Sample size and statistical methods
PK/PD, PD, TEAE, HIV inhibition
REGRESSION
For this first-in-human Phase I study, sample size was based primarily on feasibility, rather than statistical considerations. There was no imputation of missing data. In general, continuous variables were summarized to indicate the study population sample size (N), number of participants with available data (n), mean, standard deviation (SD), median, 25th percentile, 75th percentile, minimum, and maximum values. Summaries of PK concentrations also included the geometric mean, geometric coefficient of variation (CV [%]), and number and percentage of participants with below the level of quantification (BLQ) concentrations. PK values of BLQ were imputed as ½ the lower limit of quantification (LLOQ). Summaries of PD endpoints included the 95% confidence interval of the mean and change from baseline p-value. Categorical variables were summarized by the population size (N), number of participants with available data (n), number of participants in each category, and the percentage of participants in each category. Unless otherwise noted, the denominator to determine the percentage of participants in each category was based on the number of participants with available data. Select ordinal data may have been summarized using both descriptive statistics and counts and percentages of participants in each category, as appropriate.Baseline was the last non-missing value obtained closest to and prior to the insertion of the TAF/EVG vaginal insert. Data collection for baseline variables included demographic information including sexual and contraceptive history, medical history, pelvic examination, vital signs (height, weight and blood pressure), hematology testing, non-fasting chemistry testing, urine pregnancy testing, genital samples including vaginal and ectocervical tissue samples, and acceptability questionnaire. Safety assessments were performed throughout the study. TEAE data was collected at every visit after baseline sampling at visit 2. Normality of continuous data were tested using the PROC univariate command in SAS, then examining the normal quantile plot distribution and the Shapiro Wilk test statistic.Paired comparisons measuring the change in an endpoint from baseline to post treatment were performed using a paired t test or Wilcoxon signed rank sum test on difference variables. We correlated continuous PK endpoints with continuous PD endpoints using a Spearman or Pearson correlation coefficient depending on the distribution of the data. We used multiple linear regression model to fit a model of the PD data with multiple PK endpoints. For the vaginal fluid PK/PD correlations, the model was fit to include HIV inhibition in vaginal fluid with vaginal fluid concentrations of EVG, TFV and TAF. In this model, the interaction between EVG and TFV was also included. For cervical vaginal tissue PK/PD correlations, p24 antigen production in ectocervical tissue was regressed over EVG, TFV, TFVDP and TAF concentrations in vaginal tissue. Statistical significance was determined at the level of alpha = 0.05.