Assessing drug compliance using longitudinal marker data, with application to AIDS.
The assessment of non-compliance to a study medication is an important issue in the evaluation of clinical trials of self-administered drugs. Traditional methods for evaluating the compliance of subjects include self-reported questionnaires and pharmacologic assays of drug levels in randomly-drawn blood samples, but each of these has important limitations. This paper adapts and extends changepoint methods to assess compliance from longitudinal data on laboratory markers that are affected by the drug. The maximum likelihood estimators for two models are developed and examined. The effect of the drug on the marker process, as well as the spacing of the observations of the marker process relative to the time of non-compliance determine which model parameters are estimable. For the situations examined, the method of maximum likelihood is found to perform well in most cases. However, when non-compliance begins shortly before the last observation of the marker process, these (as well as any other) estimators cannot reliably distinguish non-compliance from compliance. The methods are illustrated with an example from a recent clinical trial of persons infected with HIV.
Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115.
H M
HM
Kim
S W
SW
Lagakos
D000163:Acquired Immunodeficiency Syndrome / Q000188:drug therapy* / Q000453:epidemiology; D000998:Antiviral Agents / Q000008:administration & dosage / Q000627:therapeutic use; D015415:Biomarkers; D004909:Erythrocyte Indices; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D010349:Patient Compliance; D010919:Placebos; D012646:Self Administration; D015215:Zidovudine / Q000627:therapeutic use
D000998:Antiviral Agents; D015415:Biomarkers; D010919:Placebos; D015215:Zidovudine