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

Jiaxuan Wu,1– 5,* Huohuo Zhang,1– 5,* Lan Yang,1– 5,* Jiadi Gan,1– 5 Guoqing Wang,6 Xiaolong Tang,1– 5 Jinghong Xian,1– 5 Lin Zhu,7 Yalun Li,1– 5 Weimin Li1– 5 1Department of Pulmonary and Critical Care Medicine, West China Hospital, State Key Laboratory of Respiratory Health and Multimorbidity, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 2Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 3Precision Medicine Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 4The Research Units of West China, Chinese Academy of Medical Sciences, West China Hospital, Chengdu, Sichuan, People’s Republic of China; 5Institute of Respiratory Health and Multimorbidity, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 6Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, 100084, People’s Republic of China; 7General Office, Cohort Study Center, Institute of Respiratory Health and Multimorbidity, West China Hospital, Sichuan University, Chengdu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Weimin Li, Department of Pulmonary and Critical Care Medicine, West China Hospital, Sichuan University, 37 Guoxue Lane, Wuhou District, Chengdu, Sichuan Province, 610041, People’s Republic of China, Email [email protected] Yalun Li, Department of Pulmonary and Critical Care Medicine, West China Hospital, Sichuan University, 37 Guoxue Lane, Wuhou District, Chengdu, Sichuan Province, 610041, People’s Republic of China, Email [email protected]: 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.Keywords: pre-chronic obstructive pulmonary disease, nomogram, prediction model, progression, prevention