BiostatisticsGlossary Term
ICH E9(R1) Section 5.5
A range of values calculated from study data that is expected to contain the true treatment effect with a specified probability, typically 95%, providing information about both the estimated effect size and the precision of that estimate.
Confidence intervals provide a richer description of study results than p-values alone by indicating both the direction and magnitude of observed effects and the uncertainty surrounding those estimates. A 95% confidence interval represents a range such that if the study were repeated many times using the same methodology, approximately 95% of the calculated intervals would contain the true parameter value. The width of the interval reflects the precision of the estimate, with narrower intervals indicating more precise estimation.
Interpretation of confidence intervals in clinical trials typically focuses on whether the interval includes clinically important values, particularly the null value representing no effect. When the 95% confidence interval excludes the null value, the result is statistically significant at the 0.05 level. However, confidence intervals provide additional information beyond significance testing by indicating the range of effects consistent with the observed data. An interval that excludes the null but lies entirely within a range of clinically trivial effects suggests statistical significance without clinical importance.
The boundaries of confidence intervals help assess the plausibility of clinically meaningful effects. When designing non-inferiority or equivalence trials, confidence intervals are directly compared against pre-specified margins defining acceptable performance. In superiority trials, the lower bound of the confidence interval indicates the smallest treatment benefit consistent with the data, enabling assessment of whether the treatment effect is likely to be clinically worthwhile even at the lower end of the plausible range.
Efficacy assessment
"The treatment reduced the event rate by 25%, with a 95% confidence interval of 15% to 35%, indicating that the true reduction is highly likely to be between 15% and 35% and is almost certainly clinically meaningful."
Non-inferiority margin
"The 95% confidence interval for the difference between treatments was -2% to +4%; because the lower bound did not exceed the pre-specified non-inferiority margin of -5%, non-inferiority was established."
A statistical analysis strategy that includes all randomized participants in the groups to which they were originally assigned, regardless of whether they completed the study treatment or adhered to the protocol.
A planned statistical analysis conducted before all participants have completed the study, typically to evaluate accumulating data for evidence of efficacy, futility, or safety concerns that might warrant early termination of the trial.
The probability of obtaining results at least as extreme as those observed in the study, assuming that the null hypothesis of no treatment effect is true.
A statistical analysis that includes only participants who completed the study according to protocol requirements, without major protocol violations, adequate treatment exposure, and complete outcome assessments.
The primary endpoint is the main outcome measure used to evaluate whether the treatment hypothesis is supported and forms the basis for regulatory approval decisions, while secondary endpoints provide supportive evidence and characterize additional treatment effects.
ICH E9(R1) Section 5.5
A range of values calculated from study data that is expected to contain the true treatment effect with a specified probability, typically 95%, providing information about both the estimated effect size and the precision of that estimate.
Confidence intervals provide a richer description of study results than p-values alone by indicating both the direction and magnitude of observed effects and the uncertainty surrounding those estimates. A 95% confidence interval represents a range such that if the study were repeated many times using the same methodology, approximately 95% of the calculated intervals would contain the true parameter value. The width of the interval reflects the precision of the estimate, with narrower intervals indicating more precise estimation.
Interpretation of confidence intervals in clinical trials typically focuses on whether the interval includes clinically important values, particularly the null value representing no effect. When the 95% confidence interval excludes the null value, the result is statistically significant at the 0.05 level. However, confidence intervals provide additional information beyond significance testing by indicating the range of effects consistent with the observed data. An interval that excludes the null but lies entirely within a range of clinically trivial effects suggests statistical significance without clinical importance.
The boundaries of confidence intervals help assess the plausibility of clinically meaningful effects. When designing non-inferiority or equivalence trials, confidence intervals are directly compared against pre-specified margins defining acceptable performance. In superiority trials, the lower bound of the confidence interval indicates the smallest treatment benefit consistent with the data, enabling assessment of whether the treatment effect is likely to be clinically worthwhile even at the lower end of the plausible range.
Efficacy assessment
"The treatment reduced the event rate by 25%, with a 95% confidence interval of 15% to 35%, indicating that the true reduction is highly likely to be between 15% and 35% and is almost certainly clinically meaningful."
Non-inferiority margin
"The 95% confidence interval for the difference between treatments was -2% to +4%; because the lower bound did not exceed the pre-specified non-inferiority margin of -5%, non-inferiority was established."
A statistical analysis strategy that includes all randomized participants in the groups to which they were originally assigned, regardless of whether they completed the study treatment or adhered to the protocol.
A planned statistical analysis conducted before all participants have completed the study, typically to evaluate accumulating data for evidence of efficacy, futility, or safety concerns that might warrant early termination of the trial.
The probability of obtaining results at least as extreme as those observed in the study, assuming that the null hypothesis of no treatment effect is true.
A statistical analysis that includes only participants who completed the study according to protocol requirements, without major protocol violations, adequate treatment exposure, and complete outcome assessments.
The primary endpoint is the main outcome measure used to evaluate whether the treatment hypothesis is supported and forms the basis for regulatory approval decisions, while secondary endpoints provide supportive evidence and characterize additional treatment effects.