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Framingham risk prediction equations for incidence of cardiovascular disease using detailed measures for smoking

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Published Online: Aug 1st 2018 Heart International 2010;5(1):e11 DOI: https://doi.org/10.4081/hi.2010.e11
Authors: Haider Mannan, Chris Stevenson, Anna Peeters, Helen Walls, John McNeil
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Abstract
Article
Article Information
Abstract:
Overview

Current prediction models for risk of cardiovascular
disease (CVD) incidence incorporate
smoking as a dichotomous yes/no measure.
However, the risk of CVD associated with
smoking also varies with the intensity and
duration of smoking and there is a strong
association between time since quitting and the risk of disease onset. This study aims to
develop improved risk prediction equations for
CVD incidence incorporating intensity and
duration of smoking and time since quitting.
The risk of developing a first CVD event was
evaluated using a Cox’s model for participants
in the Framingham offspring cohort who
attended the fourth examination (1988-92)
between the ages of 30 and 74 years and were
free of CVD (n=3751). The full models based
on the smoking variables and other risk factors,
and reduced models based on the smoking
variables and non-laboratory risk factors
demonstrated good discrimination, calibration
and global fit. The incorporation of both time
since quitting among past smokers and packyears
among current smokers resulted in better
predictive performance as compared to a
dichotomous current/non-smoker measure
and a current/quitter/never smoker measure.
Compared to never smokers, the risk of CVD
incidence increased with pack-years. Risk
among those quitting more than five years
prior to the baseline exam and within five
years prior to the baseline exam were similar
and twice as high as that of never smokers. A
CVD risk equation incorporating the effects of
pack-years and time since quitting provides an
improved tool to quantify risk and guide preventive
care.

Keywords

Coronary heart disease, predictive equation, detailed smoking measures, other risk factors, reduced equation.

Article:
Article Information:
Correspondence

Haider Mannan, Department of Epidemiology and Preventive Medicine, Monash University, Alfred Centre, 99 Commercial Road, Melbourne 3004, Victoria, Australia. E-mail: haider.mannan@monash.edu

Acknowledgements

The Framingham Heart Study –
Offspring (FHS-O) is conducted and supported by
the NHLBI in collaboration with the FHS-O Study
Investigators. This manuscript was prepared
using a limited access dataset obtained from the
NHLBI and does not necessarily reflect the opinions
or views of the FHS-O or the NHLBI. This
research was supported by an NHMRC health
services research grant (n. 465130), an
NHMRC/NHF PhD scholarship and a Vichealth
Fellowship.

Received

2010-07-06

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