Ataxia Center, Cognitive Behavioral Neurology Unit, Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA.
Cerebellum. 2023 Oct;22(5):790-809. doi: 10.1007/s12311-022-01424-1. Epub 2022 Aug 12.
Spinocerebellar ataxias (SCAs) are progressive neurodegenerative disorders, but there is no metric that predicts disease severity over time. We hypothesized that by developing a new metric, the Severity Factor (S-Factor) using immutable disease parameters, it would be possible to capture disease severity independent of clinical rating scales. Extracting data from the CRC-SCA and READISCA natural history studies, we calculated the S-Factor for 438 participants with symptomatic SCA1, SCA2, SCA3, or SCA6, as follows: ((length of CAG repeat expansion - maximum normal repeat length) /maximum normal repeat length) × (current age - age at disease onset) × 10). Within each SCA type, the S-Factor at the first Scale for the Assessment and Rating of Ataxia (SARA) visit (baseline) was correlated against scores on SARA and other motor and cognitive assessments. In 281 participants with longitudinal data, the slope of the S-Factor over time was correlated against slopes of scores on SARA and other motor rating scales. At baseline, the S-Factor showed moderate-to-strong correlations with SARA and other motor rating scales at the group level, but not with cognitive performance. Longitudinally the S-Factor slope showed no consistent association with the slope of performance on motor scales. Approximately 30% of SARA slopes reflected a trend of non-progression in motor symptoms. The S-Factor is an observer-independent metric of disease burden in SCAs. It may be useful at the group level to compare cohorts at baseline in clinical studies. Derivation and examination of the S-factor highlighted challenges in the use of clinical rating scales in this population.
脊髓小脑共济失调(SCA)是一种进行性神经退行性疾病,但目前尚无能够预测疾病随时间进展严重程度的指标。我们假设通过开发一种新的度量标准,即使用不可变疾病参数的严重程度因子(S-Factor),可以独立于临床评分量表来捕捉疾病严重程度。从 CRC-SCA 和 READISCA 自然史研究中提取数据,我们为 438 名有症状的 SCA1、SCA2、SCA3 或 SCA6 参与者计算了 S-Factor,方法如下:[(CAG 重复扩展长度-最大正常重复长度)/最大正常重复长度]×(当前年龄-发病年龄)×10)。在每种 SCA 类型中,第一个 Scale for the Assessment and Rating of Ataxia(SARA)就诊时(基线)的 S-Factor 与 SARA 评分以及其他运动和认知评估的评分相关。在 281 名具有纵向数据的参与者中,S-Factor 随时间的斜率与 SARA 和其他运动评分量表的斜率相关。在基线时,S-Factor 在组水平上与 SARA 和其他运动评分量表具有中度至强的相关性,但与认知表现无关。纵向来看,S-Factor 斜率与运动量表上的表现斜率没有一致的关联。大约 30%的 SARA 斜率反映了运动症状进展趋势的非进展。S-Factor 是 SCA 中疾病负担的一种观察者独立的度量标准。在临床研究中,它可能在组水平上有助于比较基线时的队列。S-Factor 的推导和检查突出了在该人群中使用临床评分量表的挑战。