What does a 95% Confidence Interval (CI) of -0.35 to 0.30 indicate about the efficacy of a medical intervention?

Interpretation of a 95% Confidence Interval of -0.35 to 0.30

A 95% confidence interval spanning from -0.35 to 0.30 indicates that the intervention has no statistically significant effect and the results are inconclusive, as the interval crosses zero (the null value of no difference). 1, 2

Statistical Significance

• This confidence interval fails to demonstrate statistical significance because it includes zero, meaning we cannot rule out the possibility of no treatment effect 2
• The interval suggests substantial uncertainty about the true effect, ranging from a potential modest harm (-0.35) to a potential modest benefit (+0.30) 1
• According to multiple guideline societies including the American Society of Hematology and European League Against Rheumatism, when a 95% CI crosses the null value (zero for differences, 1.0 for ratios), the result is not statistically significant 2

Clinical Interpretation

• This result should be classified as "inconclusive" rather than demonstrating equivalence or non-inferiority 3
• A common error is to interpret lack of statistical significance as proof that two treatments are equivalent—this is incorrect 1
• The width of this confidence interval (spanning 0.65 units) indicates imprecision in the estimate, which would warrant downgrading the certainty of evidence in GRADE assessments 1

Practical Implications

• The confidence interval provides information about both the precision (width of the interval) and accuracy (relationship to the null value) of the treatment effect 4
• This interval suggests the study may have been underpowered to detect a true difference if one exists 1
• To establish non-inferiority or equivalence, a pre-specified margin would need to be defined, and the entire confidence interval would need to exclude that margin 1
• The result indicates that more research with larger sample sizes is necessary to narrow the confidence interval and determine if a true effect exists 5, 6

Key Pitfalls to Avoid

• Do not conclude the interventions are "equally effective" based solely on a non-significant p-value or a CI crossing zero 1
• Do not ignore the clinical importance of the effect sizes at the boundaries of the interval (-0.35 and +0.30) 3
• Recognize that the width of the CI reflects both sample size and variability in the data 5