### 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) |
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Article number | 796270 |

Journal | Computational and Mathematical Methods in Medicine |

Volume | 2013 |

DOIs | |

State | Published - 2013 |

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### 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).

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 -