Jeong-Whun Kim1, Gene Huh1, Chae-Seo Rhee1, Chul Hee Lee1, Jaebong Lee2, Jin-Hang Chung3, Sung-Woo Cho1. 1. Department of Otorhinolaryngology-Head and Neck Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, South Korea. 2. Medical Research Collaborating Center, Seoul National University Bundang Hospital, Seongnam, South Korea. 3. Department of Pathology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, South Korea.
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.
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.
Authors: Daniel M Beswick; Timothy L Smith; Jess C Mace; Jeremiah A Alt; Nyssa F Farrell; Vijay R Ramakrishnan; Rodney J Schlosser; Zachary M Soler Journal: Int Forum Allergy Rhinol Date: 2020-06-18 Impact factor: 3.858
Authors: Mauricio Fernandes; Magdalena Schelotto; Philipp Maximilian Doldi; Giovanna Milani; Abul Andrés Ariza Manzano; Doriam Perera Valdivia; Alexandra Marie Winter Matos; Yasmin Hamdy Abdelrahim; Shaza Ahmed Hamad Bek; Benito K Benitez; Vanessa Luiza Romanelli Tavares; Abdulrahim M Basendwah; Luis Henrique Albuquerque Sousa; Naiara Faria Xavier; Tania Zertuche Maldonado; Sarah Toyomi de Oliveira; Melisa Chaker; Michelle Menon Miyake; Elif Uygur Kucukseymen; Kinza Waqar; Ola M J Alkhozondar; Ricardo Bernardo da Silva; Guilhermo Droppelmann; Antonio Vaz de Macedo; Rui Nakamura; Felipe Fregni Journal: F1000Res Date: 2021-01-22