After the escalator: Narrative review of biomarker-guided asthma care

Asthma, the most common chronic respiratory disease, is characterized by variable symptoms, airflow limitation, and airway inflammation. Current management relies largely on a symptom-focused stepwise escalation approach, which often leads to suboptimal outcomes. This review examines how type 2 inflammatory biomarkers-blood eosinophils and fractional exhaled nitric oxide-can complement symptom-based assessment to optimize care pathways. We synthesize evidence for biomarker-guided management across 5 critical decision points: diagnostic triage, inhaled corticosteroid initiation and dose escalation, acute attack phenotyping, and biologic selection. Across trials and observational cohorts, biomarker-high patients derived substantially greater benefit from inhaled corticosteroid-based therapy, while biomarker-low patients had a worse benefit-harm profile. Each section is balanced by a review of data that are not in favor of biomarker-based management. Indeed, tests for type 2 inflammation may be criticized in terms of accessibility or variability and require threshold validation. Nevertheless, the accumulated evidence suggests that future trials and studies of biomarker integration into diagnostic and treatment pathways may help streamline management for the most at-risk patients, from diagnosis to treatment intensification. The analogy of "fast and slow lanes" for diagnostic and treatment algorithms is developed. The utility of alternative treatable traits, including chronic airway infection, persistent airflow limitation, and breathing pattern disorders, is also explored. The quality and counterpoints of the reviewed evidence emphasize that biomarkers should complement rather than replace comprehensive clinical assessment to optimize care for all phenotypes. Trials and studies of interventions tailored according to blood eosinophils, fractional exhaled nitric oxide, and other key treatable traits are urgently needed across diagnostic and treatment algorithms for asthma.