Cluster analysis and prediction of treatment outcomes for chronic rhinosinusitis

Abstract

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.

Trial registration: ClinicalTrials.gov NCT00799097 NCT01332136.

Keywords: Chronic rhinosinusitis; cluster; outcomes; prediction; quality of life; sinusitis; treatment.

Conflict of interest statement

Conflict(s) of Interest / Financial Disclosures: Zachary M. Soler and Timothy L. Smith are supported for this investigation by a grant from the National Institute on Deafness and Other Communication Disorders (NIDCD), one of the National Institutes of Health, Bethesda, MD (R01 DC005805; PI/PD: TL Smith). Public clinical trial registration (http://www.clinicaltrials.gov) #NCT01332136. Zachary M. Soler is also supported for this investigation by another grant from the NIDCD (R03 DC013651-01). Timothy L. Smith is a consultant for IntersectENT, which is not associated with this manuscript. Zachary M. Soler is a consultant for Olympus, which is not affiliated with this manuscript. Rodney J. Schlosser is supported by grants from OptiNose and IntersectENT, neither are associated with this manuscript. Dr. Schlosser is also a consultant for Olympus and Arrinex which are not affiliated with this study.

Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1

Clinical algorithm used to define clusters. The above algorithm was used to classify patients into the 5 statistical clusters using simple clinical measures. Productivity loss is the number of work days missed in the last 90 days. SNOT-22 = 22-item Sino-Nasal Outcome Test; Yr = years of age. Property of MUSC Rhinology.

Figure 2

SNOT-22 and RSDI overall outcomes between clusters treated with surgery or continuing medication only. SNOT-22 = 22-item Sino-Nasal Outcome Test; RSDI = Rhinosinusitis Disability Index *=p-value

Figure 3

SNOT-22 outcomes by individual domain between clusters treated with surgery or continuing medication only. SNOT-22 = 22-item Sino-Nasal Outcome Test; *=p-value

Figure 4

RSDI outcomes by subscale score between clusters treated with surgery or continuing medication only. RSDI = Rhinosinusitis Disability Index; *=p-value