Statistical modeling of Huntington disease onset.
Statistical modeling of Huntington disease onset.
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DOI：
10.1016/b978-0-12-801893-4.00004-3
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发表时间：
2017
影响因子：
--
通讯作者：
Wang Y
中科院分区：
文献类型：
--
作者：
Garcia TP;Marder K;Wang Y
亨廷顿氏病（HD）是由亨廷顿基因中CAG三核苷酸扩增引起的独特疾病，并且具有从受试者特异性特征（如运动和神经成像测量）预测发病年龄的能力。在临床试验中，正确建模发病年龄非常重要，因为它可以提高功效计算，并指导临床医生招募具有某些特征的受试者。我们讨论了建模发病的历史，从简单的线性和逻辑回归到先进的生存模型。我们强调他们的优点和缺点，强调方法的挑战时，基因突变状态不可用。我们还讨论了潜在的偏见和更高的变异性与发病的主观定义的不确定性。调整生存模型中不确定性的方法仍处于起步阶段，但对于HD和具有长前驱期的神经退行性疾病（如阿尔茨海默病和帕金森病）将是有益的。
Huntington’s disease (HD) is a unique disease caused by a CAG trinucleotide expansion in the Huntingtin gene and with the power to predict age-at-onset from subject-specific features like motor and neuroimaging measures. In clinical trials, properly modeling onset age is important because it improves power calculations and directs clinicians to recruit subjects with certain features. We discuss the history of modeling onset, from simple linear and logistic regression to advanced survival models. We highlight their advantages and disadvantages, emphasizing the methodological challenges when genetic mutation status is unavailable. We also discuss the potential bias and higher variability incurred from the uncertainty associated with subjective definitions for onset. Methods to adjust for the uncertainty in survival models are still in its infancy, but would be beneficial for HD and neurodegenerative diseases with long prodromal periods like Alzheimer’s and Parkinson’s disease.