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Macrovascular Risk Equations Based on the CANVAS Program

Author

Listed:
  • Michael Willis

    (Swedish Institute for Health Economics)

  • Christian Asseburg

    (ESiOR Oy)

  • April Slee

    (Axio Research, LLC)

  • Andreas Nilsson

    (Swedish Institute for Health Economics)

  • Cheryl Neslusan

    (Janssen Scientific Affairs, LLC)

Abstract

Background Widely used risk equations for cardiovascular outcomes for individuals with type 2 diabetes mellitus (T2DM) have been incapable of predicting cardioprotective effects observed in recent cardiovascular outcomes trials (CVOTs) involving individuals with T2DM at high risk for or with established cardiovascular disease (CVD). Objective We developed cardiovascular and mortality risk equations using patient-level data from the CANVAS (CANagliflozin cardioVascular Assessment Study) Program to address this shortcoming. Methods Data from 10,142 patients with T2DM at high risk for or with established CVD, randomized to canagliflozin + standard of care (SoC) or SoC alone and followed for a mean duration of 3.6 years in the CANVAS Program were used to derive parametric risk equations for myocardial infarction (MI), stroke, hospitalization for heart failure (HHF), and death. Accumulated knowledge from the widely used UKPDS-OM2 (United Kingdom Prospective Diabetes Study Outcomes Model 2) was leveraged, and any departures in parameterization were limited to those necessary to provide adequate goodness of fit. Candidate explanatory covariates were selected using only the placebo arm to minimize confounding effects. Internal validation was performed separately by study treatment arm. Results UKPDS-OM2 predicted CANVAS Program outcomes poorly. Recalibrating UKPDS-OM2 intercepts improved calibration in some cases. Refitting the coefficients but otherwise preserving the UKPDS-OM2 structure improved the fit substantially, which was sufficient for stroke and death. For MI, reselecting UKPDS-OM2 covariates and functional form proved sufficient. For HHF, selection from a broad set of candidate covariates and inclusion of a canagliflozin indicator was required. Conclusion These risk equations address some of the limitations of widely used risk equations, such as the UKPDS-OM2, for modeling cardioprotective treatments for individuals with T2DM and high cardiovascular risk, including derivation from overly healthy patients treated with agents that lack cardioprotection and have been described as reflecting a different therapeutic era. Future work is needed to examine external validity.

Suggested Citation

  • Michael Willis & Christian Asseburg & April Slee & Andreas Nilsson & Cheryl Neslusan, 2021. "Macrovascular Risk Equations Based on the CANVAS Program," PharmacoEconomics, Springer, vol. 39(4), pages 447-461, April.
    • Handle: RePEc:spr:pharme:v:39:y:2021:i:4:d:10.1007_s40273-021-01001-0
    DOI: 10.1007/s40273-021-01001-0
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    References listed on IDEAS

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    1. Briggs, Andrew & Sculpher, Mark & Claxton, Karl, 2006. "Decision Modelling for Health Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198526629.
    2. Michael Willis & Pierre Johansen & Andreas Nilsson & Christian Asseburg, 2017. "Validation of the Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM)," PharmacoEconomics, Springer, vol. 35(3), pages 375-396, March.
    3. P. McEwan & H. Bennett & T. Ward & K. Bergenheim, 2015. "Refitting of the UKPDS 68 Risk Equations to Contemporary Routine Clinical Practice Data in the UK," PharmacoEconomics, Springer, vol. 33(2), pages 149-161, February.
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Journal round-up: PharmacoEconomics 39(4)
      by Chris Sampson in The Academic Health Economists' Blog on 2021-06-15 06:00:05

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