Treatment escalation and sustained disease control in chronic rhinosinusitis: a retrospective surgical cohort study

医学 降级 回顾性队列研究 疾病 队列 队列研究 外科 急诊医学 梅德林 入射(几何) 背景(考古学) 重症监护医学
作者
M Clari-Comes,D Martin-Jimenez,R Moreno-Luna,M Gonzalez-Garcia,A Cuvillo,I Alobid,S Sanchez-Gomez
出处
期刊:Rhinology [European Rhinologic Society]
标识
DOI:10.4193/rhin25.301
摘要

BACKGROUND: The impact of endoscopic sinus surgery (ESS) extent on long-term disease control and therapeutic escalation in chronic rhinosinusitis with nasal polyps (CRSwNP) remains unclear. This study aims to evaluate the clinical applicability of endoscopy-based criteria for therapeutic escalation and to determine the impact of surgical extent on the risk and timing of treatment intensification. METHODS: A retrospective cohort study with 3-year follow-up was conducted. CRSwNP patients who underwent ESS were included and classified according to Lamella Ostium Extent Mucosa (LOEM) system (t1â€"t4). Baseline characteristics and disease severity measures were assessed. Therapeutic escalation was defined by endoscopic criteria. Predictors of escalation and the effect of ESS extent on escalation timing across clinical phenotypes were analyzed using multivariate logistic regression, Kaplan-Meier curves and Cox regressions. RESULTS: In the overall sample (n=172), patients who required escalation showed higher SNOT-22 scores and poorer olfactory function. More extensive ESS (LOEM t3â€"t4) was associated with significantly reduced escalation risk and prolonged disease control. Post hoc analyses confirmed significant pairwise differences favoring extensive (t3â€"t4) over limited (t1â€"t2) surgery. Subgroup analyses demonstrated greater benefits in older subjects, atopic patients, revision surgeries and patients with eosinophils >300cells/μL. Higher baseline SNOT-22 scores remained an independent predictor of escalation after ESS. CONCLUSIONS: Surgical extent appears to influence both escalation risk and timing. More extensive ESS may provide more sustained control, particularly in revision cases and biomarker-defined subgroups, supporting its integration into personalized algorithms.
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