Cluster analysis and prediction of treatment outcomes for chronic rhinosinusitis

JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY

卷:137

Article

Soler, Zachary M.¹  Hyer, J. Madison²  Rudmik, Luke³  Ramakrishnan, Viswanathan²  Smith, Timothy L.⁴  Schlosser, Rodney J.¹ 

[1] Med Univ S Carolina, Dept Otolaryngol Head & Neck Surg, 135 Rutledge Ave,MSC550, Charleston, SC 29425 USA

[2] Med Univ S Carolina, Dept Publ Hlth Sci, 135 Rutledge Ave,MSC550, Charleston, SC 29425 USA

[3] Univ Calgary, Dept Surg, Div Otolaryngol Head & Neck Surg, Calgary, AB, Canada

[4] Oregon Hlth & Sci Univ, Dept Otolaryngol Head & Neck Surg, Portland, OR USA

关键词: Chronic rhinosinusitis;    sinusitis;    cluster;    quality of life;    treatment;    prediction;    outcomes;   

DOI  :  10.1016/j.jaci.2015.11.019

来源: Elsevier

【 摘 要 】

Background: Current clinical classifications of chronic rhinosinusitis (CRS) have weak prognostic utility regarding treatment outcomes. Simplified discriminant analysis based on unsupervised clustering has identified novel phenotypic subgroups of CRS, but prognostic utility is unknown. Objective: We sought to determine whether discriminant analysis allows prognostication in patients choosing surgery versus continued medical management. Methods: A multi-institutional prospective study of patients with CRS in whom initial medical therapy failed who then self-selected continued medical management or surgical treatment was used to separate patients into 5 clusters based on a previously described discriminant analysis using total Sino-Nasal Outcome Test-22 (SNOT-22) score, age, and missed productivity. Patients completed the SNOT-22 at baseline and for 18 months of follow-up. Baseline demographic and objective measures included olfactory testing, computed tomography, and endoscopy scoring. SNOT-22 outcomes for surgical versus continued medical treatment were compared across clusters. Results: Data were available on 690 patients. Baseline differences in demographics, comorbidities, objective disease measures, and patient-reported outcomes were similar to previous clustering reports. Three of 5 clusters identified by means of discriminant analysis had improved SNOT-22 outcomes with surgical intervention when compared with continued medical management (surgery was a mean of 21.2 points better across these 3 clusters at 6 months, P < .05). These differences were sustained at 18 months of follow-up. Two of 5 clusters had similar outcomes when comparing surgery with continued medical management. Conclusion: A simplified discriminant analysis based on 3 common clinical variables is able to cluster patients and provide prognostic information regarding surgical treatment versus continued medical management in patients with CRS.

【 授权许可】

Free