Matthew Strand, PhD1 Erin Austin, PhD2 Matthew Moll, MD3 Katherine A. Pratte, MSPH, PhD1 Elizabeth A. Regan, MD, PhD1 Lystra P. Hayden, MD, MMSc3 Surya P. Bhatt, MD4 Aladin M. Boriek, PhD5 Richard Casaburi, PhD, MD6 Edwin K. Silverman, MD, PhD3 Spyridon Fortis, MD7 Ingo Ruczinski, PhD8 Harald Koegler, MD9 Harry B. Rossiter, PhD6 10 Mariaelena Occhipinti, MD, PhD11* Nicola A. Hanania, MD, MS5 Hirut T. Gebrekristos, PhD12 David A. Lynch, MB1 Ken M. Kunisaki, MD13 Kendra A. Young, MSPH, PhD14 Jessica C. Sieren, PhD7 Margaret Ragland, MD, MS14 John E. Hokanson, MPH, PhD14 Sharon M. Lutz, PhD15 Barry J. Make, MD1 Gregory L. Kinney, MPH, PhD14 Michael H. Cho, MD, MPH3 Massimo Pistolesi, MD11 Dawn L. DeMeo, MD, MPH3 15 Frank C. Sciurba, MD16 Alejandro P. Comellas, MD7 Alejandro A. Diaz, MD3 Igor Barjaktarevic, MD, PhD17 Russell P. Bowler, MD, PhD1 Richard E. Kanner, MD18 Stephen P. Peters, MD, PhD19 Victor E. Ortega, MD, PhD19 Mark T. Dransfield, MD4 James D. Crapo, MD1
Author Affiliations
- National Jewish Health, Denver, Colorado
- University of Colorado at Denver
- Brigham and Women’s Hospital, Boston, Massachusetts
- University of Alabama at Birmingham
- Baylor College of Medicine, Houston, Texas
- The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California
- University of Iowa, Iowa City
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
- Boehringer-Ingelheim, Ingelheim, Germany
- University of Leeds, Leeds, United Kingdom
- University of Florence, Florence, Italy
- Morehouse School of Medicine, Atlanta, Georgia
- Minneapolis Veterans Administration Health Care System, Minnesota
- University of Colorado Anschutz Medical Campus, Aurora
- Harvard Medical School, Harvard University, Boston, Massachusetts
- University of Pittsburgh, Pittsburgh, Pennsylvania
- David Geffen School of Medicine, University of California-Los Angeles, Los Angeles
- School of Medicine, University of Utah, Salt Lake City
- Wake Forest School of Medicine, Wake Forest University, Winston-Salem, North Carolina
* Dr. Occhipinti is now at the Imaging Institute, Ente Ospedaliero Cantonale, Lugano, Switzerland
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 chronic Obstructive Lung Disease (GOLD) criteria.