Using marginal structural measurement-error models to estimate the long-term effect of antiretroviral therapy on incident AIDS or death.
To estimate the net effect of imperfectly measured highly active antiretroviral therapy on incident acquired immunodeficiency syndrome or death, the authors combined inverse probability-of-treatment-and-censoring weighted estimation of a marginal structural Cox model with regression-calibration methods. Between 1995 and 2007, 950 human immunodeficiency virus-positive men and women were followed in 2 US cohort studies. During 4,054 person-years, 374 initiated highly active antiretroviral therapy, 211 developed acquired immunodeficiency syndrome or died, and 173 dropped out. Accounting for measured confounders and determinants of dropout, the weighted hazard ratio for acquired immunodeficiency syndrome or death comparing use of highly active antiretroviral therapy in the prior 2 years with no therapy was 0.36 (95% confidence limits: 0.21, 0.61). This association was relatively constant over follow-up (P = 0.19) and stronger than crude or adjusted hazard ratios of 0.75 and 0.95, respectively. Accounting for measurement error in reported exposure using external validation data on 331 men and women provided a hazard ratio of 0.17, with bias shifted from the hazard ratio to the estimate of precision as seen by the 2.5-fold wider confidence limits (95% confidence limits: 0.06, 0.43). Marginal structural measurement-error models can simultaneously account for 3 major sources of bias in epidemiologic research: validated exposure measurement error, measured selection bias, and measured time-fixed and time-varying confounding.
Cole
Stephen R
SR
University of North Carolina Gillings School of Global Public Health, MacGavran-Greenberg Hall, CB#7435, Chapel Hill, NC 27599-7435, USA. cole@unc.edu
Jacobson
Lisa P
LP
Tien
Phyllis C
PC
Kingsley
Lawrence
L
Chmiel
Joan S
JS
Anastos
Kathryn
K
D000163:Acquired Immunodeficiency Syndrome / Q000188:drug therapy* / Q000453:epidemiology / Q000401:mortality; D000328:Adult; D044966:Anti-Retroviral Agents / Q000191:economics / Q000627:therapeutic use*; D023241:Antiretroviral Therapy, Highly Active / Q000706:statistics & numerical data*; D015982:Bias; D015331:Cohort Studies; D015986:Confounding Factors, Epidemiologic; D005260:Female; D015658:HIV Infections / Q000188:drug therapy; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015337:Multicenter Studies as Topic; D009657:North Carolina / Q000453:epidemiology; D017891:Pharmacoepidemiology; D016016:Proportional Hazards Models; D012044:Regression Analysis; D013223:Statistics as Topic; D014481:United States / Q000453:epidemiology
D044966:Anti-Retroviral Agents