Journal Article
Multicenter Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
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Practice Pattern Variation in Pediatric Eosinophilic Esophagitis in the Carolinas EoE Collaborative: A Research Model in Community and Academic Practices.

OBJECTIVES: Differences in the initial management of pediatric eosinophilic esophagitis (EoE) by practice setting have not been well characterized. We aimed to characterize these differences for sites in the Carolinas EoE Collaborative (CEoEC), a multicenter network of academic and community practices.

METHODS: We performed a retrospective cohort study of pediatric EoE patients at five CEoEC sites: University of North Carolina (UNC) Hospital, Charlotte Asthma and Allergy Specialists, Greenville Health Systems, Wake Forest Baptist Medical Center, and the Medical University of South Carolina Hospital. Cases of EoE were defined by consensus guidelines. Data were extracted from electronic medical records. We tested for differences among sites and used a multinomial model (polytomous regression) to assess associations between treatment and site, adjusting on patient factors.

RESULTS: We identified 464 children with EoE across the CEoEC sites. The median age was highest at Wake Forest (11.4 years), the median eosinophil count was highest at UNC (69 eos/hpf), and UNC had the most male patients (82%). UNC used topical steroids for initial treatment in 86% of cases, compared with <1% in Greenville ( P < 0.01). Greenville used dietary elimination more frequently than UNC (81% vs 2%, P < 0.01). Differences in treatment approach held after adjusting for potential baseline confounders. There was no significant association between patient factors and initial treatment approach.

CONCLUSIONS: Significant differences in EoE patient factors and treatment approaches were identified across CEoEC sites and were not explained by patient or practice factors. This suggests that institutional or provider preferences drive initial treatment approaches, and that more data are needed to drive best practice decisions.

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