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. 2019 Jan;9(1):79-86.
doi: 10.1002/alr.22221. Epub 2018 Oct 3.

Unsupervised cluster analysis of chronic rhinosinusitis with nasal polyp using routinely available clinical markers and its implication in treatment outcomes

Jeong-Whun Kim  1 , Gene Huh  1 , Chae-Seo Rhee  1 , Chul Hee Lee  1 , Jaebong Lee  2 , Jin-Hang Chung  3 , Sung-Woo Cho  1
Affiliations

Unsupervised cluster analysis of chronic rhinosinusitis with nasal polyp using routinely available clinical markers and its implication in treatment outcomes

Jeong-Whun Kim et al. Int Forum Allergy Rhinol. 2019 Jan.

Abstract

Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a multidimensional disease. In this study, we performed an unsupervised cluster analysis of CRSwNP using routinely available clinical markers.

Methods: We conducted a retrospective review of patients treated with endoscopic sinus surgery due to medically intractable bilateral CRSwNP from 2009 to 2017. Unsupervised cluster analysis was performed using a patient's clinical features, including age, peripheral blood eosinophil, tissue eosinophilia, Lund-Mackay computed tomography (CT) scores, ratio of the CT scores for the ethmoid sinus and maxillary sinus (E/M ratio), and comorbid asthma. Tree analysis was performed to develop a clustering algorithm. Kaplan-Meier survival analysis was performed to determine the revision surgery-free probability corresponding to each cluster.

Results: Data were available on 375 patients. Patients were categorized into 6 clusters comprising 2 asthmatic clusters and 4 non-asthmatic clusters. The labels for the 2 asthmatic clusters were: asthmatic non-eosinophilic polyp (cluster A1) and asthmatic eosinophilic polyp (cluster A2). The labels for the 4 non-asthmatic clusters were: non-eosinophilic polyp with older age (cluster NA1); non-eosinophilic pol'yp with younger age (cluster NA2); eosinophilic polyp with lower E/M ratio (cluster NA3); and eosinophilic polyp with higher E/M ratio (cluster NA4). The 4-year revision-free rates were 100% (cluster NA1), 80.3% (NA2), 98.0% (NA3), 66.7% (NA4), 100% (A1), and 66.7% (A2). The clusters showed statistically significant differences in terms of 4-year revision-free rates (log-rank p < 0.05).

Conclusion: Cluster analysis identified 2 asthmatic clusters and 4 non-asthmatic clusters in CRSwNP. Each cluster corresponded to a different clinical outcome.

Keywords: clinical markers; cluster analysis; nasal polyps; sinusitis; treatment outcome.

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