Patient-Reported Outcome Measures as Predictive Tools for Disease Control in Chronic Rhinosinusitis With Nasal...

Area of Science:

• Otolaryngology
• Medical Informatics
• Surgical Outcomes Research

Background:

• Chronic rhinosinusitis with nasal polyps (CRSwNP) significantly impacts quality of life.
• Current patient-reported outcome measures (PROMs) have limited predictive value for long-term postoperative disease control.
• Effective disease control is the primary goal in CRSwNP management.

Purpose of the Study:

• To evaluate postoperative recovery in CRSwNP patients.
• To identify predictors of suboptimal disease control after functional endoscopic sinus surgery (FESS).
• To integrate preoperative PROMs with objective clinical features for improved prediction.

Main Methods:

• Prospective follow-up study of 102 CRSwNP patients undergoing FESS.
• Comparison of preoperative and postoperative PROMs across disease control groups.
• Machine learning models developed using logistic regression, incorporating CRS-PRO scores and clinical predictors.

Main Results:

• Eosinophil and neutrophil counts identified as key objective predictors.
• Logistic regression model integrating CRS-PRO and clinical features achieved an AUC of 0.866.
• The best model demonstrated high accuracy (83.3%), sensitivity (72.7%), and specificity (89.5%).

Conclusions:

• Integrating preoperative CRS-PRO scores with objective clinical parameters accurately predicts suboptimal CRSwNP disease control post-FESS.
• This approach facilitates personalized risk stratification.
• Supports tailored postoperative management strategies for CRSwNP patients.