A Predicted FEV1/FVC Model Based on a Simple Respiratory Questionnaire for Early Diagnosis of COPD in Shimane Cohort, Japan

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Purpose: Early detection of chronic obstructive pulmonary disease (COPD) remains challenging in primary care settings where spirometry is not always available. We aimed to develop a simple questionnaire-based approach to estimate the forced expiratory volume in one second (FEV 1 )/forced vital capacity (FVC) ratio for COPD screening. Patients and Methods: This was a single-center retrospective observational study based on the Shimane cohort. From 2008 to 2014, respiratory questionnaires and spirometry were performed during health check-ups of individuals aged ≥ 40 years. Among 2230 participants who underwent spirometry, 727 current or former smokers without a history of bronchial asthma were included for model development. Multiple regression analysis was used to identify questionnaire items associated with FEV 1 /FVC and to construct a simplified estimation model. Results: Four variables—age, smoking intensity, exertional dyspnea, and paroxysmal dyspnea—were independently associated with FEV 1 /FVC and were incorporated into the model. The model demonstrated modest explanatory power (R2 = 0.136), with no significant lack-of-fit (F = 1.152). Based on these variables, a simple four-item model enabled estimation of FEV 1 /FVC and identification of individuals at risk for airflow limitation. Conclusion: We developed a simple questionnaire-based model to estimate FEV 1 /FVC using four easily obtainable variables. Although the model is exploratory and requires external validation, it may serve as a practical screening tool to identify individuals at risk for COPD in settings where spirometry is not readily available. Plain Language Summary: Chronic obstructive pulmonary disease (COPD) is an important respiratory disease, but the need for spirometry for diagnosis makes early diagnosis difficult in primary care settings. We analyzed data from 727 smokers, selected from 13,280 patients aged 40 years or older, who underwent a respiratory interview and spirometry during an annual check-up. We found statistically significant differences in four parameters: age, smoking index, exertional breathlessness, and paroxysmal breathlessness in COPD patients compared with non-COPD patients. Therefore, we used these parameters to create a four-item-only predictive model for COPD screening. This model can be used to identify patients with possible COPD without spirometry for early diagnosis and appropriate COPD management. Keywords: chronic obstructive pulmonary disease, COPD screening, questionnaire, spirometry, international primary care airways group, IPAG

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