Pavel J. Fatulla, Henrik Imberg, I. Hirsch, T. Heise, M. Lind
{"title":"967-P: Evaluation of CV and SD as Glucose Variability Metrics Based on Data from the GOLD and SILVER Trials","authors":"Pavel J. Fatulla, Henrik Imberg, I. Hirsch, T. Heise, M. Lind","doi":"10.2337/db23-967-p","DOIUrl":null,"url":null,"abstract":"Objective: Coefficient of variation (CV) and standard deviation (SD) are key metrics of glucose variability (GV) in clinical care and research. We evaluated the adequacy of CV and SD as GV metrics over a wide range of mean blood glucose (MBG) levels in people with (T1D).\n Methods: Analyses were performed on data from the randomized clinical GOLD and SILVER trials (n=160). Mixed effects models were used to evaluate the SD in relation to MBG during stable therapy, accounting for subject-specific trends and correlations in repeated measures data.\n Results: The SD of blood glucose levels did not increase linearly with MBG level during CGM and blood glucose monitoring (BGM) treatments (both p<0.0001). The lack-of-fit of the constant CV model was most distinct at high glucose levels >12 mmol/L (Fig.). During BGM, a 33% reduction in MBG from 12 to 8 mmol/L was associated with a 20% (95% CI 14.9 to 24.9%) reduction in SD. The treatment effect on MBG-adjusted GV measured by CV was underestimated by 27%, compared to an adjusted analysis accounting for a quadratic relation between SD and MBG.\n Conclusion: CV is not an optimal GV measure since SD changes less than the MBG during stable glucose-lowering therapy. A quadratic model adjusting SD to MBG is instead suggested when evaluating glucose-lowering therapies in people with T1D.\n Fig. - Association between SD and MBG in the GOLD and SILVER trials during stable glucose-monitoring method CGM/SMBG.\n \n \n \n P.J.Fatulla: None. H.Imberg: None. I.B.Hirsch: Consultant; Abbott Diabetes, Lifecare, Inc., Hagar, Research Support; Beta Bionics, Inc., Insulet Corporation, Dexcom, Inc. T.Heise: Advisory Panel; Novo Nordisk, Consultant; Gan & Lee Pharmaceuticals, Research Support; Adocia, AstraZeneca, Biocon, Crinetics Pharmaceuticals, Inc., Eli Lilly and Company, Genova, Novo Nordisk, Sanofi, Zealand Pharma A/S, Speaker's Bureau; Eli Lilly and Company, Novo Nordisk. M.Lind: Consultant; AstraZeneca, Eli Lilly and Company, Novo Nordisk, Research Support; Eli Lilly and Company.\n","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":" ","pages":""},"PeriodicalIF":6.2000,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2337/db23-967-p","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Coefficient of variation (CV) and standard deviation (SD) are key metrics of glucose variability (GV) in clinical care and research. We evaluated the adequacy of CV and SD as GV metrics over a wide range of mean blood glucose (MBG) levels in people with (T1D).
Methods: Analyses were performed on data from the randomized clinical GOLD and SILVER trials (n=160). Mixed effects models were used to evaluate the SD in relation to MBG during stable therapy, accounting for subject-specific trends and correlations in repeated measures data.
Results: The SD of blood glucose levels did not increase linearly with MBG level during CGM and blood glucose monitoring (BGM) treatments (both p<0.0001). The lack-of-fit of the constant CV model was most distinct at high glucose levels >12 mmol/L (Fig.). During BGM, a 33% reduction in MBG from 12 to 8 mmol/L was associated with a 20% (95% CI 14.9 to 24.9%) reduction in SD. The treatment effect on MBG-adjusted GV measured by CV was underestimated by 27%, compared to an adjusted analysis accounting for a quadratic relation between SD and MBG.
Conclusion: CV is not an optimal GV measure since SD changes less than the MBG during stable glucose-lowering therapy. A quadratic model adjusting SD to MBG is instead suggested when evaluating glucose-lowering therapies in people with T1D.
Fig. - Association between SD and MBG in the GOLD and SILVER trials during stable glucose-monitoring method CGM/SMBG.
P.J.Fatulla: None. H.Imberg: None. I.B.Hirsch: Consultant; Abbott Diabetes, Lifecare, Inc., Hagar, Research Support; Beta Bionics, Inc., Insulet Corporation, Dexcom, Inc. T.Heise: Advisory Panel; Novo Nordisk, Consultant; Gan & Lee Pharmaceuticals, Research Support; Adocia, AstraZeneca, Biocon, Crinetics Pharmaceuticals, Inc., Eli Lilly and Company, Genova, Novo Nordisk, Sanofi, Zealand Pharma A/S, Speaker's Bureau; Eli Lilly and Company, Novo Nordisk. M.Lind: Consultant; AstraZeneca, Eli Lilly and Company, Novo Nordisk, Research Support; Eli Lilly and Company.
期刊介绍:
Diabetes is a scientific journal that publishes original research exploring the physiological and pathophysiological aspects of diabetes mellitus. We encourage submissions of manuscripts pertaining to laboratory, animal, or human research, covering a wide range of topics. Our primary focus is on investigative reports investigating various aspects such as the development and progression of diabetes, along with its associated complications. We also welcome studies delving into normal and pathological pancreatic islet function and intermediary metabolism, as well as exploring the mechanisms of drug and hormone action from a pharmacological perspective. Additionally, we encourage submissions that delve into the biochemical and molecular aspects of both normal and abnormal biological processes.
However, it is important to note that we do not publish studies relating to diabetes education or the application of accepted therapeutic and diagnostic approaches to patients with diabetes mellitus. Our aim is to provide a platform for research that contributes to advancing our understanding of the underlying mechanisms and processes of diabetes.