What does a significant log-rank test indicate when comparing survival curves?

• A. It quantifies the exact difference in survival probabilities
• B. It indicates a difference in survival over time but not the size of the difference
• C. It proves causation
• D. It indicates identical survival

Answer: (B)

The log-rank test is used to compare how survival experiences differ across groups over the entire follow-up period. When the result is statistically significant, it means there is evidence that the survival curves are not the same over time—the groups have different survival experiences at some points during follow-up. But the test does not quantify how large that difference is at any time point or overall; it only tells you that a difference exists. To gauge the size or direction of the difference, you’d look at effect measures from other analyses (like hazard ratios from a Cox model) or examine time-specific differences. It also doesn’t imply causation, and a non-significant result doesn’t prove identical survival—just that there isn’t strong evidence of a difference given the data.