Additive Hazard Regression Models: An Application to the Natural History of Human Papillomavirus
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 proporti...
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| Format: | Online |
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Hindawi Publishing Corporation
2013
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3569891/ |
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pubmed-35698912013-02-19 Additive Hazard Regression Models: An Application to the Natural History of Human Papillomavirus Xie, Xianhong Strickler, Howard D. Xue, Xiaonan Research Article 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. Hindawi Publishing Corporation 2013 2013-01-28 /pmc/articles/PMC3569891/ /pubmed/23424606 http://dx.doi.org/10.1155/2013/796270 Text en Copyright © 2013 Xianhong Xie et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Xie, Xianhong Strickler, Howard D. Xue, Xiaonan |
| spellingShingle |
Xie, Xianhong Strickler, Howard D. Xue, Xiaonan Additive Hazard Regression Models: An Application to the Natural History of Human Papillomavirus |
| author_facet |
Xie, Xianhong Strickler, Howard D. Xue, Xiaonan |
| author_sort |
Xie, Xianhong |
| title |
Additive Hazard Regression Models: An Application to the Natural History of Human Papillomavirus |
| title_short |
Additive Hazard Regression Models: An Application to the Natural History of Human Papillomavirus |
| title_full |
Additive Hazard Regression Models: An Application to the Natural History of Human Papillomavirus |
| title_fullStr |
Additive Hazard Regression Models: An Application to the Natural History of Human Papillomavirus |
| title_full_unstemmed |
Additive Hazard Regression Models: An Application to the Natural History of Human Papillomavirus |
| title_sort |
additive hazard regression models: an application to the natural history of human papillomavirus |
| description |
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. |
| publisher |
Hindawi Publishing Corporation |
| publishDate |
2013 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3569891/ |
| _version_ |
1611954117157060608 |