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A trial's results are not one event but a series: pre-planned looks at the data (interim analyses) while it is still running, a data cut-off date that freezes the dataset for each look, a 'topline' announcement of the headline numbers, and a final analysis when enough events have happened.
Time-to-event trials are 'event-driven': analyses occur after a set number of progressions or deaths, so timing depends on how fast events accrue, and companies announce 'readouts' when those milestones arrive. Interim analyses use alpha-spending so that repeated looks do not inflate false positives; a positive interim for progression-free survival often comes years before the final overall survival analysis. Topline press releases precede peer-reviewed publication by months and may omit key details, which is why the site distinguishes press-release from published evidence. The data cut-off, not the publication date, is the date the numbers describe.
Shares Futility analysis (stopped for futility), Statistical power, sample size and re-estimation, Data monitoring committee (DSMB, IDMC).
Shares Futility analysis (stopped for futility), Data monitoring committee (DSMB, IDMC), Seamless, adaptive and Bayesian trial designs, STAMPEDE.
Shares Futility analysis (stopped for futility), Data monitoring committee (DSMB, IDMC), Group sequential design, stopping rules and alpha spending.
Shares Data monitoring committee (DSMB, IDMC), Group sequential design, stopping rules and alpha spending, Primary, secondary and co-primary endpoints, Trial lifecycle: from protocol to label.
Shares Futility analysis (stopped for futility), Data monitoring committee (DSMB, IDMC), Group sequential design, stopping rules and alpha spending.
Shares Statistical power, sample size and re-estimation, Data monitoring committee (DSMB, IDMC), Group sequential design, stopping rules and alpha spending, Trial lifecycle: from protocol to label.
Shares Data maturity (immature vs mature survival data), Landmark and milestone survival (5-year survival, median follow-up), ADAURA.
Shares Statistical significance (P values, alpha, multiplicity), Group sequential design, stopping rules and alpha spending.