The predictive utility of the 22‐item sino‐nasal outcome test (SNOT‐22): A scoping review. Issue 1 (28th September 2021)

• Record Type: Journal Article
• Authors: Liu, Matthew; Liu, Jeremy; Weitzel, Erik K.; Chen, Philip G.
• Is Part Of: International forum of allergy & rhinology. Volume 12:Issue 1(2022)
• Page Start: 83
• Page End: 102
• Publication Date: 2021-09-28
• Subjects: diagnosis -- forecasting -- outcome assessment -- quality of life -- sinusitis; 617.51005
• DOI: 10.1002/alr.22888
• Languages: English
• ISSNs: 2042-6976

Abstract

Abstract: Background: The 22‐item sino‐nasal outcome test (SNOT‐22) is a widely used and powerful patient‐reported outcomes measure for chronic rhinosinusitis (CRS). More recently; however, the SNOT‐22 has been evaluated as a predictive tool for multiple conditions. The objective of this scoping review is to investigate the extent to which SNOT‐22 is used in this manner and present this information in a way useful for clinicians. Methods: A systematic search of PubMed, Scopus, Cochrane Library, and Web of Science was performed. Studies that evaluated SNOT‐22s predictive utility were considered for eligibility in this scoping review. Results: A total of 39 studies met eligibility. The SNOT‐22 was found to be used as a predictive tool in three broad categories: (1) to predict a diagnosis, (2) to predict an outcome of an intervention, and (3) to predict a patient treatment preference. Thirteen studies were included in the diagnosis category, which made up ten different individual predictions. Twenty‐four studies were included in the outcomes category and investigated 17 different individual predictions. Finally, two studies were included in the patient preferences category, which together made one prediction. Conclusions: The SNOT‐22 is a versatile tool that has the potential to be used in predicting various diagnoses, outcomes, and patient preferences. However, care must be taken in applying these predictions to clinical practice, as further research must be done in validating these predictions based on SNOT‐22 responses.