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Currently, I am trying to extract the HR and 95% CI from a kaplan meier curve (used DigitizeIt plus the spreadsheet provided by Tierney et al)

[Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials. 2007 Dec;8(1):16.]

Copy of KM curve here:KM Curve. I'm comparing the yellow and blue curves

I'm comparing the yellow and blue curves. In the main paper the authors state that the logrank test has found the difference in curves to be significant p=0.03.

I then proceeded to trace the KM curve and input the datapoints into the spreadsheet provided by Tierney et al. The resultant HR between the curves was 1.47(0.85-2.53), the p value will not be significant in this instance.

So then my question is: Is it plausible for the p-values to be divergent in both the logrank and the cox regression? If so, what does that mean?

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  • $\begingroup$ The differences of the curves when? The test of $H_{0}: \hat{S_{A}}(t) = \hat{S_{B}}(t)$ for groups $A$ and $B$ using the Kaplan-Meier estimators is specific to a time $t$, not for two survival functions across all times. (Notice that for the first few time periods the blue and yellow curves have identical survival). $\endgroup$ – Alexis Apr 24 '18 at 19:25
  • $\begingroup$ How did you deal with the censored observations when you traced the curves? Was there a separate table of numbers at risk at different times? Also, what hazard ratio, if any, did the authors report for the yellow versus blue curve? $\endgroup$ – EdM Apr 24 '18 at 20:00

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