IDEAS home Printed from https://ideas.repec.org/a/spr/pharme/v36y2018i9d10.1007_s40273-018-0662-1.html
   My bibliography  Save this article

Novel Risk Engine for Diabetes Progression and Mortality in USA: Building, Relating, Assessing, and Validating Outcomes (BRAVO)

Author

Listed:
  • Hui Shao

    (Tulane University)

  • Vivian Fonseca

    (Tulane University)

  • Charles Stoecker

    (Tulane University)

  • Shuqian Liu

    (Tulane University)

  • Lizheng Shi

    (Tulane University)

Abstract

Background There is an urgent need to update diabetes prediction, which has relied on the United Kingdom Prospective Diabetes Study (UKPDS) that dates back to 1970 s’ European populations. Objective The objective of this study was to develop a risk engine with multiple risk equations using a recent patient cohort with type 2 diabetes mellitus reflective of the US population. Methods A total of 17 risk equations for predicting diabetes-related microvascular and macrovascular events, hypoglycemia, mortality, and progression of diabetes risk factors were estimated using the data from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (n = 10,251). Internal and external validation processes were used to assess performance of the Building, Relating, Assessing, and Validating Outcomes (BRAVO) risk engine. One-way sensitivity analysis was conducted to examine the impact of risk factors on mortality at the population level. Results The BRAVO risk engine added several risk factors including severe hypoglycemia and common US racial/ethnicity categories compared with the UKPDS risk engine. The BRAVO risk engine also modeled mortality escalation associated with intensive glycemic control (i.e., glycosylated hemoglobin

Suggested Citation

  • 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.
    • Handle: RePEc:spr:pharme:v:36:y:2018:i:9:d:10.1007_s40273-018-0662-1
    DOI: 10.1007/s40273-018-0662-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40273-018-0662-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40273-018-0662-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jorge Elgart & Joaquin Caporale & Lorena Gonzalez & Eleonora Aiello & Maximiliano Waschbusch & Juan Gagliardino, 2013. "Treatment of type 2 diabetes with saxagliptin: a pharmacoeconomic evaluation in Argentina," Health Economics Review, Springer, vol. 3(1), pages 1-9, December.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dongzhe Hong & Lei Si & Minghuan Jiang & Hui Shao & Wai-kit Ming & Yingnan Zhao & Yan Li & Lizheng Shi, 2019. "Cost Effectiveness of Sodium-Glucose Cotransporter-2 (SGLT2) Inhibitors, Glucagon-Like Peptide-1 (GLP-1) Receptor Agonists, and Dipeptidyl Peptidase-4 (DPP-4) Inhibitors: A Systematic Review," PharmacoEconomics, Springer, vol. 37(6), pages 777-818, June.
    2. Alexandre Baptista & Inês Teixeira & Sónia Romano & António Vaz Carneiro & Julian Perelman, 2017. "The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic review of cost-effectiveness studies," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(8), pages 937-965, November.
    3. Xinyang Hua & Thomas Wai-Chun Lung & Andrew Palmer & Lei Si & William H. Herman & Philip Clarke, 2017. "How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review," PharmacoEconomics, Springer, vol. 35(3), pages 319-329, March.
    4. 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.
    5. Jonathan Karnon & Hossein Haji Ali Afzali, 2014. "When to Use Discrete Event Simulation (DES) for the Economic Evaluation of Health Technologies? A Review and Critique of the Costs and Benefits of DES," PharmacoEconomics, Springer, vol. 32(6), pages 547-558, June.
    6. 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.
    7. Jinsong Geng & Hao Yu & Yiwei Mao & Peng Zhang & Yingyao Chen, 2015. "Cost Effectiveness of Dipeptidyl Peptidase-4 Inhibitors for Type 2 Diabetes," PharmacoEconomics, Springer, vol. 33(6), pages 581-597, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:pharme:v:36:y:2018:i:9:d:10.1007_s40273-018-0662-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.