Dataset Information

Novel scoring system and algorithm for classifying chronic rhinosinusitis: the JESREC Study.

ABSTRACT:

Background

Chronic rhinosinusitis (CRS) can be classified into CRS with nasal polyps (CRSwNP) and CRS without nasal polyps (CRSsNP). CRSwNP displays more intense eosinophilic infiltration and the presence of Th2 cytokines. Mucosal eosinophilia is associated with more severe symptoms and often requires multiple surgeries because of recurrence; however, even in eosinophilic CRS (ECRS), clinical course is variable. In this study, we wanted to set objective clinical criteria for the diagnosis of refractory CRS.

Methods

This was a retrospective study conducted by 15 institutions participating in the Japanese Epidemiological Survey of Refractory Eosinophilic Chronic Rhinosinusitis (JESREC). We evaluated patients with CRS treated with endoscopic sinus surgery (ESS), and risk of recurrence was estimated using Cox proportional hazard models. Multiple logistic regression models and receiver operating characteristics curves were constructed to create the diagnostic criterion for ECRS.

Results

We analyzed 1716 patients treated with ESS. To diagnose ECRS, the JESREC scoring system assessed unilateral or bilateral disease, the presence of nasal polyps, blood eosinophilia, and dominant shadow of ethmoid sinuses in computed tomography (CT) scans. The cutoff value of the score was 11 points (sensitivity: 83%, specificity: 66%). Blood eosinophilia (>5%), ethmoid sinus disease detected by CT scan, bronchial asthma, aspirin, and nonsteroidal anti-inflammatory drugs intolerance were associated significantly with recurrence.

Conclusion

We subdivided CRSwNP in non-ECRS, mild, moderate, and severe ECRS according to our algorithm. This classification was significantly correlated with prognosis. It is notable that this algorithm may give useful information to clinicians in the refractoriness of CRS before ESS or biopsy.

SUBMITTER: Tokunaga T

PROVIDER: S-EPMC5032997 | biostudies-literature |

REPOSITORIES: biostudies-literature

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