AUTHOR=Wang Qinqin , Liu Lingjun , Zhang Qiao , Li Hong , Ma Qianli 

TITLE=Dynamic performance and scenario-based screening strategy of six COPD questionnaires: a cross-sectional study with prevalence-driven robustness validation

JOURNAL=Frontiers in Medicine

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1666703

DOI=10.3389/fmed.2025.1666703

ISSN=2296-858X

ABSTRACT=IntroductionChronic Obstructive Pulmonary Disease (COPD) imposes a high global burden. Spirometry is the diagnostic gold standard but has accessibility barriers. Screening questionnaires provide a feasible alternative.ObjectivesTo compare the diagnostic performance and robustness of six COPD screening questionnaires (LFQ: Lung Function Questionnaire; IPAG: International Primary Care Airways Group Questionnaire; Modified-IPAG; COPD-PS: COPD Population Screener Questionnaire; COPD-SQ: COPD Screening Questionnaire; SCSQ: The Salzburg COPD Screening Questionnaire) within a single cohort population, thereby providing evidence to support targeted screening for COPD.MethodsThis cross-sectional study enrolled adults ≥40 years without prior asthma or non-COPD chronic lung diseases. Participants completed six screening questionnaires and spirometry. COPD was confirmed by pulmonologists. Receiver operating characteristic (ROC) curves were constructed for each questionnaire; sensitivity, specificity, accuracy (ACC), positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) were calculated. Dynamic variations in screening performance were simulated under different disease prevalence scenarios.ResultsModified-IPAG and LFQ showed highest sensitivity (94.78%/91.79%) and NPV (98.11%/97.45%); COPD-PS and COPD-SQ had highest specificity (79.32%/87.05%) and PPV (43.50%/43.87%). AUC ranged 0.681 (SCSQ)–0.796 (COPD-PS). Dynamic simulations revealed COPD-PS maintained stable ACC across prevalence (ΔACC = 0.06; β = −0.018; P = 0.114), while SQ declined with increasing prevalence (ΔACC = 0.26; β = −0.263; P < 0.001).ConclusionA “Scenario-Priority” strategy is proposed: For rule-out screening, use high-sensitivity tools (Modified-IPAG/LFQ); for high-risk identification, prioritize robust COPD-PS; in low-prevalence regions (<30%), use high-specificity SQ. This approach transcends the conventional “tool-first” static framework, delivering evidence-based support for precision COPD screening implementation.