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. 2015 Feb;101(3):201-8.
doi: 10.1136/heartjnl-2014-305637. Epub 2014 Oct 16.

A cardiovascular disease policy model that predicts life expectancy taking into account socioeconomic deprivation

J D Lewsey  1 , K D Lawson  1 , I Ford  2 , K A A Fox  3 , L D Ritchie  4 , H Tunstall-Pedoe  5 , G C M Watt  6 , M Woodward  7 , S Kent  1 , M Neilson  1 , A H Briggs  1
Affiliations
Free PMC article

A cardiovascular disease policy model that predicts life expectancy taking into account socioeconomic deprivation

J D Lewsey et al. Heart. 2015 Feb.
Free PMC article

Abstract

Objectives: A policy model is a model that can evaluate the effectiveness and cost-effectiveness of interventions and inform policy decisions. In this study, we introduce a cardiovascular disease (CVD) policy model which can be used to model remaining life expectancy including a measure of socioeconomic deprivation as an independent risk factor for CVD.

Design: A state transition model was developed using the Scottish Heart Health Extended Cohort (SHHEC) linked to Scottish morbidity and death records. Individuals start in a CVD-free state and can transit to three CVD event states plus a non-CVD death state. Individuals who have a non-fatal first event are then followed up until death. Taking a competing risk approach, the cause-specific hazards of a first event are modelled using parametric survival analysis. Survival following a first non-fatal event is also modelled parametrically. We assessed discrimination, validation and calibration of our model.

Results: Our model achieved a good level of discrimination in each component (c-statistics for men (women)-non-fatal coronary heart disease (CHD): 0.70 (0.74), non-fatal cerebrovascular disease (CBVD): 0.73 (0.76), fatal CVD: 0.77 (0.80), fatal non-CVD: 0.74 (0.72), survival after non-fatal CHD: 0.68 (0.67) and survival after non-fatal CBVD: 0.65 (0.66)). In general, our model predictions were comparable with observed event rates for a Scottish randomised statin trial population which has an overlapping follow-up period with SHHEC. After applying a calibration factor, our predictions of life expectancy closely match those published in recent national life tables.

Conclusions: Our model can be used to estimate the impact of primary prevention interventions on life expectancy and can assess the impact of interventions on inequalities.

Keywords: CORONARY ARTERY DISEASE; QUALITY OF CARE AND OUTCOMES.

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Figures

Figure 1
Figure 1
Structure of the state transition model. CBVD, cerebrovascular disease; CHD, coronary heart disease; CPD, cigarettes per day; CVD, cardiovascular disease; HDL, high-density lipoprotein cholesterol (mmol/L); SIMD, Scottish Index of Multiple Deprivation; SBP, systolic blood pressure (mm Hg); TC, total cholesterol (mmol/L).
Figure 2
Figure 2
A and B, Validation of model predictions using West of Scotland Coronary Prevention Study trial population. CBVD, cerebrovascular disease; CHD, coronary heart disease; CVD, cardiovascular disease.
Figure 2
Figure 2
A and B, Validation of model predictions using West of Scotland Coronary Prevention Study trial population. CBVD, cerebrovascular disease; CHD, coronary heart disease; CVD, cardiovascular disease.
Figure 3
Figure 3
Predicted life expectancy for ranked fifths of socioeconomic deprivation (SIMD) scores.
See this image and copyright information in PMC

References

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