Semiparametric Accelerated Failure Time Partial Linear Model and Its Application to Breast Cancer.
Semiparametric Accelerated Failure Time Partial Linear Model and Its Application to Breast Cancer.
复制标题
半参数加速失效时间偏线性模型及其在乳腺癌中的应用
DOI：
10.1016/j.csda.2010.10.012
复制
发表时间：
2011-03-01
影响因子：
1.8
通讯作者：
Qin, Guoyou
中科院分区：
文献类型：
--
作者：
Zou, Yubo;Zhang, Jiajia;Qin, Guoyou
乳腺癌是女性最常见的非皮肤癌，也是美国女性癌症相关死亡的第二大常见原因。众所周知，乳腺癌的生存率因诊断时的年龄而异。对于大多数癌症，相对存活率随年龄而下降，但乳腺癌可能具有不寻常的年龄模式。为了揭示阶段风险和年龄效应的规律，提出了半参数加速失效时间部分线性模型，并基于P样条和秩估计方法给出了其估计方法。仿真研究表明，当数据不受污染时，该方法与参数方法相当，而当数据受污染时，该方法比参数方法更稳定。通过将所提出的模型和方法应用于来自SEER项目的新泽西大西洋县的乳腺癌数据集，我们成功地揭示了阶段的显著影响，并表明38岁左右诊断的妇女的生存率始终高于年轻或老年妇女。
Breast cancer is the most common non-skin cancer in women and the second most common cause of cancer-related death in U.S. women. It is well known that the breast cancer survival varies by age at diagnosis. For most cancers, the relative survival decreases with age but breast cancer may have the unusual age pattern. In order to reveal the stage risk and age effects pattern, we propose the semiparametric accelerated failure time partial linear model and develop its estimation method based on the P-spline and the rank estimation approach. The simulation studies demonstrate that the proposed method is comparable to the parametric approach when data is not contaminated, and more stable than the parametric methods when data is contaminated. By applying the proposed model and method to the breast cancer data set of Atlantic county, New Jersey from SEER program, we successfully reveal the significant effects of stage, and show that women diagnosed around 38s have consistently higher survival rates than either younger or older women.
登录
查看更多内容
影响因子：
2.2
作者：
Xu J;Leng C;Ying Z
通讯作者：
Ying Z
影响因子：
5.7
作者：
Eilers, PHC;Marx, BD
通讯作者：
Marx, BD
影响因子：
1
作者：
Huang, Jianhua Z.;Zhang, Liangyue;Zhou, Lan
通讯作者：
Zhou, Lan
DOI：
10.1016/s0378-3758(00)00314-1
发表时间：
2001-10-01
影响因子：
0.9
作者：
Lu, XW;Singh, RS;Desmond, AF
通讯作者：
Desmond, AF
影响因子：
2.7
作者：
Jin, ZZ;Lin, DY;Ying, ZL
通讯作者：
Ying, ZL