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. 2017 Nov-Dec;5(6):1582-1588.e3.
doi: 10.1016/j.jaip.2017.04.009. Epub 2017 May 10.

Lack of Efficacy of Symptoms and Medical History in Distinguishing the Degree of Eosinophilia in Nasal Polyps

John W Steinke  1 , Anna R Smith  1 , Delaney J Carpenter  2 , James T Patrie  3 , Spencer C Payne  4 , Larry Borish  5
Affiliations

Lack of Efficacy of Symptoms and Medical History in Distinguishing the Degree of Eosinophilia in Nasal Polyps

John W Steinke et al. J Allergy Clin Immunol Pract. 2017 Nov-Dec.

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.

Keywords: CT scan; Chronic rhinosinusitis; Eosinophils; Nasal polyps; Sinonasal outcome test.

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Conflict of interest statement

Conflicts of interest: J. W. Steinke has received research support from the National Institutes of Health; has received lecture fees from the American Academy of Allergy, Asthma & Immunology; and receives royalties for the LUVA cell line. S. Payne has received consultancy fees from Acclarent, Medtronic, and Cook; has provided expert testimony for various legal firms; has received research support from Allakos and Knopp Bioscience; and receives royalties from Jaypee Publishing. L. Borish has received research support from the National Institutes of Health and is on the American Board of Allergy and Immunology. The rest of the authors declare that they have no relevant conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Tissue eosinophil distribution in NP samples. Eosinophils were counted in ten 400× hpfs. Distribution of the cohort as a function of average (A) and peak (B) expression is displayed. For the distribution of eosinophil numbers in Figure 1, A and B, (indicates inclusion of that number and) indicates less than that number.
FIGURE 2
FIGURE 2
Correlation of total SNOT-22 scores with tissue eosinophilia. Correlation of total SNOT-22 scores with average (A) and peak (B) NP eosinophil counts is displayed. The Spearman rank correlation coefficient for the relationship in Figure 2, A, is 0.16 (95% CI, −0.09 to 0.40; P =.195) and the Spearman rank correlation coefficient for the relationship in Figure 2, B, is 0.17 (95% CI, −0.09 to 0.40; P = .189).
FIGURE 3
FIGURE 3
Correlation of clinical biomarkers with tissue eosinophilia. AEC (A), total serum IgE (B), and LMS (C) as a function of tissue average eosinophil tertile. Blue circles identify the geometric mean (GM), and vertical lines identify the GM 95% CI. P values are for the null hypothesis test that there are no tertile-to-tertile differences in the GM of the distribution. LMS, Lund-Mackay score.
FIGURE 4
FIGURE 4
Correlation of postoperative improvement with tissue eosinophilia. Postoperative improvement in SNOT-22 scores as a function of average (A; rs = −0.13; 95% CI, −0.39 to 0.15; P =.345) and peak (B; rs = −0.12; 95% CI, −0.37 to 0.16; P =.394) tissue eosinophilia.
See this image and copyright information in PMC

Comment in

  • Nasal Polyps and Biomarkers.
    Naclerio RM, Baroody FM, Pinto JM. Naclerio RM, et al. J Allergy Clin Immunol Pract. 2017 Nov-Dec;5(6):1589-1590. doi: 10.1016/j.jaip.2017.05.007. J Allergy Clin Immunol Pract. 2017. PMID: 29122157 No abstract available.

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