Introna Alessandro, Milella Giammarco, Morea Antonella, Ucci Maria, Fraddosio Angela, Zoccolella Stefano, D'Errico Eustachio, Simone Isabella Laura
Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari "Aldo Moro", piazza Giulio Cesare 11, 70100 Bari, Italy.
ASL Bari, San Paolo Hospital, Bari, Italy.
J Neurol Sci. 2021 Dec 15;431:120041. doi: 10.1016/j.jns.2021.120041. Epub 2021 Oct 28.
To estimate King's college clinical stage progression rate (ΔKC) at first clinical evaluation in order to define its predictive and prognostic role on survival in a large cohort of Amyotrophic Lateral Sclerosis (ALS) patients.
The ΔKC was calculated with the following formula: 0 - KC clinical stage at first clinical evaluation/disease duration from onset to first evaluation, and each result was reported as absolute value. All the evaluations were performed in two cohorts: one from our tertiary centre for motor neuron disease and the other one from a pooled resource open-access ALS clinical trials (PRO-ACT) database. C-statistic was used to evaluate the model discrimination of survival at different time points (1-3 years). Cox proportional hazard model was used to identify factors associated with survival.
ΔKC predicted survival at three years in our centre and in the PRO-ACT cohort (C-statistic 0.83, 95% CI 0.8-0.86, p < 0.0001; 0.7, 95% CI 0.68-0.73, p < 0.0001, respectively). At multivariate analysis, ΔKC was independently associated with survival both in our cohort (HR 3.62 95% CI 2.71-4.83 p = 0.001) and in the PRO-ACT cohort (HR 2.75 95% CI 2.1-3.6 p = 0.001).
Based on our results, ΔKC could be used as a novel measure of disease progression, hence as an accurate predictor of survival in ALS patients. Indeed, greater values of ΔKC were associated with a 3.5-fold higher risk to experience the event, confirming its robust prognostic value.
为了评估在首次临床评估时的King分期临床进展率(ΔKC),以确定其在一大群肌萎缩侧索硬化症(ALS)患者生存中的预测和预后作用。
使用以下公式计算ΔKC:0 - 首次临床评估时的KC临床分期/从发病到首次评估的疾病持续时间,每个结果均以绝对值报告。所有评估均在两个队列中进行:一个来自我们的三级运动神经元疾病中心,另一个来自汇总资源开放获取的ALS临床试验(PRO-ACT)数据库。C统计量用于评估不同时间点(1 - 3年)生存的模型辨别力。Cox比例风险模型用于识别与生存相关的因素。
ΔKC在我们中心和PRO-ACT队列中预测了三年生存率(C统计量分别为0.83,95%可信区间0.8 - 0.86,p < 0.0001;0.7,95%可信区间0.68 - 0.73,p < 0.0001)。在多变量分析中,ΔKC在我们的队列(风险比3.62,95%可信区间2.71 - 4.83,p = 0.001)和PRO-ACT队列(风险比2.75,95%可信区间2.1 - 3.6,p = 0.001)中均与生存独立相关。
基于我们的结果,ΔKC可作为疾病进展的一种新指标,因此可作为ALS患者生存的准确预测指标。事实上,ΔKC值越高,发生该事件的风险高3.5倍,证实了其强大的预后价值。