Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Cancer. 2012 Feb 15;118(4):1091-9. doi: 10.1002/cncr.27404. Epub 2012 Jan 6.
A study was undertaken to evaluate the temporal projection methods that are applied by the American Cancer Society to predict 4-year-ahead projections.
Cancer mortality data recorded in each year from 1969 through 2007 for the United States overall and for each state from the National Center for Health Statistics was obtained. Based on the mortality data through 2000, 2001, 2002, and 2003, Projections were made 4 years ahead to estimate the expected number of cancer deaths in 2004, 2005, 2006, 2007, respectively, in the United States and in each state, using 5 projection methods. These predictive estimates were compared to the observed number of deaths that occurred for all cancers combined and 47 cancer sites at the national level, and 21 cancer sites at the state level.
Among the models that were compared, the joinpoint regression model with modified Bayesian information criterion selection produced estimates that are closest to the actual number of deaths. Overall, results show the 4-year-ahead projection has larger error than 3-year-ahead projection of death counts when the same method is used. However, 4-year-ahead projection from the new method performed better than the 3-year-ahead projection from the current state-space method.
The Joinpoint method with modified Bayesian information criterion model has the smallest error of all the models considered for 4-year-ahead projection of cancer deaths to the current year for the United States overall and for each state. This method will be used by the American Cancer Society to project the number of cancer deaths starting in 2012.
本研究旨在评估美国癌症协会（American Cancer Society）用于预测未来 4 年的时间投影方法。
从国家卫生统计中心（National Center for Health Statistics）获取了美国整体和各州 1969 年至 2007 年每年的癌症死亡率数据。根据 2000 年、2001 年、2002 年和 2003 年的死亡率数据，使用 5 种预测方法，向前预测 4 年，以分别估算 2004 年、2005 年、2006 年和 2007 年美国和各州的预期癌症死亡人数。将这些预测估计值与全国所有癌症和 47 个癌症部位以及 21 个癌症部位的实际死亡人数进行比较。
在所比较的模型中，使用修正贝叶斯信息准则选择的联合回归模型产生的估计值最接近实际死亡人数。总体而言，当使用相同方法时，4 年的死亡预测比 3 年的预测误差更大。然而，新方法的 4 年预测比当前状态空间方法的 3 年预测表现更好。
对于美国整体和各州，修正贝叶斯信息准则模型的联合回归方法是所有考虑的模型中用于预测当前年份后 4 年癌症死亡人数的方法，其误差最小。美国癌症协会将使用这种方法来预测自 2012 年开始的癌症死亡人数。
