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1.
Arch Bronconeumol ; 60(2): 95-100, 2024 Feb.
Article in English, Spanish | MEDLINE | ID: mdl-38216404

ABSTRACT

INTRODUCTION: The Global Initiative for Obstructive Lung Disease (GOLD) recommends lung cancer screening for patients with Chronic Obstructive Pulmonary Disease (COPD), but data is lacking regarding results of screening in this high-risk population. The main goal of the present work is to explore if lung cancer screening with Low Dose Chest Tomography (LDCT) in people with COPD, allows lung cancer (LC) diagnosis in early stages with survival compatible with curative state. METHODS: This is a post hoc exploratory analysis. Pamplona International Early Lung Cancer Action Program (P-IELCAP) participants with a GOLD defined obstructive pattern (post bronchodilator FEV1/FVC<0.70) were selected for analysis. The characteristics of those who developed LC and their survival are described. A Cox proportional analysis explored the factors associated with LC diagnosis. RESULTS: Eight hundred and sixty-five patients (77% male, 93% in spirometric GOLD stage 1+2) were followed for 102±63 months. LC prevalence was 2.6% at baseline, with an annual LC diagnosis rate of 0.68%. Early-stage tumors predominated (74%) with a median survival (25-75th percentiles) of 139 (76-185) months. Cumulative tobacco exposure, FEV1%, and emphysema were the main predictors of an LC diagnosis. Eight (11%) patients with COPD had a second LC, most of them in early stage (92%), and 6 (8%) had recurrence. Median survival (25-75th percentiles) in these patients was 168 (108-191) months. CONCLUSIONS: Lung cancer screening of selected high-risk participants with COPD allowed the LC diagnosis in early stages with survival compatible with curative state.


Subject(s)
Lung Neoplasms , Pulmonary Disease, Chronic Obstructive , Pulmonary Emphysema , Humans , Male , Female , Lung Neoplasms/diagnosis , Lung Neoplasms/epidemiology , Early Detection of Cancer , Tomography, X-Ray Computed/methods , Pulmonary Disease, Chronic Obstructive/complications , Pulmonary Disease, Chronic Obstructive/diagnosis , Pulmonary Disease, Chronic Obstructive/epidemiology , Pulmonary Emphysema/epidemiology , Forced Expiratory Volume
2.
PLoS One ; 14(7): e0219187, 2019.
Article in English | MEDLINE | ID: mdl-31344121

ABSTRACT

BACKGROUND: To assess the relationship between lung cancer and emphysema subtypes. OBJECTIVE: Airflow obstruction and emphysema predispose to lung cancer. Little is known, however, about the lung cancer risk associated with different emphysema phenotypes. We assessed the risk of lung cancer based on the presence, type and severity of emphysema, using visual assessment. METHODS: Seventy-two consecutive lung cancer cases were selected from a prospective cohort of 3,477 participants enrolled in the Clínica Universidad de Navarra's lung cancer screening program. Each case was matched to three control subjects using age, sex, smoking history and body mass index as key variables. Visual assessment of emphysema and spirometry were performed. Logistic regression and interaction model analysis were used in order to investigate associations between lung cancer and emphysema subtypes. RESULTS: Airflow obstruction and visual emphysema were significantly associated with lung cancer (OR = 2.8, 95%CI: 1.6 to 5.2; OR = 5.9, 95%CI: 2.9 to 12.2; respectively). Emphysema severity and centrilobular subtype were associated with greater risk when adjusted for confounders (OR = 12.6, 95%CI: 1.6 to 99.9; OR = 34.3, 95%CI: 25.5 to 99.3, respectively). The risk of lung cancer decreases with the added presence of paraseptal emphysema (OR = 4.0, 95%CI: 3.6 to 34.9), losing this increased risk of lung cancer when it occurs alone (OR = 0.7, 95%CI: 0.5 to 2.6). CONCLUSIONS: Visual scoring of emphysema predicts lung cancer risk. The centrilobular phenotype is associated with the greatest risk.


Subject(s)
Emphysema/pathology , Lung Neoplasms/etiology , Female , Humans , Logistic Models , Male , Middle Aged , Models, Biological , Multivariate Analysis , Odds Ratio , Phenotype , Risk Factors
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