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 The relationship between emphysema progression and long-term outcomes is unclear. Purpose To determine the relationship between emphysema progression at CT and mortality among participants with emphysema. Materials and Methods In a secondary analysis of two prospective observational studies, COPDGene (clinicaltrials.gov, NCT00608764) and Evaluation of Chronic Obstructive Pulmonary Disease Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE; clinicaltrials.gov, NCT00292552), emphysema was measured at CT at two points by using the volume-adjusted lung density at the 15th percentile of the lung density histogram (hereafter, lung density perc15) method. The association between emphysema progression rate and all-cause mortality was analyzed by using Cox regression adjusted for ethnicity, sex, baseline age, pack-years, and lung density, baseline and change in smoking status, forced expiratory volume in 1 second, and 6-minute walk distance. In COPDGene, respiratory mortality was analyzed by using the Fine and Gray method. Results A total of 5143 participants (2613 men [51%]; mean age, 60 years ± 9 [standard deviation]) in COPDGene and 1549 participants (973 men [63%]; mean age, 62 years ± 8) in ECLIPSE were evaluated, of which 2097 (40.8%) and 1179 (76.1%) had emphysema, respectively. Baseline imaging was performed between January 2008 and December 2010 for COPDGene and January 2006 and August 2007 for ECLIPSE. Follow-up imaging was performed after 5.5 years ± 0.6 in COPDGene and 3.0 years ± 0.2 in ECLIPSE, and mortality was assessed over the ensuing 5 years in both. For every 1 g/L per year faster rate of decline in lung density perc15, all-cause mortality increased by 8% in COPDGene (hazard ratio [HR], 1.08; 95% CI: 1.01, 1.16; P = .03) and 6% in ECLIPSE (HR, 1.06; 95% CI: 1.00, 1.13; P = .045). In COPDGene, respiratory mortality increased by 22% (HR, 1.22; 95% CI: 1.13, 1.31; P < .001) for the same increase in the rate of change in lung density perc15. Conclusion In ever-smokers with emphysema, emphysema progression at CT was associated with increased all-cause and respiratory mortality. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Lee and Park in this issue.

Project description:Background and Objectives: Acute kidney injury (AKI) that results from ischemia is a common clinical syndrome and correlates with high morbidity and mortality among hospitalized patients. However, a clinical tool to predict mortality risk of ischemic AKI is not available. In this study, we aimed to develop and validate models to predict the 30-day and 1-year mortality risk of hospitalized patients with ischemic AKI. Methods A total of 1,836 admissions with ischemic AKI were recruited from 277,898 inpatients admitted to three affiliated tertiary general hospitals of Central South University in China between January 2015 and December 2015. Patients in the final analysis were followed up for 1 year. Study patients were randomly divided in a 7:3 ratio to form the training cohort and validation cohort. Multivariable regression analyses were used for developing mortality prediction models. Results Hepatorenal syndrome, shock, central nervous system failure, Charlson comorbidity index (≥2 points), mechanical ventilation, renal function at discharge were independent risk factors for 30-day mortality after ischemic AKI, while malignancy, sepsis, heart failure, liver failure, Charlson comorbidity index (≥2 points), mechanical ventilation, and renal function at discharge were predictors for 1-year mortality. The area under the receiver operating characteristic curves (AUROCs) of 30-day prediction model were 0.878 (95% confidence interval (CI): 0.849-0.908) in the training cohort and 0.867 (95% CI: 0.820–0.913) in the validation cohort. The AUROCs of the 1-year mortality prediction in the training and validation cohort were 0.803 (95% CI: 0.772–0.834) and 0.788 (95% CI: 0.741–0.835), respectively. Conclusion Our easily applied prediction models can effectively identify individuals at high mortality risk within 30 days or 1 year in hospitalized patients with ischemic AKI. It can guide the optimal clinical management to minimize mortality after an episode of ischemic AKI.

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.

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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