Ohno-Machado L, Musen M A
Section on Medical Informatics, Stanford University School of Medicine, CA 94305, USA.
Proc Annu Symp Comput Appl Med Care. 1995:737-41.
We compare the performances of a Cox model and a neural network model that are used as prognostic tools for a cohort of people living with AIDS. We modeled disease progression for patients who had AIDS (according to the 1993 CDC definition) in a cohort of 588 patients in California, using data from the ATHOS project. We divided the study population into 10 training and 10 test sets and evaluated the prognostic accuracy of a Cox proportional hazards model and of a neural network model by determining the number of predicted deaths, the sensitivities, specificities, positive predictive values, and negative predictive values for intervals of one year following the diagnosis of AIDS. For the Cox model, we further tested the agreement between a series of binary observations, representing death in one, two, and three years, and a set of estimates which define the probability of survival for those intervals. Both models were able to provide accurate numbers on how many patients were likely to die at each interval, and reasonable individualized estimates for the two- and three-year survival of a given patient, but failed to provide reliable predictions for the first year after diagnosis. There was no evidence that the Cox model performed better than did the neural network model or vice-versa, but the former method had the advantage of providing some insight on which variables were most influential for prognosis. Nevertheless, it is likely that the assumptions required by the Cox model may not be satisfied in all data sets, justifying the use of neural networks in certain cases.
我们比较了作为艾滋病患者队列预后工具的Cox模型和神经网络模型的性能。我们利用ATHOS项目的数据，对加利福尼亚州588名患有艾滋病（根据1993年美国疾病控制与预防中心的定义）的患者的疾病进展进行建模。我们将研究人群分为10个训练集和10个测试集，并通过确定艾滋病诊断后一年间隔内的预测死亡人数、敏感性、特异性、阳性预测值和阴性预测值，评估Cox比例风险模型和神经网络模型的预后准确性。对于Cox模型，我们进一步测试了一系列二元观察结果（代表一年、两年和三年后的死亡情况）与一组定义这些间隔生存概率的估计值之间的一致性。两种模型都能够准确给出每个间隔可能死亡的患者数量，并对给定患者的两年和三年生存率提供合理的个体化估计，但在诊断后的第一年未能提供可靠的预测。没有证据表明Cox模型比神经网络模型表现更好，反之亦然，但前一种方法的优势在于能对哪些变量对预后影响最大提供一些见解。然而，Cox模型所需的假设可能并非在所有数据集中都能满足，这就说明了在某些情况下使用神经网络的合理性。
