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On a Shape-Invariant Hazard Regression Model with application to an HIV Prevention Study of Mother-to-Child Transmission

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  • Cheng Zheng

    (University of Wisconsin-Milwaukee)

  • Ying Qing Chen

    (Fred Hutchinson Cancer Research Center)

Abstract

In survival analysis, Cox model is widely used for most clinical trial data. Alternatives include the additive hazard model, the accelerated failure time (AFT) model and a more general transformation model. All these models assume that the effects for all covariates are on the same scale. However, it is possible that for different covariates, the effects are on different scales. In this paper, we propose a shape-invariant hazard regression model that allows us to estimate the multiplicative treatment effect with adjustment of covariates that have non-multiplicative effects. We propose moment-based inference procedures for the regression parameters. We also discuss the risk prediction and the goodness of fit test for our proposed model. Numerical studies show good finite sample performance of our proposed estimator. We applied our method to the HIVNET 012 study, a milestone trial of single-dose nevirapine in prevention of mother-to-child transmission of HIV. From the HIVNET 012 data analysis, single-dose nevirapine treatment is shown to improve 18-month infant survival significantly with appropriate adjustment of the maternal CD4 counts and the virus load.

Suggested Citation

  • Cheng Zheng & Ying Qing Chen, 2020. "On a Shape-Invariant Hazard Regression Model with application to an HIV Prevention Study of Mother-to-Child Transmission," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 340-352, December.
    • Handle: RePEc:spr:stabio:v:12:y:2020:i:3:d:10.1007_s12561-019-09260-4
    DOI: 10.1007/s12561-019-09260-4
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    References listed on IDEAS

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    1. Yu Shen & S. C. Cheng, 1999. "Confidence Bands for Cumulative Incidence Curves Under the Additive Risk Model," Biometrics, The International Biometric Society, vol. 55(4), pages 1093-1100, December.
    2. Zeng, Donglin & Lin, D.Y., 2007. "Efficient Estimation for the Accelerated Failure Time Model," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1387-1396, December.
    3. Ying Qing Chen, 2001. "Accelerated Hazards Regression Model and Its Adequacy for Censored Survival Data," Biometrics, The International Biometric Society, vol. 57(3), pages 853-860, September.
    4. Yuhyun Park, 2003. "Estimating subject-specific survival functions under the accelerated failure time model," Biometrika, Biometrika Trust, vol. 90(3), pages 717-723, September.
    5. Ying Qing Chen & Nan Hu & Su-Chun Cheng & Philippa Musoke & Lue Ping Zhao, 2012. "Estimating Regression Parameters in an Extended Proportional Odds Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 318-330, March.
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