John W Steinke1, Anna R Smith1, Delaney J Carpenter2, James T Patrie3, Spencer C Payne4, Larry Borish5. 1. Department of Medicine, University of Virginia Health Systems, Charlottesville, Va. 2. Department of Otolaryngology, University of Virginia Health Systems, Charlottesville, Va. 3. Department of Public Health Science, University of Virginia Health Systems, Charlottesville, Va. 4. Department of Medicine, University of Virginia Health Systems, Charlottesville, Va; Department of Otolaryngology, University of Virginia Health Systems, Charlottesville, Va. 5. Department of Medicine, University of Virginia Health Systems, Charlottesville, Va; Department of Microbiology, University of Virginia Health Systems, Charlottesville, Va. Electronic address: lb4m@virginia.edu.
Abstract
BACKGROUND: Distinguishing eosinophilic nasal polyps (NP) from noneosinophilic NP will impact prognosis and therapeutic responsiveness. OBJECTIVE: To investigate the ability of clinical history and biomarkers to distinguish these conditions. METHODS: A total of 74 consecutive patients undergoing surgery for NP were enrolled. Clinical presentations were evaluated using the 22-item sinonasal outcome test (SNOT-22). Biomarkers included absolute eosinophil count, IgE, and extent of tissue hyperplasia on sinus computed tomography scan. Tissue eosinophilia was quantified in 10 random hpf and data analyzed addressing both peak and average results. RESULTS: No component of the SNOT-22 was predictive of tissue eosinophilia. Similarly, a medical history of allergic rhinitis, asthma, or aspirin-exacerbated respiratory disease was not predictive. An absolute eosinophil count of more than 300 was associated with NP tissue eosinophilia. In contrast, neither IgE nor extent of sinus computed tomography hyperplasia was predictive. CONCLUSIONS: The ability to individualize therapies for NP is dependent on identifying clinical features or biomarkers of eosinophilia. However, with the exception of circulating eosinophilia, we could not identify a clinical feature or biomarker that robustly predicted the presence of tissue eosinophilia. Even more problematic, even the seeming "criterion standard" determination of tissue pathology was of limited value, as our cohort displayed a continuous spectrum of tissue eosinophil expression, making arbitrary any definitive cutoff distinguishing these conditions.
BACKGROUND: Distinguishing eosinophilic nasal polyps (NP) from noneosinophilic NP will impact prognosis and therapeutic responsiveness. OBJECTIVE: To investigate the ability of clinical history and biomarkers to distinguish these conditions. METHODS: A total of 74 consecutive patients undergoing surgery for NP were enrolled. Clinical presentations were evaluated using the 22-item sinonasal outcome test (SNOT-22). Biomarkers included absolute eosinophil count, IgE, and extent of tissue hyperplasia on sinus computed tomography scan. Tissue eosinophilia was quantified in 10 random hpf and data analyzed addressing both peak and average results. RESULTS: No component of the SNOT-22 was predictive of tissue eosinophilia. Similarly, a medical history of allergic rhinitis, asthma, or aspirin-exacerbated respiratory disease was not predictive. An absolute eosinophil count of more than 300 was associated with NP tissue eosinophilia. In contrast, neither IgE nor extent of sinus computed tomography hyperplasia was predictive. CONCLUSIONS: The ability to individualize therapies for NP is dependent on identifying clinical features or biomarkers of eosinophilia. However, with the exception of circulating eosinophilia, we could not identify a clinical feature or biomarker that robustly predicted the presence of tissue eosinophilia. Even more problematic, even the seeming "criterion standard" determination of tissue pathology was of limited value, as our cohort displayed a continuous spectrum of tissue eosinophil expression, making arbitrary any definitive cutoff distinguishing these conditions.
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