Inclusion of Smoking Data in Cardiovascular Disease Risk Estimation

Meredith S. Duncan, Robert A. Greevy, Hilary A. Tindle, Ramachandran S. Vasan, Loren Lipworth, Melinda C. Aldrich, Donald M. Lloyd-Jones, Matthew S. Freiberg

Research output: Contribution to journalArticlepeer-review

Abstract

Importance: Former heavy smokers (ie, those with ≥20 pack-years of smoking) may have higher atherosclerotic cardiovascular disease (ASCVD) risk than never smokers for up to 16 years after smoking cessation. However, the 2013 pooled cohort equations (PCE) do not account for pack-years of smoking and only consider current vs noncurrent smoking status without distinguishing former smokers from never smokers. Objective: To assess the predictive utility of smoking history when added to the PCE using data from 18400 person examinations among Framingham offspring participants. Design, Setting, and Participants: This is a retrospective analysis of prospectively collected data from the Framingham Heart Study, a community-based cohort. Framingham Heart Study offspring cohort participants attending their first examination (1971-1975) who were followed-up through December 2016 were included. Exposures: Self-reported current/former/never smoking status, pack-years smoked, and years since quitting. Main Outcomes and Measures: Incident ASCVD (myocardial infarction, fatal/nonfatal ischemic stroke, coronary heart disease death). Results: Of 3908 patients, there were 358 and 197 events among 1895 men and 2013 women, respectively, with a mean (SD) age of 55 (9.5) years. Ever smoking prevalence was high (6474 men [77%] and 7760 women [78%]), as were median pack-years (men: 39; women: 32 overall person examinations). Four sex-specific ASCVD risk prediction models were built using pooled-repeated Cox proportional hazards regression. The PCEs were was fit in this sample with continuous predictors on their natural scale (ie, not logarithmically transformed) as well as polynomials accounting for nonlinearity and then cumulatively adjusted for former smoking, pack-years, and years since quitting. Models were compared via change in C statistic, continuous net reclassification improvement (NRI[>0]), and relative integrated discrimination improvement (rIDI). Including former smoking status, pack-years, and years since quitting had significant but modest NRI(>0) and rIDI values compared with the PCE with continuous variables on their natural scale in both sexes (men: NRI[>0] = 0.23; rIDI = 0.19; women: NRI[>0] = 0.34, rIDI = 0.11; change in C statistic = 0.01 for both). Conclusions and Relevance: Former smoking, pack-years, and years since quitting significantly improved ASCVD risk prediction in this sample. The Framingham Heart Study offspring cohort is largely composed of non-Hispanic White participants of European ancestry. If results are validated in cohorts of race and ethnicity groups other than White, these variables could be considered for inclusion in future ASCVD risk prediction models.

Original languageEnglish (US)
Pages (from-to)195-203
Number of pages9
JournalJAMA Cardiology
Volume7
Issue number2
DOIs
StatePublished - Feb 2022
Externally publishedYes

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Fingerprint

Dive into the research topics of 'Inclusion of Smoking Data in Cardiovascular Disease Risk Estimation'. Together they form a unique fingerprint.

Cite this