Skip to:

All FSI News News July 13, 2021

A New Validated Tool Helps Predict Lifetime Health Outcomes for Prediabetes and Type 2 Diabetes in Chinese Populations

A research team including APARC's Karen Eggleston developed a new simulation model that supports the economic evaluation of policy guidelines and clinical treatment pathways to tackle diabetes and prediabetes among Chinese and East Asian populations, for whom existing models may not be applicable.
Closeup on hands holding a glucometer

Diabetes is one of the fastest-growing health challenges of the 21st century. On the frontlines of the epidemic rise in the number of people with diabetes is the Asia-Pacific region. China, in particular, has by far the largest absolute burden of diabetes, with an estimated 116 million adults living with the disease accounting for one-quarter of patients with diabetes globally. By 2045, the number of adults living with diabetes in the country is expected to increase to 147 million, not including the large diaspora community China provides worldwide.

Evaluating the health and economic outcomes of diabetes and its complications is vital for formulating health policy. The existing predictive outcomes models for type 2 diabetes, however, were developed and validated in historical European populations and may not be applicable for East Asian populations with their distinct epidemiology and complications. Additionally, the existing models are typically limited to diabetes alone and ignore the progression from prediabetes to diabetes. The lack of an appropriate simulation model for East Asian individuals and prediabetes is a major gap for the economic evaluation of health interventions.

New collaborative research now addresses these limitations. The research team includes APARC’s Asia Health Policy Program Director Karen Eggleston. The researchers developed and validated a patient-level simulation model for predicting lifetime health outcomes of prediabetes and type 2 diabetes in East Asian populations. They report on their findings in the journal PLOS Medicine


Sign up for APARC newsletters to receive our research updates

Modeling Health Outcomes Among East Asian Populations

The chronic progression to diabetes-related complications is apt for computer simulation modeling due to the long-term nature of health outcomes and the time lag for interventions to impact patient outcomes. It is problematic, however, to estimate the impacts of health interventions on East Asian populations with diabetes using existing models, which were developed and validated in European and North American populations with different epidemiology and outcomes.

To fill in this gap, Eggleston and her colleagues set out to develop and validate an outcomes model for the progression of diabetes and related complications in Chinese populations. They compared this new model, called the Chinese Hong Kong Integrated Modeling and Evaluation (CHIME), to two widely used existing models developed and validated in the United Kingdom (known as the United Kingdom Prospective Diabetes Study Outcomes Model 2, or UKPDS-OM2) and in the United States/Canada (called Risk Equations for Complications of type 2 Diabetes, or RECODe). Despite the continuum of risk across the spectrum of risk factor values, these two existing models ignore the progression from prediabetes to diabetes.

The CHIME integrates prediabetes and diabetes into a comprehensive model comprising 13 outcomes. These include mortality, micro- and macrovascular complications, and the development of diabetes. The researchers developed the CHIME simulation model using data from a population-based cohort of 97,628 participants in Hong Kong with type 2 diabetes (43.5%) or prediabetes (56.5%) from 2006 to 2017. Known as the Hong Kong Clinical Management System (CMS), this cohort makes one of the largest Chinese electronic health informatics systems with detailed clinical records. 

The CHIME outperformed the widely used United Kingdom Prospective Diabetes Study Outcomes Model 2 (UKPDS-OM2) and Risk Equations for Complications of type 2 Diabetes (RECODe) models on real-world data.
Karen Eggleston et al

The next step was to externally validate the CHIME model against individual-level data from the China Health and Retirement Longitudinal Study (CHARLS) cohort (2011-2018), a nationally representative longitudinal cohort of middle-aged and elderly Chinese residents age 45 and older. The researchers validated the CHIME model against six outcomes measures recorded in the CHARLS data and an additional 80 endpoints from nine published trials of diabetes patients using simulated cohorts of 100,000 individuals.

Towards Reducing the Disease Burden of Diabetes

The researchers found that the CHIME model outperformed the widely used UKPDS-OM2 and RECODe models on the data used, meaning that the validation of the CHIME model was more accurate for trials with mainly Asian participants than trials with mostly non-Asian participants. The results indicate that the CHIME model is a validated tool for predicting the progression of diabetes and its outcomes, particularly among Chinese and East Asian populations, for which the existing models have been unsuitable.

With the new model, clinicians and health economists can evaluate population health status for prediabetes and diabetes using routinely recorded data and therapies related to the long-term management of diabetes. In particular, the CHIME outcomes model enables them to assess patients' quality of life and measure cost per quality-adjusted life-years over the long-time horizon of chronic disease conditions. The new model thus supports the economic evaluation of policy guidelines and clinical treatment pathways to tackle diabetes and prediabetes, address micro- and macrovascular complications associated with these conditions, and improve life expectancy.

read more

A parent holds a child waiting to be given an infusion at an area hospital in China.
News

In China, Better Financial Coverage Increases Health Care Access and Utilization

Research evidence from China’s Tongxiang county by Karen Eggleston and colleagues indicates that enhanced financial coverage for catastrophic medical expenditures increased health care access and expenditures among resident insurance beneficiaries while decreasing out-of-pocket spending as a portion of total spending.
Logo of the New South Wales Ministry of Health's podcast Future Health
News

Robotics and the Future of Work: Lessons from Nursing Homes in Japan

On the Future Health podcast, Karen Eggleston discusses the findings and implications of her collaborative research into the effects of robot adoption on staffing in Japanese nursing homes.
A woman walks past a mural referring to the Covid-19 coronavirus painted on a wall on December 10, 2020 in New Delhi, India.
News

How COVID-19 Disproportionately Impacts People with Chronic Conditions in India

A collaborative study by a group of researchers including APARC’s Karen Eggleston documents the adverse effects of COVID-19 on people with chronic conditions in India, particularly among poor, rural, and marginalized populations. The pandemic’s impacts extend beyond health disparities to encompass psychosocial and economic consequences, the study shows.