Learn why hazard ratio confidence intervals crossing 1 indicate non-significant survival differences in clinical trials. Essential for Pharma Data Science certification exam prep.
Table of Contents
Question
What does it mean if confidence intervals for hazard ratios cross 1?
A. The survival difference is significant
B. The new treatment is definitely better
C. The new treatment is definitely worse
D. The survival difference is not significant
Answer
D. The survival difference is not significant
Explanation
When the confidence interval for hazard ratios includes the value 1, it suggests that the survival difference is not statistically significant. This means we cannot confidently say there is a difference in survival between the groups being compared.
When confidence intervals (CIs) for hazard ratios (HRs) cross 1, it means the observed survival difference between groups is not statistically significant. Here’s why:
Hazard Ratio Basics
HR compares the instantaneous risk of an event (e.g., death, relapse) between two groups.
HR = 1: No difference in risk.
HR < 1: Lower risk in the treatment group. HR > 1: Higher risk in the treatment group.
Role of Confidence Intervals
CIs reflect the precision of the HR estimate. A 95% CI means we are 95% confident the true HR lies within this range.
If the CI includes 1: The true HR could plausibly be 1, indicating no meaningful difference in survival between groups. The result is not statistically significant.
Example: An HR of 0.8 (CI: 0.6–1.2) suggests the treatment might reduce risk by 20%, but the CI’s inclusion of 1 means this effect could be due to chance.
Why Other Options Are Incorrect
A (Significant difference): Requires the CI to exclude 1 entirely (e.g., CI: 0.5–0.9).
B/C (Definitely better/worse): Statistical significance ≠ clinical certainty. CIs quantify uncertainty, not definitive outcomes.
Practical Implications
A non-significant HR (CI crossing 1) means the treatment effect is inconclusive. Further research or larger sample sizes may clarify the relationship.
Always interpret HRs alongside CIs, median survival times, and clinical context.
Data Science with Real World Data in Pharma certification exam assessment practice question and answer (Q&A) dump including multiple choice questions (MCQ) and objective type questions, with detail explanation and reference available free, helpful to pass the Data Science with Real World Data in Pharma exam and earn Data Science with Real World Data in Pharma certification.