TY - JOUR
T1 - Development of a hypoglycaemia risk score to identify high-risk individuals with advanced type 2 diabetes in DEVOTE
AU - DEVOTE Study Group
AU - Heller, Simon
AU - Lingvay, Ildiko
AU - Marso, Steven P.
AU - Philis-Tsimikas, Athena
AU - Pieber, Thomas R.
AU - Poulter, Neil R.
AU - Pratley, Richard E.
AU - Hachmann-Nielsen, Elise
AU - Kvist, Kajsa
AU - Lange, Martin
AU - Moses, Alan C.
AU - Trock Andresen, Marie
AU - Buse, John B.
N1 - Funding Information:
S.H. has served on speaker panels for MSD, Eli Lilly, Takeda, Novo Nordisk and AstraZeneca, for which he has received remuneration. He has served on advisory panels or as a consultant for Zeeland, UNEEG Medical, Boehringer Ingelheim, Novo Nordisk, Eli Lilly and Takeda, for which his institution has received remuneration. I.L. received funds for research, consulting, editorial support and/or travel expenses from Novo Nordisk, Eli Lilly, Sanofi, AstraZeneca, Boehringer Ingelheim, Merck, Novartis, Intarcia, MannKind, TARGETPharma, GI Dynamics and Pfizer. S.P.M. has received personal fees from Abbott Vascular, Novo Nordisk, University of Oxford, AstraZeneca, Bristol‐Myers Squibb, Asahi‐Intec and Boehringer Ingelheim, and research support from Novo Nordisk. D.K.M. has led clinical trials for AstraZeneca, Boehringer Ingelheim, Eisai, Esperion, GlaxoSmithKline, Janssen, Lexicon, Merck & Co. Inc., Novo Nordisk and Sanofi Aventis, and has received consultancy fees from AstraZeneca, Boehringer Ingelheim, Lilly, Merck & Co. Inc., Pfizer, Novo Nordisk, Metavant and Sanofi Aventis. A.P.T. has served on advisory panels for Eli Lilly and Co, Dexcom, Inc. and Voluntis, provided consultancy services for Novo Nordisk A/S and Sanofi US, and received research support from Merck & Co., Inc, Novo Nordisk A/S, Sanofi US, Eli Lilly and Co, AstraZeneca, Janssen Pharmaceuticals, Inc. and Genentech, Inc. A.P.T. did not receive any direct or indirect payment for these services. She is supported by grants from the US National Institutes of Health (R01DK112322, R18DK104250, R01NR015754 and 1UL1TR002550). T.R.P. has received research support from Novo Nordisk and AstraZeneca (paid directly to the Medical University of Graz), and personal fees as a consultant from AstraZeneca, Bristol‐Myers Squibb, Eli Lilly, Novo Nordisk and Roche Diabetes Care. T.R.P. is also the Chief Scientific Officer of CBmed (Centre for Biomarker Research in Medicine), a public‐funded biomarker research company. N.R.P. has received personal fees from Servier, Takeda, Novo Nordisk and AstraZeneca in relation to speakers' fees and advisory board activities (concerning diabetes mellitus), and research grants for his research group (relating to type 2 diabetes) from Diabetes UK, the UK National Institute for Health Research Efficacy and Mechanism Evaluation (NIHR EME), Julius Clinical and the British Heart Foundation. R.E.P.'s services were paid directly to AdventHealth, a non‐profit organization. He reports speaker fees from Novo Nordisk, consulting fees from Novo Nordisk, Merck, Pfizer, Sanofi, Scohia Pharmaceuticals Inc. and Sun Pharmaceuticals Inc., and grants from Hanmi Pharmaceutical Co., Janssen, Novo Nordisk, Poxel SA and Sanofi. K.K., M.L. and M.T.A. are full‐time employees of, and hold stock in, Novo Nordisk A/S. E.H.N. is a full‐time employee of Novo Nordisk A/S. A.C.M. was an employee of Novo Nordisk during the conduct of DEVOTE. He now serves as an independent consultant, including consulting for Novo Nordisk, and retains shares in Novo Nordisk A/S. J.B.B.'s contracted consulting fees and associated travel support are paid to the University of North Carolina by Adocia, AstraZeneca, Dance Biopharm, Eli Lilly, MannKind, NovaTarg, Novo Nordisk, Sanofi, Senseonics, vTv Therapeutics and Zafgen, and he receives grant support from Novo Nordisk, Sanofi, Tolerion and vTv Therapeutics. He is also a consultant to Cirius Therapeutics Inc, CSL Behring, Mellitus Health, Neurimmune AG, Pendulum Therapeutics and Stability Health. He holds stock/options in Mellitus Health, Pendulum Therapeutics, PhaseBio and Stability Health. He is supported by grants from the US National Institutes of Health (UL1TR002489, U01DK098246, UC4DK108612, U54DK118612, P30DK124723), the Patient‐Centred Outcomes Research Institute and the American Diabetes Association.
Funding Information:
DEVOTE and this secondary analysis were sponsored and funded by Novo Nordisk (Bagsvaerd, Denmark).
Funding Information:
We thank the trial investigators, staff and patients for their participation, and Francesca Hemingway and Helen Marshall of Watermeadow Medical?an Ashfield company, part of UDG Healthcare plc, for providing medical writing and editorial support (sponsored by Novo Nordisk). DEVOTE research activities were supported at numerous US centres by Clinical and Translational Science Awards from the US National Institutes of Health's National Centre for Advancing Translational Science. DEVOTE and this secondary analysis were sponsored and funded by Novo Nordisk (Bagsvaerd, Denmark). The trial sponsor was involved in the design of DEVOTE and this secondary analysis; the collection, and analysis of data; and writing the clinical report. J.B.B. received support from The US National Institutes of Health (UL1TR002489, P30DK124723). All authors interpreted the data and wrote the manuscript together with the sponsor's medical writing services team. The funders of the study had no role in the approval of the manuscript or the decision to submit for publication.
Funding Information:
We thank the trial investigators, staff and patients for their participation, and Francesca Hemingway and Helen Marshall of Watermeadow Medical—an Ashfield company, part of UDG Healthcare plc, for providing medical writing and editorial support (sponsored by Novo Nordisk). DEVOTE research activities were supported at numerous US centres by Clinical and Translational Science Awards from the US National Institutes of Health's National Centre for Advancing Translational Science.
Publisher Copyright:
© 2020 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.
PY - 2020/12
Y1 - 2020/12
N2 - Aims: The ability to differentiate patient populations with type 2 diabetes at high risk of severe hypoglycaemia could impact clinical decision making. The aim of this study was to develop a risk score, using patient characteristics, that could differentiate between populations with higher and lower 2-year risk of severe hypoglycaemia among individuals at increased risk of cardiovascular disease. Materials and methods: Two models were developed for the risk score based on data from the DEVOTE cardiovascular outcomes trials. The first, a data-driven machine-learning model, used stepwise regression with bidirectional elimination to identify risk factors for severe hypoglycaemia. The second, a risk score based on known clinical risk factors accessible in clinical practice identified from the data-driven model, included: insulin treatment regimen; diabetes duration; sex; age; and glycated haemoglobin, all at baseline. Both the data-driven model and simple risk score were evaluated for discrimination, calibration and generalizability using data from DEVOTE, and were validated against the external LEADER cardiovascular outcomes trial dataset. Results: Both the data-driven model and the simple risk score discriminated between patients at higher and lower hypoglycaemia risk, and performed similarly well based on the time-dependent area under the curve index (0.63 and 0.66, respectively) over a 2-year time horizon. Conclusions: Both the data-driven model and the simple hypoglycaemia risk score were able to discriminate between patients at higher and lower risk of severe hypoglycaemia, the latter doing so using easily accessible clinical data. The implementation of such a tool (http://www.hyporiskscore.com/) may facilitate improved recognition of, and education about, severe hypoglycaemia risk, potentially improving patient care.
AB - Aims: The ability to differentiate patient populations with type 2 diabetes at high risk of severe hypoglycaemia could impact clinical decision making. The aim of this study was to develop a risk score, using patient characteristics, that could differentiate between populations with higher and lower 2-year risk of severe hypoglycaemia among individuals at increased risk of cardiovascular disease. Materials and methods: Two models were developed for the risk score based on data from the DEVOTE cardiovascular outcomes trials. The first, a data-driven machine-learning model, used stepwise regression with bidirectional elimination to identify risk factors for severe hypoglycaemia. The second, a risk score based on known clinical risk factors accessible in clinical practice identified from the data-driven model, included: insulin treatment regimen; diabetes duration; sex; age; and glycated haemoglobin, all at baseline. Both the data-driven model and simple risk score were evaluated for discrimination, calibration and generalizability using data from DEVOTE, and were validated against the external LEADER cardiovascular outcomes trial dataset. Results: Both the data-driven model and the simple risk score discriminated between patients at higher and lower hypoglycaemia risk, and performed similarly well based on the time-dependent area under the curve index (0.63 and 0.66, respectively) over a 2-year time horizon. Conclusions: Both the data-driven model and the simple hypoglycaemia risk score were able to discriminate between patients at higher and lower risk of severe hypoglycaemia, the latter doing so using easily accessible clinical data. The implementation of such a tool (http://www.hyporiskscore.com/) may facilitate improved recognition of, and education about, severe hypoglycaemia risk, potentially improving patient care.
KW - risk score
KW - severe hypoglycaemia
KW - type 2 diabetes
UR - http://www.scopus.com/inward/record.url?scp=85087675086&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087675086&partnerID=8YFLogxK
U2 - 10.1111/dom.14208
DO - 10.1111/dom.14208
M3 - Article
C2 - 32996693
AN - SCOPUS:85087675086
VL - 22
SP - 2248
EP - 2256
JO - Diabetes, Obesity and Metabolism
JF - Diabetes, Obesity and Metabolism
SN - 1462-8902
IS - 12
ER -