Short-Term Projection of Cancer Incidence in Japan Using an AgePeriod Interaction Model with Spline Smoothing
Short-Term Projection of Cancer Incidence in Japan Using an AgePeriod Interaction Model with Spline Smoothing
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DOI：
10.1093/jjco/hyt163
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发表时间：
2014-01-01
影响因子：
2.4
通讯作者：
Nishimoto, Hiroshi
中科院分区：
文献类型：
--
作者：
Katanoda, Kota;Kamo, Ken-Ichi;Nishimoto, Hiroshi
在日本，以人口为基础的癌症发病率数据报告比最近一年的癌症死亡率数据晚了几年。为了弥补这一差距，我们的目标是确定癌症发病率的短期预测方法。1985年至2007年的数据来自四个县(宫城县、山形县、福井县和长崎县)的基于人口的癌症登记处。考察了三种投影模型：年龄和周期的广义线性模型(A P线性)、年龄和周期及其交互作用的广义线性模型(AP线性)和年龄、周期及其交互作用的广义加性模型(AP Spline)。我们分别基于198595和19852000的数据，对2000年和2005年进行了5年预测。分析了7个癌症部位(胃癌、肝癌、结直肠癌、肺癌、女性乳腺癌、子宫颈和前列腺癌)以及所有癌症的总和。AP样条线模型准确投影13个癌部位性别组合中的8个，而A-P线性模型和AP线性模型的准确投影部位性别组合数量分别为2个和6个。对于肝癌和结直肠癌，仅AP样条法模型就能进行准确的预测；AP样条法的癌症发病率预测值和观测值之间的相对差异在0.4到10.9之间，而其他两个模型的预测值和观察值之间的相对差异在7.4到37.6之间。所有三个模型都未能预测2000年至2005年前列腺癌的突然增加。AP样条法模型是预测日本癌症发病率的候选方法。然而，我们需要对前列腺癌进行持续的验证。
In Japan, population-based cancer incidence data are reported several years behind the latest year of cancer mortality data. To bridge this gap, we aimed to determine a short-term projection method for cancer incidence.Data between 1985 and 2007 were obtained from the population-based cancer registries in four prefectures (Miyagi, Yamagata, Fukui and Nagasaki). Three projection models were examined: generalized linear model with age and period (A P linear); generalized linear model with age, period and their interactions (AP linear); and generalized additive model with age, period and their interactions smoothed by spline (AP spline). We performed a 5-year projection for the years 2000 and 2005, based on the data of 198595 and 19852000, respectively. Seven cancer sites (stomach, liver, colorectal, lung, female breast, cervix uteri and prostate) and all cancers combined were analyzed. The accuracy of projection was evaluated by whether each observed number fell within the 95 confidence interval of the projected number.The AP spline model accurately projected 8 of 13 cancer sitesex combinations, whereas the number of sitesex combinations of accurate projection was 2 and 6 for A P linear and AP linear models, respectively. For liver and colorectal cancers, the AP spline model alone performed accurate projections; the relative differences between projected and observed numbers of cancer incidence ranged between 0.4 and 10.9 for the AP spline, and between 7.4 and 37.6 for the other two models. All three models failed to project sudden increases in prostate cancer between 2000 and 2005.The AP spline model is a candidate method for the projection of cancer incidence in Japan. However, we need a continuous validation for prostate cancer.