Tiwari Ram C, Ghosh Kaushik, Jemal Ahmedin, Hachey Mark, Ward Elizabeth, Thun Michael J, Feuer Eric J
Statistical Research and Applications Branch, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA.
CA Cancer J Clin. 2004 Jan-Feb;54(1):30-40. doi: 10.3322/canjclin.54.1.30.
Every January for more than 40 years, the American Cancer Society (ACS) has estimated the total number of cancer deaths that are expected to occur in the United States and individual states in the upcoming year. In a collaborative effort to improve the accuracy of the predictions, investigators from the National Cancer Institute and the ACS have developed and tested a new prediction method. The new method was used to create the mortality predictions for the first time in Cancer Statistics, 2004 and Cancer Facts & Figures 2004. The authors present a conceptual overview of the previous ACS method and the new state-space method (SSM), and they review the results of rigorous testing to determine which method provides more accurate predictions of the observed number of cancer deaths from the years 1997 to 1999. The accuracy of the methods was compared using squared deviations (the square of the predicted minus observed values) for each of the cancer sites for which predictions are published as well as for all cancer sites combined. At the national level, the squared deviations were not consistently lower for every cancer site for either method, but the average squared deviations (averaged across cancer sites, years, and sex) was substantially lower for the SSM than for the ACS method. During the period 1997 to 1999, the ACS estimates of deaths were usually greater than the observed numbers for all cancer sites combined and for several major individual cancer sites, probably because the ACS method was less sensitive to recent changes in cancer mortality rates (and associated counts) that occurred for several major cancer sites in the early and mid 1990s. The improved accuracy of the new method was particularly evident for prostate cancer, for which mortality rates changed dramatically in the late 1980s and early 1990s. At the state level, the accuracy of the two methods was comparable. Based on these results, the ACS has elected to use the new method for the annual prediction of the number of cancer deaths at the national and state levels.
四十多年来,每年一月美国癌症协会(ACS)都会预估下一年美国及各州预计的癌症死亡总数。为提高预测准确性,美国国立癌症研究所和美国癌症协会的研究人员共同开发并测试了一种新的预测方法。这种新方法首次用于《2004年癌症统计》和《2004年癌症事实与数据》中的死亡率预测。作者对之前美国癌症协会的方法和新的状态空间方法(SSM)进行了概念性概述,并回顾了严格测试的结果,以确定哪种方法能更准确地预测1997年至1999年观察到的癌症死亡人数。使用已发布预测的每个癌症部位以及所有癌症部位合并后的平方偏差(预测值减去观察值的平方)来比较这两种方法的准确性。在国家层面,两种方法对于每个癌症部位的平方偏差并非始终更低,但状态空间方法的平均平方偏差(按癌症部位、年份和性别平均)比美国癌症协会的方法低得多。在1997年至1999年期间,美国癌症协会对所有癌症部位合并以及几个主要个体癌症部位的死亡估计通常高于观察到的数字,这可能是因为美国癌症协会的方法对二十世纪九十年代初和中期几个主要癌症部位癌症死亡率(及相关计数)的近期变化不太敏感。新方法提高的准确性在前列腺癌方面尤为明显,其死亡率在二十世纪八十年代末和九十年代初发生了巨大变化。在州层面,两种方法的准确性相当。基于这些结果,美国癌症协会已选择使用新方法对国家和州层面的癌症死亡人数进行年度预测。