Kafadar Karen, Prorok Philip C
Department of Mathematics, University of Colorado-Denver, Denver, Colorado 80217-3364, USA.
Stat Med. 2003 Jan 15;22(1):83-111. doi: 10.1002/sim.1331.
Randomized screening trials provide the optimal means of assessing the benefit of screening for cancer and other chronic diseases. Unlike therapy trials, however, where strict eligibility criteria assure the comparability of cases of disease in the arms of the trial, the cancer cases identified during follow-up are a subset of all randomized participants. Furthermore, those cases detected by screening tend to arise from length biased sampling which also can bias estimates of the screening benefit and of average lead time. To reduce or eliminate this bias, we propose several methods for defining comparable groups of cases from the trial arms. We examine, via simulation, these methods with respect to their effects on (i). point and interval estimates of average lead time and average benefit time and (ii). the logrank test statistic for a mortality effect of screening. The most successful new method for defining comparable case groups uses an estimate of the mean sojourn time (mean preclinical duration), and results in nearly unbiased estimates of average lead time and average benefit time as well as an unbiased logrank test statistic.
随机筛查试验提供了评估癌症及其他慢性病筛查益处的最佳手段。然而,与治疗试验不同,治疗试验中严格的入选标准确保了试验组中疾病病例的可比性,随访期间确定的癌症病例只是所有随机参与者中的一个子集。此外,通过筛查检测出的病例往往源于长度偏倚抽样,这也可能使筛查益处和平均提前期的估计产生偏差。为了减少或消除这种偏差,我们提出了几种从试验组中定义可比病例组的方法。我们通过模拟检验了这些方法对以下方面的影响:(i)平均提前期和平均受益期的点估计和区间估计,以及(ii)筛查死亡率效应的对数秩检验统计量。定义可比病例组最成功的新方法使用平均停留时间(平均临床前期持续时间)的估计值,结果得到的平均提前期和平均受益期估计值几乎无偏,对数秩检验统计量也无偏。