Tiwari Ram C, Li Yi, Zou Zhaohui
Food and Drug Administration.
J Data Sci. 2010 Jul;8:471-482.
Providing reliable estimates of the ratios of cancer incidence and mortality rates across geographic regions has been important for the National cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program as it profiles cancer risk factors as well decides cancer control planning. A fundamental difficulty, however, arises when such ratios have to be computed to compare the rate of a subregion (e.g., California) with that of a parent region (e.g., the US). Such a comparison is often made for policy-making purposes. Based on F-approximations as well as normal approximations, this paper provides new confidence intervals (CIs) for such rate ratios. Intensive simulations, which capture the real issues with the observed mortality data, reveal that these two CIs perform well. In general, for rare cancer sites, the F-intervals are often more conservative, and for moderate and common cancers, all intervals perform similarly.
对于美国国立癌症研究所（NCI）的监测、流行病学和最终结果（SEER）计划而言，提供跨地理区域的癌症发病率与死亡率之比的可靠估计值非常重要，因为该计划既要描绘癌症风险因素，也要制定癌症控制规划。然而，当必须计算此类比率以比较一个子区域（如加利福尼亚州）与母区域（如美国）的比率时，就会出现一个基本难题。这种比较通常是出于决策目的而进行的。基于F近似法以及正态近似法，本文为此类比率提供了新的置信区间（CI）。密集的模拟捕捉了观察到的死亡率数据的实际问题，结果表明这两种置信区间表现良好。一般来说，对于罕见癌症部位，F区间通常更为保守，而对于中度和常见癌症，所有区间的表现相似。
