{"entity":{"id":"confidence-interval","kind":"term","name":"Confidence interval","aka":["confidence intervals","95% CI","95% confidence interval","95%CI","interval estimate","margin of error"],"tldr":"The range of values consistent with the trial's data, usually given at 95%. A hazard ratio of 0.70 with an interval of 0.55 to 0.89 means the true effect probably lies somewhere in that range; if the range crossed 1.0 the result would not be statistically significant, and an upper end close to 1.0 signals a fragile result.","summary":"Because a trial studies a sample rather than every patient in the world, its estimate carries uncertainty, and the confidence interval expresses it: a narrow interval comes from a large trial with more events, a wide one from a small trial. For a hazard ratio, an interval that excludes 1.0 corresponds to a p-value below 0.05; for a difference in months or percentage points, the interval must exclude zero. Reading the interval rather than just the point estimate shows how large or small the true benefit could plausibly be, and an interval whose upper end is close to 1.0 signals a fragile result even if it is technically significant.","asOf":"2026-09-09","wikipedia":"https://en.wikipedia.org/wiki/Confidence_interval","links":[{"label":"Wikipedia","url":"https://en.wikipedia.org/wiki/Confidence_interval"}],"tags":[],"related":["p-value","hazard-ratio","hazard-ratio-basics","randomised-trial","endpoint","statistical-significance","non-inferiority-margin","absolute-benefit","bayesian-trial-design","sample-size-re-estimation"],"cancers":[],"sections":[],"technologies":[],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":[],"trials":[],"people":[],"bottlenecks":[],"keyPapers":[],"journals":[],"dependsOn":[],"notes":[],"category":"Clinic basics"},"route":"/terms/confidence-interval/","neighbours":{"term":[{"id":"absolute-benefit","kind":"term","name":"Absolute versus relative benefit (number needed to treat)","route":"/terms/absolute-benefit/"},{"id":"bayesian-trial-design","kind":"term","name":"Bayesian trial design","route":"/terms/bayesian-trial-design/"},{"id":"endpoint","kind":"term","name":"Endpoint","route":"/terms/endpoint/"},{"id":"hazard-ratio","kind":"term","name":"Hazard ratio (HR)","route":"/terms/hazard-ratio/"},{"id":"kaplan-meier-curve","kind":"term","name":"Kaplan-Meier curve, censoring and proportional hazards","route":"/terms/kaplan-meier-curve/"},{"id":"median-survival","kind":"term","name":"Median survival","route":"/terms/median-survival/"},{"id":"non-inferiority-margin","kind":"term","name":"Non-inferiority margin and equivalence trials","route":"/terms/non-inferiority-margin/"},{"id":"p-value","kind":"term","name":"P-value","route":"/terms/p-value/"},{"id":"randomised-trial","kind":"term","name":"Randomised trial","route":"/terms/randomised-trial/"},{"id":"hazard-ratio-basics","kind":"term","name":"Reading a hazard ratio","route":"/terms/hazard-ratio-basics/"},{"id":"sample-size-re-estimation","kind":"term","name":"Statistical power, sample size and re-estimation","route":"/terms/sample-size-re-estimation/"},{"id":"statistical-significance","kind":"term","name":"Statistical significance (P values, alpha, multiplicity)","route":"/terms/statistical-significance/"}]}}