Supplementary Material for: Performance of a modified version of the Charlson Comorbidity Index in predicting Multiple Sclerosis disability accrual

Background: The natural history of Multiple Sclerosis (MS) is highly heterogeneous and almost unpredictable since several factors may affect the disease course including comorbidities. The aims of this study are to predict the risk of disability worsening and disease progression at first patient’s visit by using a modified version of the Charlson Comorbidity Index (mCCI). Methods: the mCCI was obtained by incorporating the grade of pyramidal functional system scores extracted by the Expanded Disability Status Scale (EDSS) into the original CCI version. The risk of reaching EDSS 4, EDSS 6 and secondary MS progression (SPMS) associated to mCCI classes was calculated by carrying out multivariable Cox regression models and it was reported as hazard ratios (HRs) and 95% confidence intervals (95% CIs). The accuracy of mCCI for the recognition of individuals who reached the study milestones was estimated by building the receiving operator curves and the optimal cut-off values were estimated. Results: a total of n=622 individuals were enrolled (72.7% women; median age 30.8 years [24-40]). Compared with patients with a mCCI equal to zero, the HRs for those with a mCCI comprised between 1 and 2 at first visit were 1.53 (1.1-2.1), 2.17 (1.48-2.96) and 1.57 (1.16-2.1) for the reaching of EDSS 4, EDSS 6 and SPMS, respectively. Moreover, individuals with a mCCI equal or higher than 3 were at even higher risk of reaching EDSS 6 (HR= 2.34; [1.44-3.8]) and SPMS conversion (HR= 2.38; [1.29-4.01]). The mCCI cut-off value of 3 reached a sensitivity and specificity of 88.1% and 77.8%, respectively, for the recognition of EDSS 4 while the mCCI cut-off of 4 reached a sensitivity of 83.1% and a specificity of 80.7% for the recognition of EDSS 6 and a sensitivity and a specificity of 76.8% and 87.5%, respectively, for the recognition of SPMS conversion. Conclusion: mCCI appeared a simple and fast tool for the prediction of MS prognosis since the first patient’s visit and its best cut-off values showed higher sensitivity and specificity for the recognition of patients who undergo disability worsening and SPMS conversion.

背景：多发性硬化（Multiple Sclerosis, MS）的自然病程具有高度异质性且几乎难以预测，多种因素（包括合并症）均可影响疾病进程。本研究旨在通过改良版查尔森合并症指数（modified Charlson Comorbidity Index, mCCI），预测患者首次就诊时的残疾恶化与疾病进展风险。方法：本研究将从扩展残疾状况量表（Expanded Disability Status Scale, EDSS）中提取的锥体束功能系统评分等级纳入原始查尔森合并症指数，构建改良版查尔森合并症指数（mCCI）。通过多变量Cox回归模型计算与mCCI分层相关的达到EDSS 4分、EDSS 6分及继发进展型多发性硬化（secondary MS progression, SPMS）的风险，结果以风险比（hazard ratios, HRs）及95%置信区间（95% CIs）呈现。通过绘制受试者工作特征曲线评估mCCI识别达到研究终点人群的效能，并确定最优截断值。结果：本研究共纳入622例受试者，其中女性占72.7%，中位年龄为30.8岁（四分位间距24~40岁）。与首次就诊时mCCI为0的患者相比，mCCI为1~2的患者达到EDSS 4分、EDSS 6分及SPMS的HR分别为1.53（95%CI：1.1~2.1）、2.17（95%CI：1.48~2.96）及1.57（95%CI：1.16~2.1）。此外，首次就诊时mCCI≥3的患者达到EDSS 6分（HR=2.34，95%CI：1.44~3.8）及SPMS转化（HR=2.38，95%CI：1.29~4.01）的风险更高。以mCCI=3作为截断值时，识别EDSS 4分的灵敏度为88.1%、特异度为77.8%；以mCCI=4作为截断值时，识别EDSS 6分的灵敏度为83.1%、特异度为80.7%，识别SPMS转化的灵敏度为76.8%、特异度为87.5%。结论：mCCI是一种简便快捷的工具，可从患者首次就诊时起预测多发性硬化的预后，其最优截断值在识别残疾恶化及SPMS转化的患者时具有更高的灵敏度与特异度。