Diabetes & Metabolism Journal

Original Article

Metabolic Risk/Epidemiology
Predictive Models for Type 2 Diabetes Mellitus in Han Chinese with Insights into Cross-Population Applicability and Demographic Specific Risk Factors: Ying-Erh Chen, Djeane Debora Onthoni, Shao-Yuan Chuang, Guo-Hung Li, Yong-Sheng Zhuang, Hung-Yi Chiou, Wayne Huey-Herng Sheu, Ren-Hua Chung; Received June 20, 2024 Accepted January 6, 2025 Published online May 21, 2025; DOI: https://doi.org/10.4093/dmj.2024.0319 [Epub ahead of print]

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Abstract PDF: Background
The rising global incidence of type 2 diabetes mellitus (T2DM) underscores the need for predictive models that enhance early detection and prevention across diverse populations. This study aimed to identify predictors of incident T2DM within a Han Chinese population, assess their impact across various age and sex demographics, and explore their applicability to European populations.
Methods
Using data from about 65,000 participants in the Taiwan Biobank (TWB), we developed a predictive model, achieving an area under the receiver operating characteristic curve of 90.58%. Key predictors were identified through LASSO regression within the TWB cohort and validated using over 4 million records from Taiwan’s Adult Preventive Healthcare Services (APHS) program and the UK Biobank (UKB).
Results
Our analysis highlighted 13 significant predictors, including established factors like glycosylated hemoglobin (HbA1c) and blood glucose levels, and less conventionally considered variables such as peak expiratory flow. Notable differences in the effects of HbA1c levels and polygenic risk scores between the TWB and UKB cohorts were observed. Additionally, age and sex-specific impacts of these predictors, detailed through APHS data, revealed significant variances; for instance, waist circumference and diagnosed mixed hyperlipidemia showed greater impacts in younger females than in males, while effects remained uniform across male age groups.
Conclusion
Our findings offer novel insights into the diagnosis and management of diabetes for the Han Chinese and potentially for broader East Asian populations, highlighting the importance of ethnic and demographic diversity in developing predictive models for early detection and personalized intervention strategies.

Brief Report

Technology/Device
Do-It-Yourself Open Artificial Pancreas System in Children and Adolescents with Type 1 Diabetes Mellitus: Real-World Data: Min Sun Choi, Seunghyun Lee, Jiwon Kim, Gyuri Kim, Sung Min Park, Jae Hyeon Kim; Diabetes Metab J. 2022;46(1):154-159. Published online November 23, 2021; DOI: https://doi.org/10.4093/dmj.2021.0011

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Abstract PDF Supplementary Material PubReader ePub

Few studies have been conducted among Asian children and adolescents with type 1 diabetes mellitus (T1DM) using do-it-yourself artificial pancreas system (DIY-APS). We evaluated real-world data of pediatric T1DM patients using DIY-APS. Data were obtained for 10 patients using a DIY-APS with algorithms. We collected sensor glucose and insulin delivery data from each participant for a period of 4 weeks. Average glycosylated hemoglobin was 6.2%±0.3%. The mean percentage of time that glucose level remained in the target range of 70 to 180 mg/dL was 82.4%±7.8%. Other parameters including time above range, time below range and mean glucose were also within the recommended level, similar to previous commercial and DIY-APS studies. However, despite meeting the target range, unadjusted gaps were still observed between the median basal setting and temporary basal insulin, which should be handled by healthcare providers.

Citations

Citations to this article as recorded by

Real-world efficacy and safety of open-source automated insulin delivery for people with type 1 diabetes mellitus: Experience from mainland China
Yongwen Zhou, Mengyun Lei, Daizhi Yang, Ping Ling, Ying Ni, Hongrong Deng, Wen Xu, Xubin Yang, Benjamin John Wheeler, Jianping Weng, Jinhua Yan
Diabetes Research and Clinical Practice.2024; 218: 111910. CrossRef
Advances in Continuous Glucose Monitoring and Integrated Devices for Management of Diabetes with Insulin-Based Therapy: Improvement in Glycemic Control
Jee Hee Yoo, Jae Hyeon Kim
Diabetes & Metabolism Journal.2023; 47(1): 27. CrossRef
Open-source automated insulin delivery systems (OS-AIDs) in a pediatric population with type 1 diabetes in a real-life setting: the AWeSoMe study group experience
Judith Nir, Marianna Rachmiel, Abigail Fraser, Yael Lebenthal, Avivit Brener, Orit Pinhas-Hamiel, Alon Haim, Eve Stern, Noa Levek, Tal Ben-Ari, Zohar Landau
Endocrine.2023; 81(2): 262. CrossRef
Efficacy and safety of Android artificial pancreas system use at home among adults with type 1 diabetes mellitus in China: protocol of a 26-week, free-living, randomised, open-label, two-arm, two-phase, crossover trial
Mengyun Lei, Beisi Lin, Ping Ling, Zhigu Liu, Daizhi Yang, Hongrong Deng, Xubin Yang, Jing Lv, Wen Xu, Jinhua Yan
BMJ Open.2023; 13(8): e073263. CrossRef
Barriers to Uptake of Open-Source Automated Insulin Delivery Systems: Analysis of Socioeconomic Factors and Perceived Challenges of Caregivers of Children and Adolescents With Type 1 Diabetes From the OPEN Survey
Antonia Huhndt, Yanbing Chen, Shane O’Donnell, Drew Cooper, Hanne Ballhausen, Katarzyna A. Gajewska, Timothée Froment, Mandy Wäldchen, Dana M. Lewis, Klemens Raile, Timothy C. Skinner, Katarina Braune
Frontiers in Clinical Diabetes and Healthcare.2022;[Epub] CrossRef
Toward Personalized Hemoglobin A1c Estimation for Type 2 Diabetes
Namho Kim, Da Young Lee, Wonju Seo, Nan Hee Kim, Sung-Min Park
IEEE Sensors Journal.2022; 22(23): 23023. CrossRef

Original Article

Drug/Regimen
Efficacy and Safety of Self-Titration Algorithms of Insulin Glargine 300 units/mL in Individuals with Uncontrolled Type 2 Diabetes Mellitus (The Korean TITRATION Study): A Randomized Controlled Trial: Jae Hyun Bae, Chang Ho Ahn, Ye Seul Yang, Sun Joon Moon, Soo Heon Kwak, Hye Seung Jung, Kyong Soo Park, Young Min Cho; Diabetes Metab J. 2022;46(1):71-80. Published online June 16, 2021; DOI: https://doi.org/10.4093/dmj.2020.0274

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Background
To compare the efficacy and safety of two insulin self-titration algorithms, Implementing New Strategies with Insulin Glargine for Hyperglycemia Treatment (INSIGHT) and EDITION, for insulin glargine 300 units/mL (Gla-300) in Korean individuals with uncontrolled type 2 diabetes mellitus (T2DM).
Methods
In a 12-week, randomized, open-label trial, individuals with uncontrolled T2DM requiring basal insulin were randomized to either the INSIGHT (adjusted by 1 unit/day) or EDITION (adjusted by 3 units/week) algorithm to achieve a fasting self-monitoring of blood glucose (SMBG) in the range of 4.4 to 5.6 mmol/L. The primary outcome was the proportion of individuals achieving a fasting SMBG ≤5.6 mmol/L without noct urnal hypoglycemia at week 12.
Results
Of 129 individuals (age, 64.1±9.5 years; 66 [51.2%] women), 65 and 64 were randomized to the INSIGHT and EDITION algorithms, respectively. The primary outcome of achievement was comparable between the two groups (24.6% vs. 23.4%, P=0.876). Compared with the EDITION group, the INSIGHT group had a greater reduction in 7-point SMBG but a similar decrease in fasting plasma glucose and glycosylated hemoglobin. The increment of total daily insulin dose was significantly higher in the INSIGHT group than in the EDITION group (between-group difference: 5.8±2.7 units/day, P=0.033). However, body weight was significantly increased only in the EDITION group (0.6±2.4 kg, P=0.038). There was no difference in the occurrence of hypoglycemia between the two groups. Patient satisfaction was significantly increased in the INSIGHT group (P=0.014).
Conclusion
The self-titration of Gla-300 using the INSIGHT algorithm was effective and safe compared with that using the EDITION algorithm in Korean individuals with uncontrolled T2DM (ClinicalTrials.gov number: NCT03406663).

Citations

Citations to this article as recorded by

Comparison of Insulin Titration Strategies for Glycemic Control in Type 2 Diabetes: A Systematic Review and Network Meta-analysis
Kansak Boonpattharatthiti, Kirana Wechkunanukul, Noramon Mayang, E Lyn Lee, Anjana Fuangchan, Alice Y.Y. Cheng, Nathorn Chaiyakunapruk, Teerapon Dhippayom
Diabetes Care.2025; 48(5): 837. CrossRef
Time for Using Machine Learning for Dose Guidance in Titration of People With Type 2 Diabetes? A Systematic Review of Basal Insulin Dose Guidance
Camilla Heisel Nyholm Thomsen, Stine Hangaard, Thomas Kronborg, Peter Vestergaard, Ole Hejlesen, Morten Hasselstrøm Jensen
Journal of Diabetes Science and Technology.2024; 18(5): 1185. CrossRef
Comparative efficacy and safety of weekly tirzepatide versus weekly insulin in type 2 diabetes: A network meta‐analysis of randomized clinical trials
Hazem Ayesh, Sajida Suhail, Suhail Ayesh, Kevin Niswender
Diabetes, Obesity and Metabolism.2024; 26(9): 3801. CrossRef
Basal insulin titration algorithms in patients with type 2 diabetes: the simplest is the best (?)
V.I. Katerenchuk
INTERNATIONAL JOURNAL OF ENDOCRINOLOGY (Ukraine).2023; 19(1): 72. CrossRef
Issues of insulin therapy for type 2 diabetes and ways to solve them
V.I. Katerenchuk, A.V. Katerenchuk
INTERNATIONAL JOURNAL OF ENDOCRINOLOGY (Ukraine).2023; 19(3): 240. CrossRef

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