A clinical prediction model to distinguish maturity-onset diabetes of the young from type 1 and type 2 diabetes in the Chinese population

AbstractMaturity-onset diabetes of the youth (MODY), is a genetically and clinically heterogeneous group of diseasesand is often misdiagnosed as type 1 or type 2 diabetes. The aim of this study is to investigate both novel and proven mutations of 11A panel of 11We identified 28 (65%) point mutations among 43 patients. Eighteen patients haveThis is the first study including molecular studies of 11

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Establishment of Clinical Prediction Model Based on the Study of Risk Factors of Stroke in Patients With Type 2 Diabetes Mellitus

Frontiers in Endocrinology ◽

10.3389/fendo.2020.00559 ◽

2020 ◽

Vol 11 ◽

Author(s):

Rong Shi ◽

Taotao Zhang ◽

Hui Sun ◽

Fan Hu

Keyword(s):

Diabetes Mellitus ◽

Risk Factors ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Prediction Model ◽

Clinical Prediction ◽

Clinical Prediction Model ◽

Model Based

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Predicting risk of pancreatic cancer in individuals with new-onset type-2 diabetes in primary care: protocol for the development and validation of a clinical prediction model (QPancreasD)

10.1101/2021.12.22.21268161 ◽

2021 ◽

Author(s):

Pui San Tan ◽

Ashley Clift ◽

Weiqi Liao ◽

Martina Patone ◽

Carol Coupland ◽

...

Keyword(s):

Type 2 Diabetes ◽

Primary Care ◽

Pancreatic Cancer ◽

Prediction Model ◽

Individual Risk ◽

Diabetes Diagnosis ◽

Clinical Prediction ◽

Clinical Prediction Model ◽

New Onset

Background Pancreatic cancer continues to have an extremely poor prognosis in part due to late diagnosis. 25% of pancreatic cancer patients have a prior diagnosis of diabetes, and hence identifying individuals at risk of pancreatic cancer in those with recently diagnosed type 2 diabetes may be a useful opportunity to identify candidates for screening and early detection. In this study, we will comparatively evaluate regression and machine learning-based clinical prediction models for estimating individual risk of developing pancreatic cancer two years after type 2 diabetes diagnosis. Methods In the development dataset, we will include adults aged 30-84 years with incident type-2 diabetes registered with QResearch primary care database. Patients will be followed up from type-2 diabetes diagnosis to first diagnosis of pancreatic cancer as recorded in any one of primary care records, hospital episode statistics, cancer registry data, or death records. Cox-proportional hazards models will be used to develop a risk prediction model for estimating individual risk of developing pancreatic cancer during up to 2 years of follow-up. We will perform variable selection using a combination of clinical and statistical significance approach i.e. HR <0.9 or >1.1 and p<0.01. Linear predictors and baseline survivor function at 2 years will be used to compute absolute risk predictions. Internal-external cross-validation (IECV) framework across geographical regions within England will be used to assess performance and pooled using random effects meta-analysis using: (i) model fit in terms of variation explained by the model Royston & Sauerbrei's R2D, (ii) calibration slope and calibration-in-the-large, and (iii) discrimination measured in terms of Harrell's C and Royston & Sauerbrei's D-statistic. Further, we will evaluate machine learning (ML) approaches for the clinical prediction model using neural networks (NN) and XGBoost. The model predictors and performance of these will be compared with the results of those derived from the regression-based strategy. Discussion The proposed study will develop and validate a novel risk prediction model to aid early diagnosis of pancreatic cancer in patients with new-onset diabetes in primary care. With an enhanced decision-risk tool for use at point-of care by general practitioners to assess pancreatic cancer risk, it may improve decision-making so that at-risk patients are rapidly prioritised to aid early diagnosis of pancreatic cancer in patients with newly diagnosed diabetes.

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Maturity-onset diabetes of the young (MODY): an update

Journal of Pediatric Endocrinology and Metabolism ◽

10.1515/jpem-2014-0384 ◽

2015 ◽

Vol 28 (3-4) ◽

Cited By ~ 41

Author(s):

Ahmet Anık ◽

Gönül Çatlı ◽

Ayhan Abacı ◽

Ece Böber

Keyword(s):

Type 2 Diabetes ◽

Type 1 Diabetes ◽

Young Adults ◽

Maturity Onset Diabetes ◽

Monogenic Disorders ◽

Onset Diabetes ◽

Dependent Form ◽

Insulin Dependent

AbstractMaturity-onset diabetes of the young (MODY) is a group of monogenic disorders characterized by autosomal dominantly inherited non-insulin dependent form of diabetes classically presenting in adolescence or young adults before the age of 25 years. MODY is a rare cause of diabetes (1% of all cases) and is frequently misdiagnosed as Type 1 diabetes (T1DM) or Type 2 diabetes (T2DM). A precise molecular diagnosis is essential because it leads to optimal treatment of the patients and allows early diagnosis for their asymptomatic family members. Mutations in the glucokinase (

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Pregnancy Complicated by Maternal MODY 3 and Paternal MODY 2 Diabetes and Subsequent Rapidly Falling Insulin Requirement

Case Reports in Obstetrics and Gynecology ◽

10.1155/2018/9451061 ◽

2018 ◽

Vol 2018 ◽

pp. 1-5 ◽

Cited By ~ 1

Author(s):

Anastasia Mikuscheva ◽

Adel Mekhail ◽

Benjamin J. Wheeler

Keyword(s):

Type 2 Diabetes ◽

Pregnant Woman ◽

Preterm Labour ◽

Insulin Requirement ◽

Monogenic Diabetes ◽

Maturity Onset Diabetes ◽

Insulin Requirements ◽

Onset Diabetes

Background. ‘Maturity-Onset Diabetes of the Young’ (MODY) or monogenic diabetes accounts for approximately 1–2% of diabetes and is frequently misdiagnosed as type 1 or type 2 diabetes. Here we report a case of a 19-year-old pregnant woman with a MODY 3 diabetes expecting a child to a father with MODY 2 diabetes. Possible inheritance scenarios are described and the implications of these scenarios on the pregnancy and infant are discussed. In addition, the pregnancy was complicated by drastically falling insulin requirements in the mother in the 3rd trimester as well as preterm labour and delivery at 33+4 weeks of gestation.

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Derivation and validation of a clinical prediction model for assessing the risk of lower extremity amputation in patients with type 2 diabetes

Diabetes Research and Clinical Practice ◽

10.1016/j.diabres.2020.108231 ◽

2020 ◽

Vol 165 ◽

pp. 108231

Author(s):

Chia-Ing Li ◽

Cheng-Chieh Lin ◽

Hui-Man Cheng ◽

Chiu-Shong Liu ◽

Chih-Hsueh Lin ◽

...

Keyword(s):

Type 2 Diabetes ◽

Lower Extremity ◽

Prediction Model ◽

Lower Extremity Amputation ◽

Clinical Prediction ◽

Clinical Prediction Model ◽

Extremity Amputation

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Maturity-onset diabetes of the young: difficult differential diagnosis

Russian Medical Inquiry ◽

10.32364/2587-6821-2020-4-6-372-376 ◽

2020 ◽

Vol 4 (6) ◽

pp. 372-376

Author(s):

K.G. Lobanova ◽

◽

V.V. Titova ◽

K.S. Dolgova ◽

◽

...

Keyword(s):

Type 2 Diabetes ◽

Type 1 Diabetes ◽

Differential Diagnosis ◽

Genetic Testing ◽

Molecular Genetic ◽

Maturity Onset Diabetes ◽

Molecular Genetic Testing ◽

Onset Diabetes

Maturity-onset diabetes of the young (MODY) is a monogenic variant of diabetes characterized by the primary dysfunctions of pancreatic β-cells. MODY accounts for 1–2% of all variants of diabetes. MODY is generally associated with HNF1A gene mutation. The hallmarks of MODY are an autosomal dominant inheritance pattern, the onset of the disease in the young age, stable C-peptide level over a long period, the lack of the autoantibodies considered as the markers of diabetes, and the lack of ketoacidosis at disease onset. Considering that MODY manifests in children and young individuals, these patients are commonly diagnosed with type 1 diabetes. However, due to the atypical clinical signs of type 1 diabetes and the similarity of this disease to type 2 diabetes, these patients are often misdiagnosed with type 2 diabetes. This case report illustrates the differential diagnosis of diabetes in a patient with unusual disease course. The attention is focused on the features of MODY course. The indications to molecular genetic testing to verify the diagnosis are addressed.KEYWORDS: diabetes, maturity-onset diabetes of the young, monogenic diabetes, sulfonylureas, molecular genetic testing, LADA, pancreatogenic diabetes.FOR CITATION: Lobanova K.G., Titova V.V., Dolgova K.S. Maturity-onset diabetes of the young: difficult differential diagnosis. Russian Medical Inquiry. 2020;4(6):372–376. DOI: 10.32364/2587-6821-2020-4-6-372-376.

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Maturity-onset diabetes of the young (MODY): Recognition is the need of the hour.

JMS SKIMS ◽

10.33883/jms.v22i2.486 ◽

2019 ◽

Vol 22 (2) ◽

Author(s):

Javaid Bhat ◽

Shariq Rashid Masoodi ◽

Moomin Hussain Bhat

Keyword(s):

Type 2 Diabetes ◽

Cell Function ◽

Early Adulthood ◽

Genetic Diagnosis ◽

Dominant Mode ◽

Maturity Onset Diabetes ◽

Primary Defect ◽

Onset Diabetes

Maturity-onset diabetes of the young (MODY) is a monogenic form of diabetes that is characterized by autosomal dominant mode of inheritance, an early onset diabetes, mostly mild hyperglycemia as a result of a primary defect in pancreatic β-cell function. MODY represents less than 2% of all diabetes cases and is commonly misdiagnosed as type 1 or type 2 diabetes mellitus. It is a genetically heterogeneous form of monogenic diabetes that is caused by mutations occurring in a number of different genes thus tends to cause a slightly different variant of diabetes. At least 14 MODY subtypes with distinct genetic etiologies have been identified to date. MODY is typically diagnosed during late childhood, adolescence, or early adulthood and is usually observed to develop in adults during their late 50's. One of the main drawbacks in its diagnosis is that many people with MODY are misdiagnosed as having type 1 or type 2 diabetes owing to low index of suspicion and lack of availability of genetic testing at affordable cost. However, a molecular and genetic diagnosis results in a better treatment and could also help in identifying other family members with MODY. A high index of suspicion is required to diagnose cases of MODY as misdiagnosis and inappropriate treatment may have a significant impact on quality of life (QOL) with increased cost and unnecessary treatment with insulin.

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