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

J. D. Lewsey (Lead / Corresponding author), K. D. Lawson, I. Ford, K. A. A. Fox, L. D. Ritchie, H. Tunstall-Pedoe, G. C. M. Watt, M. Woodward, S. Kent, M. Neilson, A. H. Briggs

    Research output: Contribution to journalArticle

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    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.
    Original languageEnglish
    Pages (from-to)201-208
    Number of pages8
    JournalHeart (British Cardiac Society)
    Volume101
    Issue number3
    Early online date16 Oct 2014
    DOIs
    Publication statusPublished - Feb 2015

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    Life Expectancy
    Cardiovascular Diseases
    Cerebrovascular Disorders
    Calibration
    Coronary Disease
    Survival
    Hydroxymethylglutaryl-CoA Reductase Inhibitors
    Death Certificates
    Life Tables
    Health
    Primary Prevention
    Survival Analysis
    Cost-Benefit Analysis
    Morbidity
    Population

    Cite this

    Lewsey, J. D. ; Lawson, K. D. ; Ford, I. ; Fox, K. A. A. ; Ritchie, L. D. ; Tunstall-Pedoe, H. ; Watt, G. C. M. ; Woodward, M. ; Kent, S. ; Neilson, M. ; Briggs, A. H. / A cardiovascular disease policy model that predicts life expectancy taking into account socioeconomic deprivation. In: Heart (British Cardiac Society). 2015 ; Vol. 101, No. 3. pp. 201-208.
    @article{ea93f778d31c42c19d78c4b0b2bf39c4,
    title = "A cardiovascular disease policy model that predicts life expectancy taking into account socioeconomic deprivation",
    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.",
    author = "Lewsey, {J. D.} and Lawson, {K. D.} and I. Ford and Fox, {K. A. A.} and Ritchie, {L. D.} and H. Tunstall-Pedoe and Watt, {G. C. M.} and M. Woodward and S. Kent and M. Neilson and Briggs, {A. H.}",
    note = "Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.",
    year = "2015",
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    Lewsey, JD, Lawson, KD, Ford, I, Fox, KAA, Ritchie, LD, Tunstall-Pedoe, H, Watt, GCM, Woodward, M, Kent, S, Neilson, M & Briggs, AH 2015, 'A cardiovascular disease policy model that predicts life expectancy taking into account socioeconomic deprivation', Heart (British Cardiac Society), vol. 101, no. 3, pp. 201-208. https://doi.org/10.1136/heartjnl-2014-305637

    A cardiovascular disease policy model that predicts life expectancy taking into account socioeconomic deprivation. / Lewsey, J. D. (Lead / Corresponding author); Lawson, K. D.; Ford, I.; Fox, K. A. A.; Ritchie, L. D.; Tunstall-Pedoe, H.; Watt, G. C. M.; Woodward, M.; Kent, S.; Neilson, M.; Briggs, A. H.

    In: Heart (British Cardiac Society), Vol. 101, No. 3, 02.2015, p. 201-208.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - A cardiovascular disease policy model that predicts life expectancy taking into account socioeconomic deprivation

    AU - Lewsey, J. D.

    AU - Lawson, K. D.

    AU - Ford, I.

    AU - Fox, K. A. A.

    AU - Ritchie, L. D.

    AU - Tunstall-Pedoe, H.

    AU - Watt, G. C. M.

    AU - Woodward, M.

    AU - Kent, S.

    AU - Neilson, M.

    AU - Briggs, A. H.

    N1 - Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

    PY - 2015/2

    Y1 - 2015/2

    N2 - 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.

    AB - 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.

    U2 - 10.1136/heartjnl-2014-305637

    DO - 10.1136/heartjnl-2014-305637

    M3 - Article

    C2 - 25324535

    VL - 101

    SP - 201

    EP - 208

    JO - Heart

    JF - Heart

    SN - 1355-6037

    IS - 3

    ER -