East SURVIVAL

Survival Endpoints with East SURVIVAL

Trial designs for survival studies present a range of complex challenges. Since statistical power in these studies is measured in events observed, practical realities like patient drop-outs, inconstant rates of patient accrual, and variable follow-ups, can pose substantial problems for calculating power.

East SURVIVAL has a range of design and simulation tools that anticipate these challenges and strengthen capacities for resolution.

Benefits

East SURVIVAL provides powerful yet simple to use simulation tools that can illustrate complex survival data at the design stage. Design options include superiority and non-inferiority trials with fixed and variable follow-up. Elegant graphs clarify alternatives, making it easy for users to explore tradeoffs between duration and patient accrual, choice of boundaries, spending functions and hazard functions. Easy-to-read charts make these alternatives plain to designers.

Data monitoring is simplified using a single Interim Monitoring Dashboard which clearly specifies study details and interim statistics. The Dashboard also displays charts for nominal critical points, error spending and conditional power.

During interim and final looks, East SURVIVAL provides fixed sample size and group sequential hypothesis testing. It also displays Monte Carlo averages of follow-up time, and cumulative accruals, events and drop-outs, for each arm of the trial.

Features

  • Non-uniform accrual
  • Variable subject drop-outs
  • Variable and fixed subject follow-up
  • Piecewise exponential hazard rates
  • Lagged treatment effects and other non-proportional hazards scenarios
  • Option to specify accrual & study duration or accrual rate & sample size
  • Multiple survival and drop-out parameter input methods
  • Interactive event rate charts to predict accrual and accumulation of events over time
  • Power charts based on sample size, accrual duration, study duration and number of events
  • Stratified sampling and stratified Logrank Test
  • Go no-go based survival simulations with survival and binary intermediary endpoints