Moon Hojin, Ahn Hongshik, Kodell Ralph L, Lee J Jack
Division of Biometry and Risk Assessment, National Center for Toxicological Research, Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, U.S.A.
Stat Med. 2003 Aug 30;22(16):2619-36. doi: 10.1002/sim.1444.
This paper extends the survival-adjusted Cochran-Armitage test in order to achieve improved robustness to a variety of tumour onset distributions. The Cochran-Armitage test is routinely applied for detecting a linear trend in the incidence of a tumour of interest across dose groups. To improve the robustness to the effects of differential mortality across groups, Bailer and Portier introduced the poly-3 test by a survival adjustment using a fractional weighting scheme for subjects not at full risk of tumour development. The performance of the poly-3 test depends on how closely it represents the correct specification of the time-at-risk weight in the data. Bailer and Portier further suggested that this test can be improved by using a general k reflecting the shape of the tumour onset distribution. In this paper, we propose a method to estimate k by equating the empirical lifetime tumour incidence rate obtained from the data based on the fractional weighting scheme to a separately estimated cumulative lifetime tumour incidence rate. This poly-k test with the statistically estimated k appears to perform better than the poly-3 test which is conducted without prior knowledge of the tumour onset distribution. Our simulation shows that the proposed method improves the robustness to various tumour onset distributions in addition to the robustness to the effects of mortality achieved by the poly-3 test. Large sample properties are shown via simulations to illustrate the consistency of the proposed method. The proposed methods are applied to analyse two real data sets. One is to find a dose-related linear trend on animal carcinogenicity, and the other is to test an effect of calorie restriction on experimental animals.
本文扩展了生存调整后的 Cochr an - Armitage检验，以提高对各种肿瘤发病分布的稳健性。 Cochr an - Armitage检验通常用于检测感兴趣的肿瘤在不同剂量组中的发病率的线性趋势。为了提高对组间差异死亡率影响的稳健性，Bailer和Portier通过对未完全处于肿瘤发生风险的受试者使用分数加权方案进行生存调整，引入了poly - 3检验。poly - 3检验的性能取决于它对数据中风险时间权重的正确设定的近似程度。Bailer和Portier进一步建议，可以通过使用反映肿瘤发病分布形状的一般k来改进此检验。在本文中，我们提出了一种方法，通过将基于分数加权方案从数据中获得的经验性终生肿瘤发病率与单独估计的累积终生肿瘤发病率相等来估计k。这种具有统计估计k的poly - k检验似乎比在没有肿瘤发病分布先验知识的情况下进行的poly - 3检验表现更好。我们的模拟表明，除了poly - 3检验所实现的对死亡率影响的稳健性之外，所提出的方法还提高了对各种肿瘤发病分布的稳健性。通过模拟展示了大样本性质，以说明所提出方法的一致性。所提出的方法被应用于分析两个真实数据集。一个是在动物致癌性方面寻找剂量相关的线性趋势，另一个是测试热量限制对实验动物的影响。
