Cluster analysis and prediction of treatment outcomes for chronic rhinosinusitis
- Zachary M Soler 1, J Madison Hyer 2, Luke Rudmik 3, Viswanathan Ramakrishnan 2, Timothy L Smith 4, Rodney J Schlosser 1
- Zachary M Soler 1, J Madison Hyer 2, Luke Rudmik 3
- 1Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, SC.
- 2Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC.
- 3Division of Otolaryngology-Head and Neck Surgery, Department of Surgery, University of Calgary, Calgary, Alberta, Canada.
- 4Department of Otolaryngology-Head and Neck Surgery, Oregon Health Sciences University, Portland, Ore.
- 0Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, SC.
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View abstract on PubMed
Summary
This summary is machine-generated.Discriminant analysis identified chronic rhinosinusitis (CRS) patient subgroups. Surgery improved outcomes for three of five CRS clusters, offering prognostic value for treatment decisions.
Area Of Science
- Otolaryngology
- Medical Informatics
- Clinical Prognostication
Background
- Current chronic rhinosinusitis (CRS) classifications lack prognostic utility for treatment outcomes.
- Novel CRS phenotypic subgroups identified via discriminant analysis require prognostic validation.
- Prognostic value of discriminant analysis for CRS treatment selection is unknown.
Purpose Of The Study
- To determine if discriminant analysis can predict treatment outcomes.
- To assess prognostication in CRS patients choosing surgery versus medical management.
- To evaluate discriminant analysis for guiding CRS treatment decisions.
Main Methods
- Prospective, multi-institutional study of 690 CRS patients with failed initial medical therapy.
- Patients self-selected continued medical management or surgical treatment.
- Discriminant analysis clustered patients into 5 groups using Sino-Nasal Outcome Test-22 (SNOT-22) score, age, and missed productivity; outcomes tracked for 18 months.
Main Results
- Three of five clusters showed significantly improved SNOT-22 outcomes with surgery compared to continued medical management (mean improvement of 21.2 points at 6 months).
- Surgical benefits were sustained at 18 months follow-up.
- Two clusters demonstrated similar outcomes regardless of treatment choice (surgery vs. medical management).
Conclusions
- Simplified discriminant analysis using key clinical variables effectively clusters CRS patients.
- This analysis provides valuable prognostic information for surgical versus medical management decisions in CRS.
- The findings support using discriminant analysis for personalized CRS treatment strategies.
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