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

Abstract

Introduction: Chronic 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.

Objectives: To 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.

Methods: This 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.

Results: Modified-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).

Conclusion: A "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.