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Refitting of the UKPDS 68 Risk Equations to Contemporary Routine Clinical Practice Data in the UK

Author

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  • P. McEwan
  • H. Bennett
  • T. Ward
  • K. Bergenheim

Abstract

The results suggest that while the UKPDS equations perform best in newly diagnosed patients, they may overpredict the lifetime risk in this group and underpredict it in patients with more advanced diabetes. Implementation of the revised coefficients will result in different absolute numbers of predicted diabetes-related events; however, they are not expected to significantly affect the conclusions of economic modelling. Copyright Springer International Publishing Switzerland 2015

Suggested Citation

  • 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.
    • Handle: RePEc:spr:pharme:v:33:y:2015:i:2:p:149-161
    DOI: 10.1007/s40273-014-0225-z
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    Cited by:

    1. 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.
    2. Zhuo T. Su & Jose Bartelt-Hofer & Stephen Brown & Elisheva Lew & Luc Sauriol & Lieven Annemans & Daniel T. Grima, 2020. "The Use of Computer Simulation Modeling to Estimate Complications in Patients with Type 2 Diabetes Mellitus: Comparative Validation of the Cornerstone Diabetes Simulation Model," PharmacoEconomics - Open, Springer, vol. 4(1), pages 37-44, March.
    3. Hui Shao & Vivian Fonseca & Charles Stoecker & Shuqian Liu & Lizheng Shi, 2018. "Novel Risk Engine for Diabetes Progression and Mortality in USA: Building, Relating, Assessing, and Validating Outcomes (BRAVO)," PharmacoEconomics, Springer, vol. 36(9), pages 1125-1134, September.

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