Vasudha Ahuja1, Pasi Aronen2, T A Pramodkumar3, Helen Looker4, Angela Chetrit5, Aini H Bloigu6, Auni Juutilainen7, Cristina Bianchi8, Lucia La Sala9, Ranjit Mohan Anjana3, Rajendra Pradeepa3, Ulagamadesan Venkatesan3, Sarvanan Jebarani3, Viswanathan Baskar3, Teresa Vanessa Fiorentino10, Patrick Timpel11, Ralph A DeFronzo12, Antonio Ceriello9, Stefano Del Prato8, Muhammad Abdul-Ghani12, Sirkka Keinänen-Kiukaanniemi6,13, Rachel Dankner5,14, Peter H Bennett4, William C Knowler4, Peter Schwarz11,15,16, Giorgio Sesti17, Rie Oka18, Viswanathan Mohan3, Leif Groop19,20, Jaakko Tuomilehto21,22,23, Samuli Ripatti19,24,25, Michael Bergman26, Tiinamaija Tuomi19,20,27. 1. Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland vasudha.ahuja@helsinki.fi. 2. Biostatistics Unit, Faculty of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland. 3. Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialties Centre, ICMR Centre for Advanced Research on Diabetes and IDF Centre of Excellence in Diabetes, Chennai, India. 4. Phoenix Epidemiology and Clinical Research Branch, National Institute for Diabetes and Digestive and Kidney Diseases, Phoenix, AZ. 5. Unit for Cardiovascular Epidemiology, Gertner Institute for Epidemiology and Health Policy Research, Ramat Gan, Israel. 6. Center for Life Course Health Research, University of Oulu, Oulu, Finland. 7. University of Eastern Finland, Kuopio University Hospital, Kuopio, Finland. 8. Section of Diabetes and Metabolic Diseases, Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa, Italy. 9. Department of Cardiovascular and Dysmetabolic Diseases, IRCCS MultiMedica, Milan, Italy. 10. Department of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy. 11. Department of Medicine III, Technical University of Dresden, Dresden, Germany. 12. Division of Diabetes, University of Texas Health Science Center at San Antonio, San Antonio, TX. 13. Healthcare and Social Services of Selänne, Pyhäjärvi, Finland. 14. Department of Epidemiology and Preventive Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. 15. Paul Langerhans Institute of the Helmholtz Zentrum München at the University Hospital Carl Gustav Carus and the Medical Faculty of TU Dresden (PLID), Dresden, Germany. 16. German Center for Diabetes Research (DZD), Neuherberg, Germany. 17. Department of Clinical and Molecular Medicine, Sapienza University of Rome, Rome, Italy. 18. Department of Internal Medicine, Hokuriku Central Hospital, Toyama, Japan. 19. Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland. 20. Lund University Diabetes Centre, Lund University, Malmö, Sweden. 21. Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland. 22. Department of Public Health, University of Helsinki, Helsinki, Finland. 23. Saudi Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia. 24. Department of Public Health, Clinicum, University of Helsinki, Helsinki, Finland. 25. Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA. 26. Division of Endocrinology and Metabolism, Department of Medicine and Department of Population Health, and NYU Langone Diabetes Prevention Program, NYU Grossman School of Medicine, New York, NY. 27. Abdominal Centre, Endocrinology, Helsinki University Hospital, and Folkhalsan Research Centre, Biomedicum, and Research Program Unit, Clinical and Molecular Medicine, University of Helsinki, Helsinki, Finland.
Abstract
OBJECTIVE: One-hour plasma glucose (1-h PG) during the oral glucose tolerance test (OGTT) is an accurate predictor of type 2 diabetes. We performed a meta-analysis to determine the optimum cutoff of 1-h PG for detection of type 2 diabetes using 2-h PG as the gold standard. RESEARCH DESIGN AND METHODS: We included 15 studies with 35,551 participants from multiple ethnic groups (53.8% Caucasian) and 2,705 newly detected cases of diabetes based on 2-h PG during OGTT. We excluded cases identified only by elevated fasting plasma glucose and/or HbA1c. We determined the optimal 1-h PG threshold and its accuracy at this cutoff for detection of diabetes (2-h PG ≥11.1 mmol/L) using a mixed linear effects regression model with different weights to sensitivity/specificity (2/3, 1/2, and 1/3). RESULTS: Three cutoffs of 1-h PG, at 10.6 mmol/L, 11.6 mmol/L, and 12.5 mmol/L, had sensitivities of 0.95, 0.92, and 0.87 and specificities of 0.86, 0.91, and 0.94 at weights 2/3, 1/2, and 1/3, respectively. The cutoff of 11.6 mmol/L (95% CI 10.6, 12.6) had a sensitivity of 0.92 (0.87, 0.95), specificity of 0.91 (0.88, 0.93), area under the curve 0.939 (95% confidence region for sensitivity at a given specificity: 0.904, 0.946), and a positive predictive value of 45%. CONCLUSIONS: The 1-h PG of ≥11.6 mmol/L during OGTT has a good sensitivity and specificity for detecting type 2 diabetes. Prescreening with a diabetes-specific risk calculator to identify high-risk individuals is suggested to decrease the proportion of false-positive cases. Studies including other ethnic groups and assessing complication risk are warranted.
OBJECTIVE: One-hour plasma glucose (1-h PG) during the oral glucose tolerance test (OGTT) is an accurate predictor of type 2 diabetes. We performed a meta-analysis to determine the optimum cutoff of 1-h PG for detection of type 2 diabetes using 2-h PG as the gold standard. RESEARCH DESIGN AND METHODS: We included 15 studies with 35,551 participants from multiple ethnic groups (53.8% Caucasian) and 2,705 newly detected cases of diabetes based on 2-h PG during OGTT. We excluded cases identified only by elevated fasting plasma glucose and/or HbA1c. We determined the optimal 1-h PG threshold and its accuracy at this cutoff for detection of diabetes (2-h PG ≥11.1 mmol/L) using a mixed linear effects regression model with different weights to sensitivity/specificity (2/3, 1/2, and 1/3). RESULTS: Three cutoffs of 1-h PG, at 10.6 mmol/L, 11.6 mmol/L, and 12.5 mmol/L, had sensitivities of 0.95, 0.92, and 0.87 and specificities of 0.86, 0.91, and 0.94 at weights 2/3, 1/2, and 1/3, respectively. The cutoff of 11.6 mmol/L (95% CI 10.6, 12.6) had a sensitivity of 0.92 (0.87, 0.95), specificity of 0.91 (0.88, 0.93), area under the curve 0.939 (95% confidence region for sensitivity at a given specificity: 0.904, 0.946), and a positive predictive value of 45%. CONCLUSIONS: The 1-h PG of ≥11.6 mmol/L during OGTT has a good sensitivity and specificity for detecting type 2 diabetes. Prescreening with a diabetes-specific risk calculator to identify high-risk individuals is suggested to decrease the proportion of false-positive cases. Studies including other ethnic groups and assessing complication risk are warranted.
Authors: Anni Saunajoki; Juha Auvinen; Aini Bloigu; Jouko Saramies; Jaakko Tuomilehto; Hannu Uusitalo; Esko Hussi; Henna Cederberg-Tamminen; Kadri Suija; Sirkka Keinänen-Kiukaanniemi; Markku Timonen Journal: J Clin Med Date: 2022-07-15 Impact factor: 4.964