Development and Validation of DM and Pre-DM Risk Prediction Model

NCT04881383 | Completed

• 1 other identifier: UW19-831
• Study Type: observational
• Target: 1,014
• Locations: 1 country
• Sites: 1

Brief Summary

Many DM and pre-DM remain undiagnosed. The aim is to develop and validate a risk prediction function to detect DM and pre-DM in Chinese adults aged 18-84 in primary care (PC). The objectives are to:

1. 1.Develop a risk prediction function using non-laboratory parameters to predict DM and pre-DM from the data of the HK Population Health Survey 2014/2015
2. 2.Develop a risk scoring algorithm and determine the cut-off score
3. 3.Validate the risk prediction function and determine its sensitivity in predicting DM and pre-DM in PC

Conditions

Diabetes Mellitus; Pre Diabetes

Keywords

Risk prediction model; Early detection; Non-laboratory based

Outcome Measures

Primary Outcomes (1)

• The sensitivity of the risk prediction function in detecting DM and pre-DM in primary care

  To validate the risk prediction functions, each of the models developed by logistic regressions or machine learning will be applied to the prospective data collected from subjects recruited from the participating primary care clinics. Overall sensitivity will be assessed by applying the risk threshold score to the validation data and a ROC curve of predicted risk against observed events (DM and pre-DM).

  12 months

Secondary Outcomes (4)

• Area under curve (AUC) of the risk prediction function in detecting DM and pre-DM in primary care

  12 months

• Specificity of the risk prediction function in detecting DM and pre-DM in primary care

  12 months

• Positive predictive value (PPV) of the risk prediction function in detecting DM and pre-DM in primary care

  12 months

• Negative predictive value (NPV) of the risk prediction function in detecting DM and pre-DM in primary care

  12 months

Study Arms (1)

Patients from Primary Care Clinics

Participating Chinese adults aged 18-84 from Primary Care clinics to validate the risk prediction function. Each subject will complete an assessment on the relevant risk factors and have a blood test on OGTT and HbA1c on recruitment and at 12 months.

Diagnostic Test: OGTT and HbA1c

Interventions

OGTT and HbA1c DIAGNOSTIC_TEST

An investigation form will be given to the patient to attend an approved private laboratory for blood pressure, weight, height, waist and hip circumferences, and a blood test on OGTT, HbA1c, complete blood count (CBC) and lipid profile within three months

Patients from Primary Care Clinics

Eligibility Criteria

• Age: 18 Years - 84 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Chinese adults aged 18-84 attending Primary Clinics clinics with no previous history of DM, CVD, cancer, CKD and anaemia

You may qualify if:

• PHS 2014/2015 participants
• Completed the health examination including physical measurements (body height, weight, BMI, waist and hip circumference) and blood tests (fasting plasma glucose, HbA1c and lipid profile) during PHS 2014/2015
• aged 18-84 years

You may not qualify if:

• Doctor-diagnosed DM
• Doctor-diagnosed high blood glucose
• Doctor-diagnosed cardiovascular disease (coronary heart disease, stroke)
• Doctor-diagnosed cancer
• Doctor-diagnosed chronic kidney disease
• Doctor-diagnosed anaemia
• (Validation study)
• Chinese
• aged 18-84 years
• Can communicate in Chinese
• Consent to participate in the study
• Doctor-diagnosed DM
• Doctor-diagnosed high blood glucose
• Doctor-diagnosed cardiovascular disease (coronary heart disease, stroke)
• Doctor-diagnosed cancer

Sponsors & Collaborators

• The University of Hong Kong: lead

Study Sites (1)

Department of Family Medicine & Primary Care, LKS Faculty of Medicine, University of Hong Kong

Hong Kong, Hong Kong

Location

Related Publications (1)

• Dong W, Cheng WHG, Tse ETY, Mi Y, Wong CKH, Tang EHM, Yu EYT, Chin WY, Bedford LE, Ko WWK, Chao DVK, Tan KCB, Lam CLK. Development and validation of a diabetes mellitus and prediabetes risk prediction function for case finding in primary care in Hong Kong: a cross-sectional study and a prospective study protocol paper. BMJ Open. 2022 May 24;12(5):e059430. doi: 10.1136/bmjopen-2021-059430.

  PMID: 35613775 DERIVED

MeSH Terms

Conditions

Diabetes Mellitus; Glucose Intolerance

Interventions

Glucose Tolerance Test

Condition Hierarchy (Ancestors)

Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Hyperglycemia

Intervention Hierarchy (Ancestors)

Blood Chemical Analysis; Clinical Chemistry Tests; Clinical Laboratory Techniques; Diagnostic Techniques and Procedures; Diagnosis; Diagnostic Techniques, Endocrine; Investigative Techniques

Study Officials

• Cindy LK Lam, MD

  Department of Family Medicine and Primary Care, University of Hong Kong

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Danny D. B. Ho Professor in Family Medicine and Head of Department

Study Record Dates

• First Submitted: May 4, 2021
• First Posted: May 11, 2021
• Study Start: April 1, 2020
• Primary Completion: June 30, 2023
• Study Completion: September 30, 2023
• Last Updated: December 10, 2024

Record last verified: 2024-12

Locations

HK (1)