Burden of Comorbid Conditions Among Individuals Screened for Lung Cancer
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Résumé
Importance: Screening for lung cancer with low-dose computed tomography (LDCT) has been shown to reduce lung cancer mortality in trials that included relatively younger, healthier, and predominantly White populations. The comorbidity profiles among patients undergoing lung cancer screening in practice settings are poorly understood. Objective: To evaluate the comorbidity profiles of patients in the Personalized Lung Cancer Screening (PLuS) cohort as a clinical setting vs the National Lung Screening Trial (NLST) participants in a clinical trial setting. Design, Setting, and Participants: This multicenter cohort study was conducted across 3 health care systems in California, Florida, and South Carolina and included patients who underwent LDCT lung cancer screening between 2016 and 2021. Data were analyzed between January 1, 2016, and December 31, 2021. Exposures: Receipt of the LDCT scan identified through Current Procedural Terminology and Healthcare Common Procedure Coding System codes. Main Outcomes and Measures: Detailed comorbidity data, measures of pulmonary function, and study data abstracted from electronic health records and institutional, Surveillance, Epidemiology, and End Results (SEER), and state registries were compared with self-reported comorbid conditions of participants in the LDCT arm of the NLST. Results: The PLuS cohort (n = 31 795) included 49.0% participants aged 65 years or older vs 26.6% in the NLST cohort (n = 26 723); 23.3% were individuals of racial and ethnic minority groups in the PLuS cohort compared with 8.5% in the NLST. The prevalence of comorbidity was substantially higher in the PLuS cohort than the NLST group, particularly chronic obstructive pulmonary disease (32.7% vs 17.5%), diabetes (24.6% vs 9.7%), and heart disease (15.9% vs 12.9%). Among those in the PLuS cohort, 19.3% had a Charlson Comorbidity Index score of 4 or higher, 18.0% had a frailty index greater than 0.20, 16.9% had a forced expiratory volume in 1 second (FEV-1) lower than 50% of predicted, and almost 5% had an ejection fraction lower than 40%. The prevalence of multimorbidity and frailty was especially high among those in the 75 years or older age group. Conclusions and Relevance: This study found that the PLuS cohort members were older, had greater illness severity, and more racially and ethnically diverse than the NLST participants. Older patients and those with consequential comorbidity likely had different risk-benefit profiles, which may have affected screening outcomes. The high prevalence of multimorbidity, frailty, and impaired cardiopulmonary function in the PLuS cohort suggests that the balance of benefits and harms observed in the NLST group may not translate to the clinical setting.
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 découle