Get access

Improved genetic association tests for an ordinal outcome representing the disease progression process

Authors

  • Hong Zhang,

    1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
    2. Institute of Biostatistics, Fudan University, Shanghai, People's Republic of China
    Search for more papers by this author
  • Sholom Wacholder,

    1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
    Search for more papers by this author
  • Jing Qin,

    1. Division of Clinical Research, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland
    Search for more papers by this author
  • Allan Hildesheim,

    1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
    Search for more papers by this author
  • Kai Yu

    Corresponding author
    1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
    • Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Boulevard, Executive Plaza South, Room 5064, Bethesda, MD 20892
    Search for more papers by this author

Abstract

We are interested in detecting genetic variants that influence transition between discrete stages of a disease progression process, such as the natural history of progression to cervical cancer with the following four stages: (1) normal-human papillomavirus (HPV) exposed, (2) persistent infection with oncogenic HPV, (3) cervical intraepithelial neoplasia grades 2 or 3 (CIN2/3), and (4) cervical cancer. Standard statistical tests derived from the proportional odds model or polytomous regression model can be used to study this type of ordinal outcome. But these methods are either too sensitive to the proportion odds assumption or fail to take advantage of the restriction on the parameter space for the genetic variants. Two alternative tests, the maximum score test (MAX) and the adaptive P-value combination test (Adapt-P), are proposed with the aim of striking a balance between efficiency and robustness. A simulation study demonstrates that MAX and Adapt-P have the most robust performance among all considered tests under various realistic scenarios. As a demonstration, we applied the considered tests to a genetic association study of cervical cancer. Genet. Epidemiol. 2011.  © 2011 Wiley-Liss, Inc. 35: 499-505, 2011

Ancillary