10-year Risk Prediction Models of Complications and Mortality of DM in Hong Kong

NCT ID: NCT03299010

Last Updated: 2024-12-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Total Enrollment

141516 participants

Study Classification

OBSERVATIONAL

Study Start Date

2017-07-01

Study Completion Date

2019-12-31

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

Diabetes Mellitus (DM) is a well-recognized public health issue worldwide. DM can lead to many complications resulting in morbidity and mortality, approximately 70% of DM related deaths were attributed to cardiovascular diseases (CVD).

Objectives:

To develop 10-year risk prediction models for CVD, end stage renal disease (ESRD) and all-cause mortality among Chinese patients with DM in primary care.

Hypotheses:

1. Patient socio-demographic, clinical parameters, disease characteristics and treatment modalities are predictive of 10-year risk of CVD, ESRD and all-cause mortality.
2. Risk prediction models developed from this study should have over 70% of discriminating power.

Design and Subjects:

10-year retrospective cohort study. All Chinese patients who were clinically diagnosed to have DM and were receiving care in the public (Hospital Authority) primary care clinics on or before 1 July 2006 will be followed up until 31 December 2016.

Main outcomes measures:

For total CVD, CHD, stroke, heart failure, ESRD, all-cause mortality

1. 10-year incidence;
2. Predictive factors

Data analysis:

Two thirds of subjects will be randomly selected as the training sample for model development. Cox regressions will be used to develop sex-specific 10-year risk prediction models for each outcome. The validity of models will be tested on the remaining one third of subjects by Harrell C statistics and ROC

Expected results:

Risk prediction models will enable accurate risk stratification and cost-effective interventions for Chinese DM patients in primary care.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

This study aims to develop 10-year risk prediction models for total CVD and all-cause mortality among Chinese diabetic patients in primary care. Risk prediction models for individual DM complications including CHD, heart failure, stroke and ESRD will also be developed.

The objectives are to:

1. Calculate the 10 years incidence of total CVD, all-cause mortality and each major DM complication in Chinese DM patients in primary care.
2. Determine the risk factors that significantly predict total CVD, all-cause mortality and each major DM complication for Chinese DM patients in primary care.
3. Develop and validate risk prediction models for total CVD, all-cause mortality and each major DM complication for Chinese DM patients in primary care.
4. Develop a risk prediction nomogram and chart for the risk of total CVD, all-cause mortality for Chinese DM patients in primary care

Hypotheses:

1. Patient socio-demographic, clinical parameters, disease characteristics, and treatment modalities are predictive of 10-year risk of total CVD, all-cause mortality and individual DM complication as a dependent variable.
2. The risk prediction models for total CVD, all-cause mortality and individual DM complication developed in this study can have over 70% of discriminating power.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Diabetes Mellitus Cardiovascular Diseases Mortality Primary Health Care

Keywords

Explore important study keywords that can help with search, categorization, and topic discovery.

Diabetes Mellitus Risk Complications Mortality Cardiovascular Diseases Chinese Prediction

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

DM patient

Patients with a documented clinical diagnosis of DM and were receiving care in the Hospital Authority (HA) primary care General Out-Patient Clinics (GOPC) and Family Medicine Clinics (FMC) on or before 1 July 2006 identified from the HA clinical management system (CMS) database.

No interventions assigned to this group

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

1. At least 1 GOPC/FMC attendance on or within 1 year before 1 July 2006
2. Had a CMS (Clinical Management System) record in the Hospital Authority (HA) of the coding of ICPC-2 of T89 (Diabetes insulin dependent) or T90 (Diabetes non-insulin dependent) on or before 1 July 2006

Exclusion Criteria

1. Patients who had a diagnosis of any DM complications defined by the relevant ICPC-2 or ICD-9-CM on or before 1 July 2006
2. Patients exclusively managed by Specialist Out-Patient Clinic (SOPC) on or before 1 July 2006.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

The University of Hong Kong

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Professor Cindy L.K. Lam

Head of Department

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

Learn about the lead researchers overseeing the trial and their institutional affiliations.

Cindy L.K. Lam

Role: PRINCIPAL_INVESTIGATOR

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

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

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

Hong Kong, Hong Kong, China

Site Status

The University of Hong Kong

Hong Kong, , Hong Kong

Site Status

Countries

Review the countries where the study has at least one active or historical site.

China Hong Kong

References

Explore related publications, articles, or registry entries linked to this study.

Dong W, Fong DYT, Yoon JS, Wan EYF, Bedford LE, Tang EHM, Lam CLK. Generative adversarial networks for imputing missing data for big data clinical research. BMC Med Res Methodol. 2021 Apr 20;21(1):78. doi: 10.1186/s12874-021-01272-3.

Reference Type DERIVED
PMID: 33879090 (View on PubMed)

Wan EYF, Yu EYT, Chin WY, Fung CSC, Kwok RLP, Chao DVK, Chan KH, Hui EM, Tsui WWS, Tan KCB, Fong DYT, Lam CLK. Ten-year risk prediction models of complications and mortality of Chinese patients with diabetes mellitus in primary care in Hong Kong: a study protocol. BMJ Open. 2018 Oct 15;8(10):e023070. doi: 10.1136/bmjopen-2018-023070.

Reference Type DERIVED
PMID: 30327405 (View on PubMed)

Provided Documents

Download supplemental materials such as informed consent forms, study protocols, or participant manuals.

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Related Links

Access external resources that provide additional context or updates about the study.

https://doi.org/10.1186/s12875-021-01493-x

Review on continuity of care on health outcomes in patients with DM/HT

https://doi.org/10.3399/BJGP.2023.0150

Continuity of care and complications in patients with HT

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

HKUCTR-2232

Identifier Type: -

Identifier Source: org_study_id