Zhuo Z, Tsai Y J, Ackerman E, Gatewood L
Micropopulation Simulation Resource, Health Computer Sciences, University of Minnesota, Minneapolis 55455.
Int J Biomed Comput. 1994 Nov-Dec;37(3):287-96. doi: 10.1016/0020-7101(94)90126-0.
This is an extension of a series of papers dealing with certain models used in the simulation of coronary heart disease. The current study investigates implications of including age as a risk factor in the models discussed in the preceding papers. The effects of using age as a risk factor were investigated in two ways. In one of these, age is interpreted as age of entry into the study; it is similar to the other risk factors in that it is assumed to be constant throughout the study. In the other, age is interpreted as the actual age; thus it increases during the course of simulations. Two polychotomous, multivariate risk functions developed in previous studies, the logistic risk and the Neyman exponential risk, were used to explore the effects of including age as a risk factor. The estimated risk coefficient for age was found to be statistically significant for both functions. The model performance was evaluated by comparing the observational data with outcomes simulated using Monte Carlo techniques. It was found that the logistic risk function failed to describe the observations either with age as a constant or with aging during the simulations. The models including the Neyman exponential risk avoidance fit the data well. The evaluation of the results indicates that aging during the simulations is better than using only the age as the constant value at entry to the study.
这是一系列论述冠心病模拟中使用的特定模型的论文的续篇。当前研究探讨在前文所述模型中纳入年龄作为风险因素的影响。将年龄用作风险因素的影响通过两种方式进行研究。其中一种方式中，年龄被解释为进入研究时的年龄；它与其他风险因素类似，即假定在整个研究过程中保持不变。另一种方式中，年龄被解释为实际年龄；因此在模拟过程中它会增加。先前研究中开发的两个多分类多元风险函数，即逻辑风险函数和奈曼指数风险函数，被用于探究纳入年龄作为风险因素的影响。发现年龄的估计风险系数对这两个函数而言均具有统计学意义。通过将观测数据与使用蒙特卡洛技术模拟的结果进行比较来评估模型性能。结果发现，无论是将年龄视为常数还是在模拟过程中考虑年龄增长，逻辑风险函数都无法描述观测结果。包含奈曼指数风险规避的模型与数据拟合良好。对结果的评估表明，在模拟过程中考虑年龄增长比仅使用进入研究时的年龄常数更好。
