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

This study is currently recruiting participants.
Verified September 2017 by Professor Cindy L.K. Lam, The University of Hong Kong
Sponsor:
ClinicalTrials.gov Identifier:
NCT03299010
First Posted: October 2, 2017
Last Update Posted: October 2, 2017
The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
Information provided by (Responsible Party):
Professor Cindy L.K. Lam, The University of Hong Kong
  Purpose

Diabetes Mellitus (DM) is a well-recognized public health issue, affecting 415 million people and costing HK$5.2 trillion in global health expenditures worldwide. It is estimated 568,000 people are living with DM in Hong Kong, and the projected number will increase to 781,000 in 2040. In Hong Kong, the health care costs for diabetic patients are estimated to be HK$2 billion accounting for 4.5% of the gross domestic product (GDP) per capita, and a major health service burden accounting for 200,000 (17% of total) hospital admissions with 1.2 million hospitalization days per year.

DM can lead to many complications resulting in morbidity and mortality. According to the International Diabetes Federation (IDF), in 2015, diabetes led to 5.0 million (14.5% of all deaths) deaths worldwide which translated to one death every six seconds and approximately 70% of DM related deaths were attributed to cardiovascular diseases (CVD). The development of diabetes-related complications significantly increases medical costs. A previous local study also found that the direct medical cost for diabetic patients with CVD were 1.1 times more than patients without CVD in Hong Kong.

Objectives:

To develop 10-year risk prediction models for total CVD and all-cause mortality among Chinese patients with DM in primary care. Risk prediction models for individual DM complications including coronary heart disease, heart failure, stroke and end stage renal disease (ESRD) will also be developed.

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.
  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 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, all-cause mortality and each major DM complication

  1. 10-year incidence;
  2. Predictive factors

Data analysis:

The analyses will be carried out separately for men and women. Two thirds of subjects will be randomly selected as the training sample for model development. Cox regressions will be used to develop 10-year risk prediction models of total CVD, all-cause mortality and each major DM complication. The validity of models will be tested on the remaining one third of subjects by receiver operating characteristic curve.

Expected results:

Risk prediction models for diabetic complications specific to Chinese patients in primary care will enable accurate risk stratification, prioritization of resources and more cost-effective interventions for DM patients in primary care.


Condition
Diabetes Mellitus Cardiovascular Diseases Mortality Primary Health Care

Study Type: Observational
Study Design: Observational Model: Cohort
Time Perspective: Retrospective
Official Title: 10-year Risk Prediction Models of Complications and Mortality of Diabetes Mellitus in Chinese Patients in Primary Care in Hong Kong

Further study details as provided by Professor Cindy L.K. Lam, The University of Hong Kong:

Primary Outcome Measures:
  • The incidence of total CVD, all-cause mortality and each of 4 major DM complications (CHD, stroke, heart failure and ESRD) over 10 years [ Time Frame: 10 years ]

    Calculate the 10 years incidence of total CVD, all-cause mortality and each major DM complication in Chinese DM patients in primary care.

    CVD is defined as the presence of any of CHD, heart failure and stroke. CHD includes all ischaemic heart disease, myocardial infarction, coronary death or sudden death as indicated by the ICPC-2 K74 to K76 or ICD-9-CM 410.x, 411.x to 414.x, 798.x codes. Heart failure is defined by the ICPC-2 K77 or ICD-9-CM 428.x. Stoke (fatal and non-fatal stroke) is defined by the ICPC-2 K89 to K91 or ICD-9-CM 430.x to 438.x codes.


  • Factors predictive of total CVD, all-cause mortality and each of 4 major DM complications (CHD, stroke, heart failure and ESRD) over 10 years [ Time Frame: 10 years ]
    Determine the risk factors that significantly predict total CVD, all-cause mortality and each major DM complication for Chinese DM patients in primary care.

  • 10-year risk prediction models for total CVD, all-cause mortality and each of 4 major DM complications (CHD, stroke, heart failure and ESRD) [ Time Frame: 10 years ]
    Develop and validate risk prediction models for total CVD, all-cause mortality and each major DM complication for Chinese DM patients in primary care.

  • Factors that have sufficient power to classify Chinese DM patients in primary care into risk group in terms of total CVD and all-cause mortality [ Time Frame: 10 years ]
    Develop a risk prediction nomogram and chart for the risk of total CVD, all-cause mortality for Chinese DM patients in primary care


Estimated Enrollment: 70720
Actual Study Start Date: July 1, 2017
Estimated Study Completion Date: June 2019
Estimated Primary Completion Date: July 2018 (Final data collection date for primary outcome measure)
Groups/Cohorts
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.

Detailed Description:

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.
  Eligibility

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Senior)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Sampling Method:   Probability Sample
Study Population
The cohort will include all 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.
Criteria

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.
  Contacts and Locations
Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03299010


Contacts
Contact: Cindy L.K. Lam (852) 25185653 clklam@hku.hk

Locations
Hong Kong
The University of Hong Kong Recruiting
Hong Kong, Hong Kong
Contact: Cindy L.K. Lam    (852) 25185653    clklam@hku.hk   
Sponsors and Collaborators
The University of Hong Kong
Investigators
Principal Investigator: Cindy L.K. Lam Department of Family Medicine and Primary Care, Faculty of Medicine, The University of Hong Kong
  Study Documents (Full-Text)

Documents provided by Professor Cindy L.K. Lam, The University of Hong Kong:
  More Information

Responsible Party: Professor Cindy L.K. Lam, Head of Department, The University of Hong Kong
ClinicalTrials.gov Identifier: NCT03299010     History of Changes
Other Study ID Numbers: HKUCTR-2232
First Submitted: September 27, 2017
First Posted: October 2, 2017
Last Update Posted: October 2, 2017
Last Verified: September 2017

Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Professor Cindy L.K. Lam, The University of Hong Kong:
Diabetes Mellitus
Risk
Complications
Mortality
Cardiovascular Diseases
Chinese
Prediction

Additional relevant MeSH terms:
Diabetes Mellitus
Cardiovascular Diseases
Glucose Metabolism Disorders
Metabolic Diseases
Endocrine System Diseases