Package: seqDesign 1.3

seqDesign: Simulation and Group-Sequential Monitoring of Randomized Treatment Efficacy Trials with Time-to-Event Endpoints

A broad spectrum of both event-driven and fixed follow-up preventive vaccine efficacy trial designs, including designs of Gilbert, Grove et al. (2011, Statistical Communications in Infectious Diseases), are implemented, with application generally to individual-randomized clinical trials with multiple active treatment groups and a shared control group, and a study endpoint that is a time-to-event endpoint subject to right-censoring. The design accommodates the following features: (1) the possibility that the efficacy of the treatment/vaccine groups may take time to accrue while the multiple treatment administrations/vaccinations are given, (2) hazard ratio and cumulative incidence-based treatment/vaccine efficacy parameters and multiple estimation/hypothesis testing procedures are available, (3) interim/group-sequential monitoring of each treatment group for potential harm, non-efficacy (lack of benefit), efficacy (benefit), and high efficacy, (3) arbitrary alpha spending functions for different monitoring outcomes, (4) arbitrary timing of interim looks, separate for each monitoring outcome, in terms of either event accrual or calendar time, (5) flexible analysis cohort characterization (intention-to-treat vs. per-protocol/as-treated; counting only events for analysis that occur after a specific point in study time), and (6) division of the trial into two stages of time periods where each treatment is first evaluated for efficacy in the first stage of follow-up, and, if and only if it shows significant treatment efficacy in stage one, it is evaluated for longer-term durability of efficacy in stage two. The package produces plots and tables describing operating characteristics of a specified design including a description of monitoring boundaries on multiple scales for the different outcomes; event accrual since trial initiation; probabilities of stopping early for potential harm, non-efficacy, etc.; an unconditional power for intention-to-treat and per-protocol analyses; calendar time to crossing a monitoring boundary or reaching the target number of endpoints if no boundary is crossed; trial duration; unconditional power for comparing treatment efficacies; and the distribution of the number of endpoints within an arbitrary study time interval (e.g., events occurring after the treatments/vaccinations are given), useful as input parameters for the design of studies of the association of biomarkers with a clinical outcome (surrogate endpoint problem). The code can be used for a single active treatment versus control design and for a single-stage design.

Authors:Michal Juraska [aut, cre], Doug Grove [aut], Xuesong Yu [ctb], Peter Gilbert [ctb], Stephanie Wu [ctb]