Gorlova Olga, Peng Bo, Yankelevitz David, Henschke Claudia, Kimmel Marek
Department of Epidemiology, University of Texas M. D. Anderson Cancer Center, Houston, TX 77030, USA.
Stat Med. 2005 Apr 15;24(7):1117-34. doi: 10.1002/sim.1987.
A method to estimate the population variability in tumour growth rate using incomplete data was developed. We assume exponential growth and lognormal distribution for the parameter of the growth curve. Estimates of growth rate obtained based on the cases with two measurements, one of which is obtained retrospectively, are biased towards lower growth rate. For the data sets where two measurements are available for some tumours and only one measurement for others (which means that no tumour was seen in retrospect for those cases), several approaches were developed that can eliminate or substantially reduce the bias. The relative error of the best estimates, as assessed by simulation, rarely exceeds 20 per cent. We found that the results of application of our estimation procedures to chest X-ray screening data agree well with the expectations.
开发了一种使用不完整数据估计肿瘤生长率总体变异性的方法。我们假设生长曲线参数呈指数增长和对数正态分布。基于两次测量（其中一次是回顾性获得）的病例得出的生长率估计值偏向于较低的生长率。对于一些肿瘤有两次测量数据而其他肿瘤只有一次测量数据的数据集（这意味着那些病例回顾时未发现肿瘤），开发了几种可以消除或大幅减少偏差的方法。通过模拟评估，最佳估计值的相对误差很少超过20%。我们发现，将我们的估计程序应用于胸部X光筛查数据的结果与预期非常吻合。
