Development and Validation of a Predictive Nomogram for Progression from Pre-COPD to Spirometric COPD: A Multicenter Retrospective Cohort Study

Background: Early identification of Pre-chronic obstructive pulmonary disease (pre-COPD) is vital for preventing irreversible lung damage. However, despite its high prevalence, there is a lack of practical tools to predict which individuals will progress to spirometry-defined COPD. This study aimed to identify independent risk factors and develop a clinical nomogram to quantify the risk of disease progression in a pre-COPD population. Methods: We conducted a multicenter, retrospective cohort study in Southwest China (2019-2023), enrolling 1088 participants with pre-COPD. Baseline data, including demographic information, smoking status, comorbidities, lung function, and hematological and biochemical indicators, were analyzed. Independent predictors were identified via multivariate logistic regression, and a risk-prediction nomogram was constructed and validated. Results: During follow-up, 54.6% of participants progressed to COPD. The final prediction model identified six independent risk factors: age (OR=1.043), hypertension (OR=2.331), diabetes (OR=2.412), hemoglobin level (OR=1.016), lymphocyte count (OR=0.639), and basophil count (OR=1.411). The nomogram demonstrated robust discriminative ability, with an AUC of 0.758 in the training set and 0.718 in the validation set. Calibration curves showed high consistency, and Decision Curve Analysis (DCA) confirmed significant clinical net benefit. Conclusion: Progression from pre-COPD to spirometry-defined COPD is highly prevalent and driven by age, comorbidities, and systemic inflammatory markers. Our validated nomogram provides a precise, non-invasive tool for clinicians to identify high-risk individuals, enabling targeted early intervention and optimized resource allocation in COPD prevention.