Use of alternative time scales in Cox proportional hazard models: implications for time‐varying environmental exposures

Issues surrounding choice of time scales in Cox proportional hazard regression models have received limited attention in the literature. Although the choice between time on study and 'attained' age time scales has been examined, the calendar time scale may be of interest when modeling health effects of environmental exposures with noteworthy secular trends such as ambient particulate matter air pollution in large epidemiological cohort studies. The authors use simulation studies to examine performance (bias, mean squared error, coverage probabilities, and power) of models using all three time scales when the primary exposure of interest depends on calendar time. Results show that performance of models fit to the calendar time scale varies inversely with the strength of the linear association between the time-varying primary exposure and calendar time. Although models fit to attained age and time on study that do not adjust for calendar time were relatively robust, the authors conclude that care should be exercised when using time scales that are highly correlated with exposures of interest.

[1]  D Commenges,et al.  Re: "Serum transferrin saturation, stroke incidence, and mortality in women and men. The NHANES I Epidemiologic Followup Study". , 1997, American journal of epidemiology.

[2]  T Duchesne,et al.  Alternative Time Scales and Failure Time Models , 2000, Lifetime data analysis.

[3]  Beth Ann Griffin,et al.  Ambient Particulate Matter Air Pollution and Venous Thromboembolism in the Women’s Health Initiative Hormone Therapy Trials , 2010, Environmental health perspectives.

[4]  Norman E. Breslow,et al.  Multiplicative Models and Cohort Analysis , 1983 .

[5]  E L Korn,et al.  Time-to-event analysis of longitudinal follow-up of a survey: choice of the time-scale. , 1997, American journal of epidemiology.

[6]  Ana Maria Lopez,et al.  Effects of estrogen plus progestin on gynecologic cancers and associated diagnostic procedures: the Women's Health Initiative randomized trial. , 2003, JAMA.

[7]  D. Dockery,et al.  An association between air pollution and mortality in six U.S. cities. , 1993, The New England journal of medicine.

[8]  Duanping Liao,et al.  GIS Approaches for the Estimation of Residential-Level Ambient PM Concentrations , 2006, Environmental Health Perspectives.

[9]  Gretchen A. Stevens,et al.  National, regional, and global trends in systolic blood pressure since 1980: systematic analysis of health examination surveys and epidemiological studies with 786 country-years and 5·4 million participants , 2011, The Lancet.

[10]  K. Flegal,et al.  The decline in blood lead levels in the United States. The National Health and Nutrition Examination Surveys (NHANES) , 1994, JAMA.

[11]  J. Benichou,et al.  Choice of time‐scale in Cox's model analysis of epidemiologic cohort data: a simulation study , 2004, Statistics in medicine.

[12]  Simon Capewell,et al.  Cardiovascular risk factor trends and potential for reducing coronary heart disease mortality in the United States of America. , 2010, Bulletin of the World Health Organization.

[13]  L. Sheppard,et al.  Long-term exposure to air pollution and incidence of cardiovascular events in women. , 2007, The New England journal of medicine.

[14]  Michal Abrahamowicz,et al.  Comparison of algorithms to generate event times conditional on time‐dependent covariates , 2008, Statistics in medicine.

[15]  Fei Gao,et al.  Age at diagnosis and the choice of survival analysis methods in cancer epidemiology. , 2003, Journal of clinical epidemiology.

[16]  R. Burnett,et al.  Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. , 2002, JAMA.

[17]  Karen L. Soderberg,et al.  Wireless substitution: state-level estimates from the National Health Interview Survey, January 2007-June 2010. , 2011, National health statistics reports.