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Figure legends
Figure 1. Postoperative nomogram predicting 1-year probability of uncontrol disease after endoscopic surgery. [A] Each clinical variable has a certain number of points (top row) ranging from 0 to 100. The sum of points of each variable was related to the probability of uncontrol disease at 1 year. [B] An example illustrating the use of the nomogram. This patient was one of the training cohort in the current study. The patient has tissue eosinophil ratio >=10% (points=100), low blood eosinophilia(points=0), no AR(points=0) and Asthma(points=96), thus the total points are 196 and the corresponding risk event of recurrence is 46.11%. AS: asthma; PBEC: peripheral blood eosinophil count; TEN: tissue eosinophil number; TER: tissue eosinophil ratio
Figure 2. [A] ROC curves of the training cohort predicting 1-year probability of uncontrol disease after endoscopic surgery with corresponding AUC values. [B] Calibration in the primary cohort for predicting patient risk of recurrence. The x-axis is nomogram-predicted probability of survival and y-axis is actual survival. The reference line is 45°and indicates perfect calibration. ROC, receiver operating characteristic; AUC, Area under curve; CI, confidence interval AS: asthma; PBEC: peripheral blood eosinophil count; TEN: tissue eosinophil number; TER: tissue eosinophil ratio.
Figure 3. [A] ROC curves of the validation cohort predicting 1-year probability of uncontrol disease after endoscopic surgery with corresponding AUC values. [B] Calibration in the validation cohort for predicting patient risk of recurrence. The x-axis is nomogram-predicted probability of survival and y-axis is actual survival. The reference line is 45°and indicates perfect calibration. ROC, receiver operating characteristic; AUC, Area under curve; CI, confidence interval AS: asthma; PBEC: peripheral blood eosinophil count; TEN: tissue eosinophil number; TER: tissue eosinophil ratio.
Figure 4. [A] Decision curve analyses in the training cohorts: a perfect prediction model (gray line), screen none (horizontal solid black line), and screen based on the nomogram (blue thick dash line). [B] Clinical impact curve of the nomogram plots the number of CRS patients classified as high risk, and the number of cases classified as high risk with uncontrol disease at each high risk threshold.