Abstract
There are several statistical methods for time-to-event analysis, among which is the Cox proportional hazards model that is most commonly used. However, when the absolute change in risk, instead of the risk ratio, is of primary interest or when the proportional hazard assumption for the Cox proportional hazards model is violated, an additive hazard regression model may be more appropriate. In this paper, we give an overview of this approach and then apply a semiparametric as well as a nonparametric additive model to a data set from a study of the natural history of human papillomavirus (HPV) in HIV-positive and HIV-negative women. The results from the semiparametric model indicated on average an additional 14 oncogenic HPV infections per 100 woman-years related to CD4 count < 200 relative to HIV-negative women, and those from the nonparametric additive model showed an additional 40 oncogenic HPV infections per 100 women over 5 years of followup, while the estimated hazard ratio in the Cox model was 3.82. Although the Cox model can provide a better understanding of the exposure disease association, the additive model is often more useful for public health planning and intervention.
| Original language | English (US) |
|---|---|
| Article number | 796270 |
| Journal | Computational and Mathematical Methods in Medicine |
| Volume | 2013 |
| DOIs | |
| State | Published - 2013 |
Fingerprint
ASJC Scopus subject areas
- Applied Mathematics
- Modeling and Simulation
- Biochemistry, Genetics and Molecular Biology(all)
- Medicine(all)
- Immunology and Microbiology(all)
Cite this
Additive hazard regression models : An application to the natural history of human papillomavirus. / Xie, Xianhong; Strickler, Howard; Xue, Xiaonan (Nan).
In: Computational and Mathematical Methods in Medicine, Vol. 2013, 796270, 2013.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Additive hazard regression models
T2 - An application to the natural history of human papillomavirus
AU - Xie, Xianhong
AU - Strickler, Howard
AU - Xue, Xiaonan (Nan)
PY - 2013
Y1 - 2013
N2 - There are several statistical methods for time-to-event analysis, among which is the Cox proportional hazards model that is most commonly used. However, when the absolute change in risk, instead of the risk ratio, is of primary interest or when the proportional hazard assumption for the Cox proportional hazards model is violated, an additive hazard regression model may be more appropriate. In this paper, we give an overview of this approach and then apply a semiparametric as well as a nonparametric additive model to a data set from a study of the natural history of human papillomavirus (HPV) in HIV-positive and HIV-negative women. The results from the semiparametric model indicated on average an additional 14 oncogenic HPV infections per 100 woman-years related to CD4 count < 200 relative to HIV-negative women, and those from the nonparametric additive model showed an additional 40 oncogenic HPV infections per 100 women over 5 years of followup, while the estimated hazard ratio in the Cox model was 3.82. Although the Cox model can provide a better understanding of the exposure disease association, the additive model is often more useful for public health planning and intervention.
AB - There are several statistical methods for time-to-event analysis, among which is the Cox proportional hazards model that is most commonly used. However, when the absolute change in risk, instead of the risk ratio, is of primary interest or when the proportional hazard assumption for the Cox proportional hazards model is violated, an additive hazard regression model may be more appropriate. In this paper, we give an overview of this approach and then apply a semiparametric as well as a nonparametric additive model to a data set from a study of the natural history of human papillomavirus (HPV) in HIV-positive and HIV-negative women. The results from the semiparametric model indicated on average an additional 14 oncogenic HPV infections per 100 woman-years related to CD4 count < 200 relative to HIV-negative women, and those from the nonparametric additive model showed an additional 40 oncogenic HPV infections per 100 women over 5 years of followup, while the estimated hazard ratio in the Cox model was 3.82. Although the Cox model can provide a better understanding of the exposure disease association, the additive model is often more useful for public health planning and intervention.
UR - http://www.scopus.com/inward/record.url?scp=84874589163&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84874589163&partnerID=8YFLogxK
U2 - 10.1155/2013/796270
DO - 10.1155/2013/796270
M3 - Article
C2 - 23424606
AN - SCOPUS:84874589163
VL - 2013
JO - Computational and Mathematical Methods in Medicine
JF - Computational and Mathematical Methods in Medicine
SN - 1748-670X
M1 - 796270
ER -