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).
We developed cardiovascular and mortality risk equations using patient-level data from the CANVAS (CANagliflozin cardioVascular Assessment Study) Program to address this shortcoming.
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.
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.
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.
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Vital status was collected for all patients who did not withdraw consent (1.4% of the population withdrew consent). The analysis considers the outcomes censored at the minimum of last trial contact date, trial end date, or the last laboratory measurement + 13 months.
For example, a post hoc analysis of the EMPA-REG OUTCOME trial attributed 90% of reduction in cardiovascular death to risk factors (mostly hematocrit, hemoglobin, and albumin) , but these risk factors may have captured features identifying empagliflozin treatment (and associated benefits in other channels) rather than a direct causal relationship between these biomarkers and event risk .
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Editorial assistance was provided by Alaina Mitsch, PhD, of MedErgy, and was funded by Janssen Global Services, LLC. The authors wish to thank Shana Traina, PhD, of Janssen Global Services, LLC, for assistance with the methods of the analysis and for commenting on the manuscript.
This study was supported by Janssen Global Services, LLC.
Conflict of interest
MW and AN are employees of the Swedish Institute for Health Economics, which provides consulting services for governmental bodies, academic institutions, and commercial life science enterprises (including Janssen Global Services, LLC). CA was an employee of the Swedish Institute for Health Economics at the initiation of the study and is currently an employee of ESiOR Oy, which provides consulting services to governmental bodies, academic institutions, and commercial life science enterprises. AS is an employee of Axio Research, LLC. CN is an employee of Janssen Scientific Affairs, LLC.
Availability of Data and Material
Data from the CANVAS Program are available in the public domain via the Yale University Open Data Access Project (http://yoda.yale.edu/).
All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by all authors. The first draft of the manuscript was written by Michael Willis and Andreas Nilsson, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
No code will be made available.
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Willis, M., Asseburg, C., Slee, A. et al. Macrovascular Risk Equations Based on the CANVAS Program. PharmacoEconomics (2021). https://doi.org/10.1007/s40273-021-01001-0