Parametric models for studying time to antiretroviral resistance associated with illicit drug use.
OBJECTIVE
Biomedical researchers tend to choose semiparametric methods to model time-to-event data because they do not require any assumptions about the shape of the underlying hazard. An example is provided where parametric models are a desirable alternative.


METHODS
Data were analyzed from a prospective cohort study of 195 adults receiving HIV care and highly active antiretroviral therapy in Baltimore, Md. They were followed for 1188 visits between February 2000 and December 2001. Kaplan-Meier estimation and Cox and Weibull regressions were performed.


RESULTS
Illicit drug users experienced a greater hazard of clinically significant antiretroviral resistance as compared to non-users. Weibull regression demonstrated that a quarter and a half of illicit drug users developed resistance within 5 and 20 months of viral suppression, respectively, compared to 20 and 85 months, respectively, for non-users.


CONCLUSIONS
Both semiparametric and parametric methods demonstrated an increased hazard of clinically significant resistance associated with illicit drug use. The parametric model facilitated the estimation of elapsed time to resistance associated with illicit drug use.
Sethi
Ajay K
AK
Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, 610 Walnut St, 587 WARF, Madison, WI 53726-2397, USA. aksethi@wisc.edu
Gange
Stephen J
SJ
D000328:Adult; D023241:Antiretroviral Therapy, Highly Active; D024882:Drug Resistance, Viral; D015658:HIV Infections / Q000188:drug therapy* / Q000453:epidemiology; D006801:Humans; D008396:Maryland / Q000453:epidemiology; D015233:Models, Statistical; D011446:Prospective Studies; D019966:Substance-Related Disorders / Q000150:complications* / Q000453:epidemiology; D013997:Time Factors