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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.