Age Related Multiple Sclerosis Severity Score: Disability ranked by age
Age Related Multiple Sclerosis Severity Score: Disability ranked by age
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DOI：
10.1177/1352458517690618
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发表时间：
2017-12-01
影响因子：
5.8
通讯作者：
Hillert, Jan
中科院分区：
文献类型：
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作者：
Manouchehrinia, Ali;Westerlind, Helga;Hillert, Jan
背景资料：多发性硬化严重程度评分（MSSS）是通过将疾病持续时间的扩展残疾状态量表（EDSS）评分标准化而获得的，并且在横断面研究中一直是一种有价值的工具。目的：评估使用年龄而不是固有的模糊疾病持续时间是否是一种可行的方法。我们汇总了来自三个人群队列的残疾数据，并制定了年龄相关多发性硬化严重程度（ARMSS）根据评估时患者的年龄对EDSS评分进行排名。我们建立的权力，以检测组间的差异所提供的ARMSS评分，并评估其相对一致性随着时间的推移。结果：研究人群包括26058例患者来自瑞典（n=11846），加拿大（n=6179）和英国（n=8033）。EDSS与病程（r=0.46，95%CI：0.45-0.47）和年龄（r=0.44，95%CI：0.43-0.45）呈中度相关。ARMSS评分显示出相当的权力，以检测残疾组之间的差异，更新和原始MSSS.Conclusion：由于年龄通常是公正的，很容易获得，和ARMSS和MSSS是可比的，ARMSS可以提供一个更通用的工具，可以尽量减少研究偏见和损失的统计权力所造成的不准确或缺失的发病日期。
Background: The Multiple Sclerosis Severity Score (MSSS) is obtained by normalising the Expanded Disability Status Scale (EDSS) score for disease duration and has been a valuable tool in cross-sectional studies.Objective: To assess whether use of age rather than the inherently ambiguous disease duration was a feasible approach.Method: We pooled disability data from three population-based cohorts and developed an Age Related Multiple Sclerosis Severity (ARMSS) score by ranking EDSS scores based on the patient's age at the time of assessment. We established the power to detect a difference between groups afforded by the ARMSS score and assessed its relative consistency over time.Results: The study population included 26058 patients from Sweden (n=11846), Canada (n=6179) and the United Kingdom (n=8033). There was a moderate correlation between EDSS and disease duration (r=0.46, 95% confidence interval (CI): 0.45-0.47) and between EDSS and age (r=0.44, 95% CI: 0.43-0.45). The ARMSS scores showed comparable power to detect disability differences between groups to the updated and original MSSS.Conclusion: Since age is typically unbiased and readily obtained, and the ARMSS and MSSS were comparable, the ARMSS may provide a more versatile tool and could minimise study biases and loss of statistical power caused by inaccurate or missing onset dates.