A Systematic Review of Multidimensional Predictors for Refractory Chronic Rhinosinusitis: Clinical, Systemic and Local Insights.

Abstract

The identification of predictive markers for refractory chronic rhinosinusitis with nasal polyps (RCRSwNP) is essential for advancing precision medicine. In this review, we systematically reviewed the literature on the predictive value of clinical characteristics and biomarkers for RCRSwNP, aiming to better understand current findings and support medical therapy for these patients. PubMed, EMBASE, The Cochrane Library, and Web of Science were searched from data inception until June 2024. The titles and abstracts of 6934 publications were screened, and finally, 54 eligible studies encompassing 450 markers, with categories including clinical characteristics, biomarkers, and multi-marker panels (combinations of multiple markers to predict outcomes of CRSwNP) were evaluated. Data extraction and quality control were performed by two authors independently. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool was used to assess the risk of bias of included studies. Markers were categorized by specimen type (systemic [in blood] vs. local [in nasal polyp tissues vs. in noninvasive samplings]) and analysis method (receiver operating characteristic-based vs. group comparison-based). Most markers demonstrated satisfactory diagnostic performance. Among demographic and clinical characteristics, the E/M ratio showed the highest diagnostic accuracy (area under the curve [AUC] = 0.947). Biomarkers derived from nasal polyp tissues-particularly Charcot-Leyden crystals (CLCs), and eosinophil counts or percentages, achieved high AUCs (up to 0.973). Noninvasive local markers, including cystatin SN and galectin-10 protein levels in nasal secretions and CLC mRNA levels in nasal brushings, also showed strong predictive potential (AUCs > 0.930). Over 90% of the multi-marker panels that integrated multiple markers demonstrated moderate to high predictive accuracy (AUCs > 0.700). This systematic review highlights critical predictors and their implications for the diagnosis and management of RCRSwNP, and emphasizes the need for standardized methodologies, larger cohorts, and validation studies to refine the predictive utility of these markers. Future advances in multi-omics technologies and noninvasive sampling methods may further enhance the precision of RCRSwNP prediction, paving the way for improved therapeutic strategies.