logrank test p-value comparing quantile intervals
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7.3 years ago


I'm using the FIREBROWSE platform and I'm trying to replicate the survival analysis described here:


In the description of the method used they reported: " logrank test in univariate Cox regression analysis with proportional hazards model was used to estimate the P values comparing quantile intervals using the 'coxph' function in R. Kaplan-Meier survival curves were plotted using quantile intervals at c(0, 0.25, 0.50, 0.75, 1). If there is only one interval group, it will not try survival analysis."

This description is not really clear to me. I know that I can estimate the logrank p-value using the coxph function, but I can't understand how they used the quantile intervals information.

Sorry if the question is trivial and thanks for your help.

RNA-Seq survival cox logrank R • 2.7k views
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I assume that they used the quantiles of each of their clinical features as the groups for the test.

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Thanks for the comment.

Since they are performing survival analysis looking, ad example, for the correlation with "time to death or last follow up", I've assumed that the grouping was given by the event ("death") of the patient.

My guess was that the quantile was computed on the output (score) of the cox model for each clinical feature. Doing so they define different groups for the Kaplan-Mayer curves from which compute the logrank. But also in this way is not clear how they compute the logrank for multiple curves.


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