SNOT-22-based clusters in chronic rhinosinusitis without nasal polyposis exhibit distinct endotypic and prognostic...

Endotypic and prognosticating features of chronic rhinosinusitis without nasal polyposis (CRSsNP) are poorly understood. Our objectives were to use an unbiased symptom-based approach to: (1) study symptoms, clinical and endotypic features; and (2) identify features predicating outcomes from endoscopic sinus surgery (ESS).

Clinical, computed tomography (CT), histopathology, and 22-item Sino-Nasal Outcome Test (SNOT-22) data was collected on 146 adult CRSsNP patients who underwent ESS. Unsupervised network modeling of presurgical SNOT-22 scores was performed to classify symptom-based clusters. Subject characteristics and post-ESS SNOT-22 scores were compared between clusters.

Baseline characteristics of the subject population were as follows: females, 56.2%; revision ESS status in 35%; asthma prevalence, 32.6%; median Lund-Mackay CT score, 8; and median SNOT-22 total score, 43. Network mapping and unsupervised clustering of preoperative SNOT-22 scores revealed 4 clusters: (A) severely burdened with high scores in all 4 subdomains; (B) moderately burdened with high scores in the rhinologic subdomain; (C) moderately burdened with high scores in psychological-sleep subdomains; and (D) mildly burdened. The number of previous ESS and asthma prevalence differed significantly between clusters; CT scores were similar. Asthma burden and tissue eosinophilia were greatest in cluster A (p = 0.03). All groups showed significant improvement at 3 months post-ESS (p < 0.0001). At 6 months, patients in cluster C tended to worsen.

SNOT-22-based network modeling of CRSsNP patients yielded 4 clusters with distinct features. Asthma prevalence and tissue eosinophilia were highest in the cluster with highest SNOT-22 scores. All patients showed significant improvement from ESS at 3 months; those with high sleep-psychosocial symptoms tended to show worsening at 6 months.