Beyond Classification: Rethinking the Interpretation of Pulmonary Function Tests

Contemporary approaches to pulmonary function test (PFT) interpretation are commonly presented as interpretive strategies; however, in practice, many function primarily as classification frameworks based on predefined thresholds and probabilistic models. This commentary examines the conceptual distinction between classification and interpretation in pulmonary function testing and discusses the limitations of cross sectional, cut-off–based approaches. The inherent constraints of statistical definitions of normality, the continuous nature of lung function, and the presence of clinically relevant risk gradients within the normal range are highlighted. Alternative interpretive frameworks, including longitudinal assessment of lung function trajectories and emerging perspectives from systems medicine and artificial intelligence, are discussed as avenues to enhance contextual, patient-centered interpretation. Ultimately, this work argues that pulmonary function tests should be understood as tools that modify diagnostic probability rather than establish definitive diagnoses, underscoring the central role of clinical judgment in their interpretation.