ArticleLung2024
Development and Validation of a Screening Tool for Generalized Anxiety and Major Depressive Disorder in Patients with Chronic Obstructive Pulmonary Disease.
Article in Lung, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Machine learning-based identification of anxiety symptoms in Chinese community-dwelling older adults: a comparative study of six algorithms with SHAP analysis and nomogram development.Frontiers in psychiatry · 2026Article
- Development and validation of a risk prediction model for depression in patients with chronic obstructive pulmonary disease.BMC psychiatry · 2025Article
- LUNG Year in Review: 2024.Lung · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
purposeAnxiety and depression are often underdiagnosed in patients with chronic obstructive pulmonary disease (COPD). This study aimed to develop and validate a screening tool for anxiety and depression in COPD patients.
methodsStable COPD patients were consecutively recruited from November 2021 to October 2023 and underwent a psychiatric interview to diagnose generalized anxiety disorder (GAD) and/or major depressive disorder (MDD) based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Patients were split into training and validation sets according to their recruitment time. We assessed known risk factors and used core items from the Patient Health Questionnaire Anxiety and Depression Scale (PHQ-ADS) to develop a prediction nomogram. Multivariable logistic regression with least absolute shrinkage and selection operator (LASSO) were used to construct the nomogram.
resultsAmong the enrolled COPD patients (n = 329), 58 (25.6%) in the training cohort and 33 (32.4%) in the validation cohort were diagnosed with GAD and/or MDD. Three variables were identified in the prediction nomogram: COPD Assessment Test score and two core items from PHQ-ADS. The under the curve (AUC) value for the nomogram was 0.826 (95% CI: 0.755-0.897) and 0.855 (95% CI: 0.767-0.942) in the training and validation cohorts, respectively. The calibration curve was close to the diagonal. The discriminatory power of the screening nomogram was comparable to that of PHQ-ADS (AUC: 0.826 vs. 0.831, P = 0.832).
conclusionThe new screening tool for GAD and MDD in COPD patients is concise and valid, with discriminatory power comparable to existing anxiety/depression screening questionnaires.
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