Estimating long-term multivariate progression from short-term data.
Estimating long-term multivariate progression from short-term data.
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DOI：
10.1016/j.jalz.2013.10.003
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发表时间：
2014-10
期刊：
影响因子：
--
通讯作者：
Alzheimer's Disease Neuroimaging Initiative
中科院分区：
文献类型：
--
作者：
Donohue MC;Jacqmin-Gadda H;Le Goff M;Thomas RG;Raman R;Gamst AC;Beckett LA;Jack CR Jr;Weiner MW;Dartigues JF;Aisen PS;Alzheimer's Disease Neuroimaging Initiative
进展缓慢的疾病通常是通过对疾病不同阶段的队列进行短期观察来研究的。阿尔茨海默病神经成像倡议(ADNI)跟踪调查了患有不同程度认知障碍的老年人，从正常到受损。这项研究包括一系列新的认知测试、生物标记物和大脑图像的丰富小组，每六个月收集一次，持续长达六年。关于疾病病理学的观察的相对时间尚不清楚。我们提出了一个通用的半参数模型和迭代估计程序来同时估计病理时间和长期生长曲线。由此得出的长期进展的估计是使用来自长期“Personnes Agées quid”(PAQUID)研究的认知轨迹进行微调的。我们通过模拟证明，该方法可以从短期观测中恢复长期的疾病趋势。该方法还根据疾病病理估计个体的时间顺序，提供对症状出现之前的时间的特定受试者的预后估计。当该方法应用于ADNI数据时，估计的增长曲线与阿尔茨海默病级联的主流理论大体一致。具有共同结果度量的其他数据集可以使用所提出的算法来组合。使用统计软件R对模型进行拟合并再现结果的软件可作为GREASE软件包(http://mdonohue.bitbucket.org/grace/).ADNI数据可从神经成像实验室(http://loni.usc.edu).)下载
Diseases that progress slowly are often studied by observing cohorts at different stages of disease for short periods of time. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) follows elders with various degrees of cognitive impairment, from normal to impaired. The study includes a rich panel of novel cognitive tests, biomarkers, and brain images collected every six months for up to six years. The relative timing of the observations with respect to disease pathology is unknown. We propose a general semi-parametric model and iterative estimation procedure to simultaneously estimate pathologic timing and long-term growth curves. The resulting estimates of long-term progression are fine-tuned using cognitive trajectories derived from the long-term “Personnes Agées QUID” (PAQUID) study. We demonstrate with simulations that the method can recover long-term disease trends from short-term observations. The method also estimates temporal ordering of individuals with respect to disease pathology, providing subject-specific prognostic estimates of the time until onset of symptoms. When the method is applied to ADNI data, the estimated growth curves are in general agreement with prevailing theories of the Alzheimer’s disease cascade. Other datasets with common outcome measures can be combined using the proposed algorithm. Software to fit the model and reproduce results with the statistical software R is available as the grace package (http://mdonohue.bitbucket.org/grace/). ADNI data can be downloaded from the Laboratory of NeuroImaging (http://loni.usc.edu).
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影响因子：
9.9
作者：
Jagust, W. J.;Landau, S. M.;Mathis, C. A.
通讯作者：
Mathis, C. A.
DOI：
10.1111/1467-9868.00130
发表时间：
1998-01-01
影响因子：
5.8
作者：
Ramsay, JO
通讯作者：
Ramsay, JO
影响因子：
2
作者：
LINDSTROM, MJ
通讯作者：
LINDSTROM, MJ
影响因子：
5.7
作者：
DARTIGUES, JF;GAGNON, M;SALAMON, R
通讯作者：
SALAMON, R
影响因子：
9.9
作者：
Petersen, R. C.;Aisen, P. S.;Weiner, M. W.
通讯作者：
Weiner, M. W.