New Model for Estimation of the Age at Onset in Spinocerebellar Ataxia Type 3
New Model for Estimation of the Age at Onset in Spinocerebellar Ataxia Type 3
复制标题
估计 3 型脊髓小脑共济失调发病年龄的新模型
DOI：
10.1212/wnl.0000000000012068
复制
发表时间：
2021-06-08
期刊：
影响因子：
9.9
通讯作者：
Jiang, Hong
中科院分区：
文献类型：
--
作者：
Peng, Linliu;Chen, Zhao;Jiang, Hong
目的建立适用于中国大陆中国人群脊髓小脑性共济失调3型/马查多-约瑟夫病(SCA3/MJD)患者发病年龄的参数生存模型。方法比较基于ATXN3重复长度的6种参数生存分析方法(指数法、威布尔法、对数高斯法、高斯法、对数Logistic法和Logistic法)在预测SCA3/MJD患者最大队列中发生AAO的效率和性能。采用−-2对数似然统计量、阿凯克信息准则、贝叶斯信息准则、Nagelkerke R^2(Nagelkerke R^2)和考克斯-斯奈尔残差图等一系列评价标准来确定最佳模型。结果在这6个参数生存模型中，Logistic模型具有最低的−-2对数似然(6,560.12)、最低的AIC值(6,566.12)、最低的BIC值(6,566.14)和最高的NagelkerkeR^2(0.54)，其图最接近平分线Cox-Snell残差图。因此，Logistic生存模型最适合于所研究的数据。利用最优Logistic生存模型，根据CAG重复数大小和当前年龄，给出了AAO的年龄分布。结论首次证明Logistic生存模型对中国地区SCA3/MJD患者的AAO预测具有最好的拟合度。该优化模型具有一定的临床应用价值和研究价值。然而，它的临床应用还需要其他独立队列的严格临床测试和实践。一个跨多民族队列的统一模型值得进一步探索，方法是确定AAO测定的地区差异和重要影响因素。
Objectives The aim of this study was to develop an appropriate parametric survival model to predict patient's age at onset (AAO) for spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) populations from mainland China. Methods We compared the efficiency and performance of 6 parametric survival analysis methods (exponential, weibull, log-gaussian, gaussian, log-logistic, and logistic) based on cytosine-adenine-guanine (CAG) repeat length at ATXN3 to predict the probability of AAO in the largest cohort of patients with SCA3/MJD. A set of evaluation criteria, including −2 log-likelihood statistic, Akaike information criterion (AIC), bayesian information criterion (BIC), Nagelkerke R-squared (Nagelkerke R^2), and Cox-Snell residual plot, were used to identify the best model. Results Among these 6 parametric survival models, the logistic model had the lowest −2 log-likelihood (6,560.12), AIC (6,566.12), and BIC (6,566.14) and the highest value of Nagelkerke R^2 (0.54), with the closest graph to the bisector Cox-Snell residual graph. Therefore, the logistic survival model was the best fit to the studied data. Using the optimal logistic survival model, we indicated the age-specific probability distribution of AAO according to the CAG repeat size and current age. Conclusions We first demonstrated that the logistic survival model provided the best fit for AAO prediction in patients with SCA3/MJD from mainland China. This optimal model can be valuable in clinical and research. However, the rigorous clinical testing and practice of other independent cohorts are needed for its clinical application. A unified model across multiethnic cohorts is worth further exploration by identifying regional differences and significant modifiers in AAO determination.