Møller Bjørn, Fekjaer Harald, Hakulinen Timo, Sigvaldason Helgi, Storm Hans H, Talbäck Mats, Haldorsen Tor
Kreftregisteret, Institute of Population-based Cancer Research, N-0310 Oslo, Norway.
Stat Med. 2003 Sep 15;22(17):2751-66. doi: 10.1002/sim.1481.
Prediction of the future number of cancer cases is of great interest to society. The classical approach is to use the age-period-cohort model for making cancer incidence predictions. We made an empirical comparison of different versions of this model, using data from cancer registries in the Nordic countries for the period 1958-1997. We have applied 15 different methods to 20 sites for each sex in Denmark, Finland, Norway and Sweden. Median absolute value of the relative difference between observed and predicted numbers of cases for these 160 combinations of site, sex and country was calculated. The medians varied between 10.4 per cent and 15.3 per cent in predictions 10 years ahead, and between 15.1 per cent and 32.0 per cent for 20 year predictions. We have four main conclusions: (i) projecting current trends worked better than assuming that future rates are equal to present rates; (ii) the method based on the multiplicative APC model often overestimated the number of cancer cases due to its exponential growth over time, but using a power function to level off this growth improved the predictions; (iii) projecting only half of the trend after the first 10 years also gave better long-term predictions; (iv) methods that emphasize trends in the last decade seem to perform better than those that include earlier time trends.
预测未来癌症病例数备受社会关注。经典方法是使用年龄-时期-队列模型来预测癌症发病率。我们利用北欧国家癌症登记处1958 - 1997年期间的数据,对该模型的不同版本进行了实证比较。我们在丹麦、芬兰、挪威和瑞典,针对每个性别的20个部位应用了15种不同方法。计算了这些部位、性别和国家的160种组合的观察病例数与预测病例数相对差异的中位数绝对值。10年预测中,中位数在10.4%至15.3%之间,20年预测中则在15.1%至32.0%之间。我们有四个主要结论:(i)预测当前趋势比假设未来发病率等于当前发病率效果更好;(ii)基于乘法年龄-时期-队列模型的方法由于其随时间呈指数增长,常常高估癌症病例数,但使用幂函数来平缓这种增长可改善预测;(iii)在前10年后仅预测一半的趋势也能给出更好的长期预测;(iv)强调过去十年趋势的方法似乎比包含更早时间趋势的方法表现更好。