错误分类（基于公式），总体误差为8/65（12.31％）。结论：我们首次创建了MPI，使用临床和生物学标志物来预测诊断时MS的临床过程。该指数可以支持临床医生进行患者咨询，治疗选择以及临床试验的患者选择标准。

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