Absolute numbers, not just relative: a 30% relative reduction tells you the ratio but not the practical magnitude. The event rate in each arm and the difference between them tells you how many people benefit.
Interim analyses and stopping rules — does this still hold? posts 31–35
This is a continuation of a long topic, addressed by post number rather than by page. Start at post 1 · go to the accepted answer.
Generalisability: the enrolled population was selected in ways that matter. Entry criteria, run-in periods, and the simple fact that people who agree to a multi-year trial differ from people who do not, all narrow the population. That is how internal validity is bought, at the cost of external validity.
I read post #31 twice before replying, because I had assumed the opposite.
Risk of bias: structured appraisal of internal validity. Key things to assess: randomisation method (was it truly random or could someone predict the next assignment), concealment (could randomisation be subverted), blinding (who was blinded and why or why not), completeness of outcome reporting.
This follows post #31 rather than contradicting it.
Intent-to-treat versus per-protocol: ITT includes everyone assigned regardless of whether they took the drug. Per-protocol includes only those who completed it as intended. The two can give substantially different results.
Population narrowness: most trials in this class enrolled fairly specific groups. Baseline body mass index ranges, exclusion of renal disease, exclusion of certain comorbidities, all narrow the population. Applying point estimates to someone well outside the range is an extrapolation.
This topic was referenced in
- Non-inferiority margins: how they are chosen and how they are abused — a second datasetEvidence › Trials · 37 replies
- Adjudicated events and why the definition matters — the long versionEvidence › Trials · 146 replies
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