Dataset Information

A Risk Prediction Model for Mortality Among Smokers in the COPDGene® Study.

ABSTRACT:

Background

Risk factor identification is a proven strategy in advancing treatments and preventive therapy for many chronic conditions. Quantifying the impact of those risk factors on health outcomes can consolidate and focus efforts on individuals with specific high-risk profiles. Using multiple risk factors and longitudinal outcomes in 2 independent cohorts, we developed and validated a risk score model to predict mortality in current and former cigarette smokers.

Methods

We obtained extensive data on current and former smokers from the COPD Genetic Epidemiology (COPDGene^®) study at enrollment. Based on physician input and model goodness-of-fit measures, a subset of variables was selected to fit final Weibull survival models separately for men and women. Coefficients and predictors were translated into a point system, allowing for easy computation of mortality risk scores and probabilities. We then used the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) cohort for external validation of our model.

Results

Of 9867 COPDGene participants with standard baseline data, 17.6% died over 10 years of follow-up, and 9074 of these participants had the full set of baseline predictors (standard plus 6-minute walk distance and computed tomography variables) available for full model fits. The average age of participants in the cohort was 60 for both men and women, and the average predicted 10-year mortality risk was 18% for women and 25% for men. Model time-integrated area under the receiver operating characteristic curve statistics demonstrated good predictive model accuracy (0.797 average), validated in the external cohort (0.756 average). Risk of mortality was impacted most by 6-minute walk distance, forced expiratory volume in 1 second and age, for both men and women.

Conclusions

Current and former smokers exhibited a wide range of mortality risk over a 10- year period. Our models can identify higher risk individuals who can be targeted for interventions to reduce risk of mortality, for participants with or without chronic obstructive pulmonary disease (COPD) using current Global initiative for obstructive Lung Disease (GOLD) criteria.

SUBMITTER: Strand M

PROVIDER: S-EPMC7883903 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

A Risk Prediction Model for Mortality Among Smokers in the COPDGene® Study.

Strand Matthew M Austin Erin E Moll Matthew M Pratte Katherine A KA Regan Elizabeth A EA Hayden Lystra P LP Bhatt Surya P SP Boriek Aladin M AM Casaburi Richard R Silverman Edwin K EK Fortis Spyridon S Ruczinski Ingo I Koegler Harald H Rossiter Harry B HB Occhipinti Mariaelena M Hanania Nicola A NA Gebrekristos Hirut T HT Lynch David A DA Kunisaki Ken M KM Young Kendra A KA Sieren Jessica C JC Ragland Margaret M Hokanson John E JE Lutz Sharon M SM Make Barry J BJ Kinney Gregory L GL Cho Michael H MH Pistolesi Massimo M DeMeo Dawn L DL Sciurba Frank C FC Comellas Alejandro P AP Diaz Alejandro A AA Barjaktarevic Igor I Bowler Russell P RP Kanner Richard E RE Peters Stephen P SP Ortega Victor E VE Dransfield Mark T MT Crapo James D JD

Chronic obstructive pulmonary diseases (Miami, Fla.) 20201001 4

<h4>Background</h4>Risk factor identification is a proven strategy in advancing treatments and preventive therapy for many chronic conditions. Quantifying the impact of those risk factors on health outcomes can consolidate and focus efforts on individuals with specific high-risk profiles. Using multiple risk factors and longitudinal outcomes in 2 independent cohorts, we developed and validated a risk score model to predict mortality in current and former cigarette smokers.<h4>Methods</h4>We obta ...[more]

PMID: 32877963

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Project description:RATIONALE:A significant proportion of smokers have lung function impairment characterized by a reduced FEV(1) with a preserved FEV(1)/FVC ratio. These smokers are a poorly characterized group due to their systematic exclusion from chronic obstructive pulmonary disease (COPD) studies. OBJECTIVES:To characterize the clinical, functional, and radiographic features of Global Initiative for Chronic Obstructive Lung Disease (GOLD)-Unclassified (FEV(1)/FVC ≥ 0.7 and FEV(1) < 80% predicted) and lower limits of normal (LLN)-unclassified (FEV(1)/FVC ≥ LLN and FEV(1) < LLN) subjects compared to smokers with normal lung function and subjects with COPD. METHODS:Data from the first 2,500 subjects enrolled in the COPDGene study were analyzed. All subjects had 10 or more pack-years of smoking and were between the ages of 45 and 80 years. Multivariate regression models were constructed to determine the clinical and radiological variables associated with GOLD-Unclassified (GOLD-U) and LLN-Unclassified status. Separate multivariate regressions were performed in the subgroups of subjects with complete radiologic measurement variables available. MEASUREMENTS AND MAIN RESULTS:GOLD-U smokers account for 9% of smokers in COPDGene and have increased body mass index (BMI), a disproportionately reduced total lung capacity, and a higher proportion of nonwhite subjects and subjects with diabetes. GOLD-U subjects exhibit increased airway wall thickness compared to smoking control subjects and decreased gas trapping and bronchodilator responsiveness compared to subjects with COPD. When LLN criteria were used to define the "unclassified" group, African American subjects were no longer overrepresented. Both GOLD-U and LLN-Unclassified subjects demonstrated a wide range of lung function impairment, BMI, and percentage of total lung emphysema. CONCLUSIONS:Subjects with reduced FEV(1) and a preserved FEV(1)/FVC ratio are a heterogeneous group with significant symptoms and functional limitation who likely have a variety of underlying etiologies beyond increased BMI. Clinical trial registered with www.clinicaltrials.gov (NCT000608764).

Project description:Background:Chronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality. Present-day diagnostic criteria are largely based solely on spirometric criteria. Accumulating evidence has identified a substantial number of individuals without spirometric evidence of COPD who suffer from respiratory symptoms and/or increased morbidity and mortality. There is a clear need for an expanded definition of COPD that is linked to physiologic, structural (computed tomography [CT]) and clinical evidence of disease. Using data from the COPD Genetic Epidemiology study (COPDGene®), we hypothesized that an integrated approach that includes environmental exposure, clinical symptoms, chest CT imaging and spirometry better defines disease and captures the likelihood of progression of respiratory obstruction and mortality. Methods:Four key disease characteristics - environmental exposure (cigarette smoking), clinical symptoms (dyspnea and/or chronic bronchitis), chest CT imaging abnormalities (emphysema, gas trapping and/or airway wall thickening), and abnormal spirometry - were evaluated in a group of 8784 current and former smokers who were participants in COPDGene® Phase 1. Using these 4 disease characteristics, 8 categories of participants were identified and evaluated for odds of spirometric disease progression (FEV1 > 350 ml loss over 5 years), and the hazard ratio for all-cause mortality was examined. Results:Using smokers without symptoms, CT imaging abnormalities or airflow obstruction as the reference population, individuals were classified as Possible COPD, Probable COPD and Definite COPD. Current Global initiative for obstructive Lung Disease (GOLD) criteria would diagnose 4062 (46%) of the 8784 study participants with COPD. The proposed COPDGene® 2019 diagnostic criteria would add an additional 3144 participants. Under the new criteria, 82% of the 8784 study participants would be diagnosed with Possible, Probable or Definite COPD. These COPD groups showed increased risk of disease progression and mortality. Mortality increased in patients as the number of their COPD characteristics increased, with a maximum hazard ratio for all cause-mortality of 5.18 (95% confidence interval [CI]: 4.15-6.48) in those with all 4 disease characteristics. Conclusions:A substantial portion of smokers with respiratory symptoms and imaging abnormalities do not manifest spirometric obstruction as defined by population normals. These individuals are at significant risk of death and spirometric disease progression. We propose to redefine the diagnosis of COPD through an integrated approach using environmental exposure, clinical symptoms, CT imaging and spirometric criteria. These expanded criteria offer the potential to stimulate both current and future interventions that could slow or halt disease progression in patients before disability or irreversible lung structural changes develop.

Project description:BackgroundUpper gastrointestinal bleeding is a common presentation in emergency departments and carries significant morbidity worldwide. It is paramount that treating physicians have access to tools that can effectively evaluate the patient risk, allowing quick and effective treatments to ultimately improve their prognosis. This study aims to establish a mortality risk assessment model for patients with acute upper gastrointestinal bleeding at an emergency department.MethodsA total of 991 patients presenting with acute upper gastrointestinal bleeding between July 2016 and June 2019 were enrolled in this retrospective single-center cohort study. Patient demographics, parameters assessed at admission, laboratory test, and clinical interventions were extracted. We used the least absolute shrinkage and selection operator regression to identify predictors for establishing a nomogram for death in the emergency department or within 24 h after leaving the emergency department and a corresponding nomogram. The area under the curve of the model was calculated. A bootstrap resampling method was used to internal validation, and decision curve analysis was applied for evaluate the clinical utility of the model. We also compared our predictive model with other prognostic models, such as AIMS65, Glasgow-Blatchford bleeding score, modified Glasgow-Blatchford bleeding score, and Pre-Endoscopic Rockall Score.ResultsAmong 991 patients, 41 (4.14%) died in the emergency department or within 24 h after leaving the emergency department. Five non-zero coefficient variables (transfusion of plasma, D-dimer, albumin, potassium, age) were filtered by the least absolute shrinkage and selection operator regression analysis and used to establish a predictive model. The area under the curve for the model was 0.847 (95% confidence interval [0.794-0.900]), which is higher than that of previous models for mortality of patients with acute upper gastrointestinal bleeding. The decision curve analysis indicated the clinical usefulness of the model.ConclusionsThe nomogram based on transfusion of plasma, D-dimer, albumin, potassium, and age effectively assessed the prognosis of patients with acute upper gastrointestinal bleeding presenting at the emergency department.

Dataset Information

A Risk Prediction Model for Mortality Among Smokers in the COPDGene® Study.

Background

Methods

Results

Conclusions

Publications

A Risk Prediction Model for Mortality Among Smokers in the COPDGene® Study.

Similar Datasets

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