Continuous glucose monitoring and metrics for clinical trials: an international consensus statement
Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA as the measure of average blood glucose levels for the 3 months preceding the HbA test date. The use of this measure highlights the long-establi...
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| Vydáno v: | The lancet. Diabetes & endocrinology Ročník 11; číslo 1; s. 42 |
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| Hlavní autoři: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
England
01.01.2023
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| ISSN: | 2213-8595, 2213-8595 |
| On-line přístup: | Zjistit podrobnosti o přístupu |
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| Abstract | Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA
as the measure of average blood glucose levels for the 3 months preceding the HbA
test date. The use of this measure highlights the long-established correlation between HbA
and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA
findings, and further assess the effects of therapeutic interventions on HbA
. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA
concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA
for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability. |
|---|---|
| AbstractList | Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA
as the measure of average blood glucose levels for the 3 months preceding the HbA
test date. The use of this measure highlights the long-established correlation between HbA
and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA
findings, and further assess the effects of therapeutic interventions on HbA
. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA
concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA
for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability. Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA1c as the measure of average blood glucose levels for the 3 months preceding the HbA1c test date. The use of this measure highlights the long-established correlation between HbA1c and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA1c findings, and further assess the effects of therapeutic interventions on HbA1c. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA1c concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA1c for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability.Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA1c as the measure of average blood glucose levels for the 3 months preceding the HbA1c test date. The use of this measure highlights the long-established correlation between HbA1c and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA1c findings, and further assess the effects of therapeutic interventions on HbA1c. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA1c concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA1c for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability. |
| Author | Nimri, Revital Rosenstock, Julio Del Prato, Stefano Garg, Satish Heverly, Julie Nishimura, Rimei Kovatchev, Boris Phillip, Moshe Battelino, Tadej Carroll, James Close, Kelly Ceriello, Antonio Gabbay, Robert Mauricio, Dídac Maahs, David Renard, Eric Chow, Elaine Ueki, Kohjiro Arreaza-Rubin, Guillermo Dutta, Sanjoy Amiel, Stephanie A Kenney, Julia Bergenstal, Richard M Laffel, Lori Umpierrez, Guillermo E Saboo, Banshi Hirsch, Irl B Buckingham, Bruce A Danne, Thomas Mathieu, Chantal Scharf, Mauro Kader, Tina Choudhary, Pratik Alexander, Charles M Beck, Roy W Weinzimer, Stuart A |
| Author_xml | – sequence: 1 givenname: Tadej surname: Battelino fullname: Battelino, Tadej email: tadej.battelino@mf.uni-lj.si organization: Department of Pediatric Endocrinology, Diabetes and Metabolism, University Children's Hospital, University Medical Centre Ljubljana, and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia. Electronic address: tadej.battelino@mf.uni-lj.si – sequence: 2 givenname: Charles M surname: Alexander fullname: Alexander, Charles M organization: diaTribe Foundation, San Francisco, CA, USA – sequence: 3 givenname: Stephanie A surname: Amiel fullname: Amiel, Stephanie A organization: Diabetes Research Group, King's College London, London, UK – sequence: 4 givenname: Guillermo surname: Arreaza-Rubin fullname: Arreaza-Rubin, Guillermo organization: Division of Diabetes, Endocrinology and Metabolic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA – sequence: 5 givenname: Roy W surname: Beck fullname: Beck, Roy W organization: Jaeb Center for Health Research, Tampa, FL, USA – sequence: 6 givenname: Richard M surname: Bergenstal fullname: Bergenstal, Richard M organization: International Diabetes Center, Park Nicollet, Minneapolis, MN, USA – sequence: 7 givenname: Bruce A surname: Buckingham fullname: Buckingham, Bruce A organization: Division of Endocrinology and Diabetes, Department of Pediatrics, Stanford Medical Center, Stanford, CA, USA – sequence: 8 givenname: James surname: Carroll fullname: Carroll, James organization: diaTribe Foundation, San Francisco, CA, USA – sequence: 9 givenname: Antonio surname: Ceriello fullname: Ceriello, Antonio organization: IRCCS MultiMedica, Milan, Italy – sequence: 10 givenname: Elaine surname: Chow fullname: Chow, Elaine organization: Phase 1 Clinical Trial Centre, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China – sequence: 11 givenname: Pratik surname: Choudhary fullname: Choudhary, Pratik organization: Leicester Diabetes Research Centre, University of Leicester, Leicester, UK – sequence: 12 givenname: Kelly surname: Close fullname: Close, Kelly organization: diaTribe Foundation, San Francisco, CA, USA; Close Concerns, San Francisco, CA, USA – sequence: 13 givenname: Thomas surname: Danne fullname: Danne, Thomas organization: Diabetes Centre for Children and Adolescents, Auf der Bult, Hanover, Germany – sequence: 14 givenname: Sanjoy surname: Dutta fullname: Dutta, Sanjoy organization: JDRF, New York, NY, USA – sequence: 15 givenname: Robert surname: Gabbay fullname: Gabbay, Robert organization: American Diabetes Association, Arlington, VA, USA; Harvard Medical School, Harvard University, Boston, MA, USA – sequence: 16 givenname: Satish surname: Garg fullname: Garg, Satish organization: Barbara Davis Centre for Diabetes, University of Colorado Denver, Aurora, CO, USA – sequence: 17 givenname: Julie surname: Heverly fullname: Heverly, Julie organization: diaTribe Foundation, San Francisco, CA, USA – sequence: 18 givenname: Irl B surname: Hirsch fullname: Hirsch, Irl B organization: Division of Metabolism, Endocrinology and Nutrition, University of Washington School of Medicine, University of Washington, Seattle, WA, USA – sequence: 19 givenname: Tina surname: Kader fullname: Kader, Tina organization: Jewish General Hospital, Montreal, QC, Canada – sequence: 20 givenname: Julia surname: Kenney fullname: Kenney, Julia organization: diaTribe Foundation, San Francisco, CA, USA – sequence: 21 givenname: Boris surname: Kovatchev fullname: Kovatchev, Boris organization: Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA – sequence: 22 givenname: Lori surname: Laffel fullname: Laffel, Lori organization: Pediatric, Adolescent and Young Adult Section, Joslin Diabetes Center, Harvard Medical School, Harvard University, Boston, MA, USA – sequence: 23 givenname: David surname: Maahs fullname: Maahs, David organization: Department of Pediatrics, Stanford Diabetes Research Center, Stanford, CA, USA – sequence: 24 givenname: Chantal surname: Mathieu fullname: Mathieu, Chantal organization: Clinical and Experimental Endocrinology, KU Leuven, Leuven, Belgium – sequence: 25 givenname: Dídac surname: Mauricio fullname: Mauricio, Dídac organization: Department of Endocrinology and Nutrition, CIBERDEM (Instituto de Salud Carlos III), Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Barcelona, Spain – sequence: 26 givenname: Revital surname: Nimri fullname: Nimri, Revital organization: National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel – sequence: 27 givenname: Rimei surname: Nishimura fullname: Nishimura, Rimei organization: The Jikei University School of Medicine, Jikei University, Tokyo, Japan – sequence: 28 givenname: Mauro surname: Scharf fullname: Scharf, Mauro organization: Centro de Diabetes Curitiba and Division of Pediatric Endocrinology, Hospital Nossa Senhora das Graças, Curitiba, Brazil – sequence: 29 givenname: Stefano surname: Del Prato fullname: Del Prato, Stefano organization: Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy – sequence: 30 givenname: Eric surname: Renard fullname: Renard, Eric organization: Department of Endocrinology, Diabetes and Nutrition, Montpellier University Hospital, Montpellier, France; Institute of Functional Genomics, University of Montpellier, Montpellier, France; INSERM Clinical Investigation Centre, Montpellier, France – sequence: 31 givenname: Julio surname: Rosenstock fullname: Rosenstock, Julio organization: Velocity Clinical Research, Medical City, Dallas, TX; University of Texas Southwestern Medical Center, University of Texas, Dallas, TX, USA – sequence: 32 givenname: Banshi surname: Saboo fullname: Saboo, Banshi organization: Dia Care, Diabetes Care and Hormone Clinic, Ahmedabad, India – sequence: 33 givenname: Kohjiro surname: Ueki fullname: Ueki, Kohjiro organization: Diabetes Research Center, National Center for Global Health and Medicine, Tokyo, Japan – sequence: 34 givenname: Guillermo E surname: Umpierrez fullname: Umpierrez, Guillermo E organization: Emory University School of Medicine; Grady Health System, Atlanta, GA, USA – sequence: 35 givenname: Stuart A surname: Weinzimer fullname: Weinzimer, Stuart A organization: Department of Pediatrics, Yale University School of Medicine, Yale University, New Haven, CT, USA – sequence: 36 givenname: Moshe surname: Phillip fullname: Phillip, Moshe organization: National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36493795$$D View this record in MEDLINE/PubMed |
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| References | 36739873 - Lancet Diabetes Endocrinol. 2023 Mar;11(3):155. doi: 10.1016/S2213-8587(23)00026-8. 38272612 - Lancet Diabetes Endocrinol. 2024 Feb;12(2):e12. doi: 10.1016/S2213-8587(24)00001-9. |
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| Snippet | Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA
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| Title | Continuous glucose monitoring and metrics for clinical trials: an international consensus statement |
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