Leveraging low-dose CT in lung cancer screening to improve chronic obstructive pulmonary disease diagnosis and treatment
Notice bibliographique
Résumé
Abstract:Lung cancer screening (LCS) programs offer an opportunity to improve access to COPD diagnosis and treatment in high-risk individuals. COPD is one of the top three causes of death globally and remains underdiagnosed due to its heterogeneous clinical presentation, with most patients diagnosed at moderate to severe stages. LCS-eligible individuals, typically smokers or ex-smokers, are at high risk of COPD. Markers such as emphysema and airway thickening can be identified on low-dose CT (LDCT), presenting an opportunity to use these scans to increase early COPD diagnosis and reduce mortality.Objectives:To identify the proportion of untreated individuals with symptomatic COPD—defined as radiographic emphysema on LDCT plus dyspnea and/or elevated CAT score—and to explore factors associated with receiving COPD pharmacotherapy among LCS participants.Methods: Data were analyzed from participants recruited through the Quebec LCS program between April 2023 and July 2024 across 10 hospitals. The study included smokers or ex-smokers aged 55–74 with a PLCOm2012 ≥ 2% and a Lung-RADS 1–2 baseline LDCT. Radiographic COPD was defined as emphysema identified on LDCT by a thoracic radiologist, combined with dyspnea and COPD symptoms (mMRC ≥ 1) and/or CAT score ≥ 10. The primary outcome was having COPD pharmacotherapy (long-acting bronchodilators). Secondary outcomes included COPD symptoms, health literacy and quality of life. Logistic regression identified factors associated with treatment, adjusting for emphysema severity, smoking status, BMI, and sociodemographic factors. Gender-based differences were explored through stratified analysis, and BMI was evaluated in relation to symptoms and emphysema severity.Results: Among 1026 participants with Lung-RADS 1–2 LDCT, 801 had visual emphysema. Most (603/801; 75%) were untreated or only using short-acting beta agonists. Of these, 66% (397/603) were screened for dyspnea and COPD symptoms, and 56% (221/397) were found symptomatic (mean CAT 12.6, mMRC 0.91). Women (111/174; 64%) reported more dyspnea and COPD symptoms than men (110/223; 49%), particularly in minimal-to-mild emphysema (mean CAT 10.2 vs. 8.2, p < 0.05).Adjusted analyses showed that treatment with long-acting bronchodilators was associated with moderate-to-severe emphysema (OR 2.35; 95% CI 1.49–3.70), lower education (OR 0.58; 95% CI 0.37–0.91), and female sex (OR 1.58; 95% CI 1.04–2.42). Symptom burden increased with BMI category, although underweight and normal-weight participants had similar proportions of symptoms (50% and 49%, respectively), and no significant mMRC differences were observed between BMI groups. Pack-years increased with BMI. The likelihood of treatment increased with emphysema severity in normal (OR 1.84; 95% CI 0.90–3.74), overweight (OR 2.46; 95% CI 1.18–5.13), and obese (OR 4.06; 95% CI 1.21–13.6) categories. Lower education (OR 0.46; 95% CI 0.22–0.98) in normal weight and ex-smoking status (OR 0.45; 95% CI 0.23–0.89) in the overweight group were also associated with increased treatment likelihood. The underweight group was too small for model convergence.Conclusion: Untreated radiographic COPD with significant symptoms was frequent in this LCS cohort. Treatment was associated with female sex and moderate-to-severe emphysema. LDCT-reported emphysema and symptom burden should be considered by clinicians when reviewing LCS results. Integrating COPD diagnosis into LCS programs presents a key opportunity to improve early detection and management of COPD in a high-risk population
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».