Evaluation of alternative statistical methods for linear model analysis to compare two treatments for 24-hour blood...

This paper evaluates alternative statistical methods for the analysis of 24-hour blood pressure data from a clinical trial which compares two treatments for hypertension. The primary objective of the study discussed here was to determine the time course for the blood pressure lowering effects of a test drug given once daily in the treatment of mild to moderate hypertension when compared with placebo. Thirty-five patients (24 on drug and 11 on placebo) were monitored for 24 hours at baseline and at two weeks post treatment, with diastolic blood pressure (DBP) measurements recorded at 22 time points within each 24-hour visit. The changes in DBP from baseline across the 22 time points are the response variables of interest. Various statistical methods for the assessment of treatment effects over the entire 24-hour dosing interval in a setting with small sample size are discussed and illustrated. The results from a special application of weighted least squares analysis of covariance, which employs a smoothed covariance matrix, support the hypothesis that a once daily dose of the drug significantly reduces DBP over the entire 24-hour dosing interval when compared with placebo. This method has the distinct advantage of enabling evaluation of treatment differences for the change in DBP from baseline at the 22 time points with the corresponding 22 baseline DBP as covariates simultaneously in a situation where the treatment group sample sizes are small.