Running average analysis of clinical trial ambulatory blood pressure data.

A method is presented for analyzing ambulatory blood pressure monitoring (ABPM) time series data obtained from well-controlled clinical trials. The method uses running averages based on fixed time-of-day intervals (rather than a fixed number of neighboring measurements). These "interval running averages" effectively estimate average blood pressure during the specified time intervals, adjusting for unequal spacing between measurements, embedded missing data, varying measurement times-of-day, and doses of study medication taken during ABP monitoring. Blood pressure changes from baseline may be computed using the interval running averages in order to separate treatment effects from patients' normal daily blood pressure cycles. To ensure valid estimation of treatment effects over time, study medication dosing times should be rigorously controlled in the trial design and conduct. Interval running average curves may be presented graphically, and from them summary statistics may be computed for purposes of statistical analysis. By allowing for the inherent complications of ABP data collection, the effect of antihypertensive treatment in well-controlled clinical trials can be discerned.

Analysis of covariance in parallel-group clinical trials with pretreatment baselines.

Analysis of covariance (ANCOVA) techniques are often employed in the analysis of clinical trials to try to account for the effects of varying pretreatment baseline values of an outcome variable on posttreatment measurements of the same variable. Baseline measurements of outcome variables are typically random variables, which violates the usual ANCOVA assumption that covariate values are fixed. Therefore, the usual ANCOVA hypothesis tests of treatment effects may be invalid, and the ANCOVA slope parameter estimator biased, for this application. We show, however, that if the pretreatment - posttreatment measurements have a bivariate normal distribution, then (i) the ANCOVA model with residual error independent of the covariate is a valid expression of the relationship between pretreatment and posttreatment measurements; (ii) the usual (fixed-covariate analysis) ANCOVA estimates of the slope parameter and treatment effect contrasts are unbiased; and (iii) the usual ANCOVA treatment effect contrast t-tests are valid significance tests for treatment effects. Moreover, as long as the magnitudes of the treatment effects do not depend on the "true" pretreatment value of the outcome variable, the true slope parameter must lie in the interval (0, 1) and the ANCOVA model has a clear interpretation as an adjustment (based on between- and within-subject variability) to an analysis of variance model applied to the posttreatment-pretreatment differences.

Met-enkephalin, age and anatomy: a microiontophoretic study in the hippocampus.

Met-enkephalin, administered microiontophoretically, produced a greater increase in firing in cells in area CA 3-4 in the hippocampus of both young and aged Fisher 344 rats than it did in the CA 1 area. Furthermore, the effect of met-enkephalin on neuronal firing rates was not as great in old rats as it was in young rats. Finally, 20-40 nA of met-enkephalin produced an increase in firing in old rats that was equivalent to the difference (2.5 spikes/sec) in baseline firing between old (2.6 spikes/sec) and young rats (5.1 spikes/sec).