I developed a cox model based on rna-seq datasets. To assess the performance of the model, I applied model to patients and calculated a risk score for every patients. Then we divided the patients into a high risk and low risk group (the median value of all risk score was cutoff value). I applied KM analysis (log-rank test) to these 2 group. Next, I applied the ROC analysis to the model. In my opinion, I believed a good model should have a log-rank test P-value < 0.05 and a large AUC value of ROC analysis (such as >0.70). However, the results were pretty wired and I did not know how to explain them. The P-value of log-rank test were more than 0.05, but the AUC value of ROC was more than 0.70. The figures could be seen as follow.
Is there somebody who can help me understand this result?? I really need your help. Many thanks!!