Claus J J, van Gool W A, Teunisse S, Walstra G J, Kwa V I, Hijdra A, Verbeeten B, Koelman J H, Bour L J, Ongerboer De Visser B W
Department of Neurology, Academic Medical Center, University of Amsterdam, The Netherlands.
Dement Geriatr Cogn Disord. 1998 Sep-Oct;9(5):284-93. doi: 10.1159/000017073.
We investigated whether an index based on clinical features, electroencephalogram and computed tomography is useful to predict survival in early Alzheimer's disease. One hundred and sixty-three consecutively referred patients to an outpatient memory clinic and first diagnosed with Alzheimer's disease (105 'probable' and 58 'possible', NINCDS-ADRDA criteria) were studied and outcome measure was death. Cox proportional hazards regression analysis and Kaplan-Meier survival curves were used to investigate relations between baseline parameters and survival. Eighty-four patients (51. 5%) died during the follow-up period that extended to 5.8 years, with a median duration of survival after entry of 4.3 years. Baseline factors that were statistically significant and independently related to increased risk of mortality were high age, male sex, poor cognitive function as measured with the CAMCOG, low alpha and beta power on electroencephalogram, and temporoparietal atrophy on computed tomography scan. These results were independent of the diagnosis probable or possible Alzheimer's disease. Based on the coefficients from the regression equation, we computed a survival index for each patient and we constructed three groups according to tertiles of this index. After 5.2 years of follow-up, survival curves showed a low mortality group with 81.7% patients alive (median survival at least 5.7 years), an intermediate mortality group with 35.9% patients alive (median survival 3.8 years), and a high mortality group with no patients alive (median survival 2.3 years). Log rank tests were statistically significant for comparisons between all three groups. We conclude that an overall index combining demographic, cognitive, electroencephalogram and computed tomography features is a strong predictor of survival in early Alzheimer's disease.
我们研究了一种基于临床特征、脑电图和计算机断层扫描的指标是否有助于预测早期阿尔茨海默病的生存期。对163例连续转诊至门诊记忆诊所且首次被诊断为阿尔茨海默病（按照美国国立神经疾病与中风研究所-阿尔茨海默病及相关疾病协会（NINCDS-ADRDA）标准，其中105例为“很可能的”，58例为“可能的”）的患者进行了研究，观察指标为死亡情况。采用Cox比例风险回归分析和Kaplan-Meier生存曲线来研究基线参数与生存期之间的关系。在长达5.8年的随访期内，84例患者（51.5%）死亡，入组后的中位生存期为4.3年。与死亡率增加具有统计学显著意义且独立相关的基线因素包括高龄、男性、用认知能力综合量表（CAMCOG）测得的认知功能差、脑电图上α和β波功率低以及计算机断层扫描显示颞顶叶萎缩。这些结果与阿尔茨海默病是“很可能的”还是“可能的”诊断无关。根据回归方程的系数，我们为每位患者计算了一个生存指数，并根据该指数的三分位数构建了三组。随访5.2年后，生存曲线显示低死亡率组81.7%的患者存活（中位生存期至少5.7年），中死亡率组35.9%的患者存活（中位生存期3.8年），高死亡率组无患者存活（中位生存期2.3年）。三组之间的比较，对数秩检验具有统计学显著性。我们得出结论，一个综合人口统计学、认知、脑电图和计算机断层扫描特征的总体指数是早期阿尔茨海默病生存期的有力预测指标。
