Development of a Model to Predict 10-Year Risk of Ischemic and Hemorrhagic Stroke and Ischemic Heart Disease Using the China Kadoorie Biobank

One-size-fits-all versus risk-category-based screening interval strategies for cardiovascular disease prevention in Chinese adults: a prospective cohort study

Background

In non-high-risk individuals, risk-category-based atherosclerotic cardiovascular disease (ASCVD) screening strategies may be more cost-effective than one-size-fits-all approaches. However, current decisions are constrained by a lack of research evidence. We aimed to explore appropriate risk-category-based screening interval strategies for non-high-risk individuals in ASCVD primary prevention in the Chinese population.

Methods

We used data from 28,624 participants in the China Kadoorie Biobank (CKB) who had completed at least two field surveys. The risk assessment tools were the 10-year ASCVD risk prediction models developed based on the CKB cohort. We constructed multistate Markov models to model disease progression and estimate transition probabilities between different risk categories. The total person-years spent unidentified in the high-risk state over a 10-year period were calculated for each screening interval protocol. We also estimated the number of ASCVD events prevented, quality-adjusted life years (QALYs) gained, and costs saved when compared to the 3-yearly screening protocol.

Findings

When compared to the uniform 3-yearly protocol, most risk-category-based screening interval protocols would identify more high-risk individuals timely, thus preventing more ASCVD events and gaining QALYs. A few of them would reduce total health-care costs. The protocol, which used 6-year, 3-year, and 2-year screening intervals for low-risk, intermediate-low-risk, and intermediate-high risk individuals, was optimal, and would reduce the person-years spent unidentified in the high-risk category by 17.9% (95% CI: 13.1%-21.9%), thus preventing an estimated 113 thousand (95% CI: 83-138) hard ASCVD events for Chinese adults aged 30-79 over a 10-year period. When using a lower cost of statin therapy, more screening protocols would gain QALYs while saving costs.

Interpretation

For the primary prevention of ASCVD, risk-category-based screening protocols outperformed the one-size-fits-all approach in the Chinese population.

Funding

This work was supported by National Natural Science Foundation of China (82192904, 82388102, 82192900) and grants (2023YFC2509400) from the National Key R&D Program of China. The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), grants (2016YFC0900500) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 91846303, 81941018), and Chinese Ministry of Science and Technology (2011BAI09B01).

Prediction model of malnutrition in hospitalized patients with acute stroke

OBJECTIVE

The prognosis of stroke patients is greatly threatened by malnutrition. However, there is no model to predict the risk of malnutrition in hospitalized stroke patients. This study developed a predictive model for identifying high-risk malnutrition in stroke patients.

METHODS

Stroke patients from two tertiary hospitals were selected as the objects. Binary logistic regression was used to build the model. The model's performance was evaluated using various metrics including the receiver operating characteristic curve, Hosmer-Lemeshow test, sensitivity, specificity, Youden index, clinical decision curve, and risk stratification.

RESULTS

A total of 319 stroke patients were included in the study. Among them, 27% experienced malnutrition while in the hospital. The prediction model included all independent variables, including dysphagia, pneumonia, enteral nutrition, Barthel Index, upper arm circumference, and calf circumference (all p < 0.05). The AUC area in the modeling group was 0.885, while in the verification group, it was 0.797. The prediction model produces greater net clinical benefit when the risk threshold probability is between 0% and 80%, as revealed by the clinical decision curve. All p values of the Hosmer test were > 0.05. The optimal cutoff value for the model was 0.269, with a sensitivity of 0.849 and a specificity of 0.804. After risk stratification, the MRS scores and malnutrition incidences increased significantly with escalating risk levels (p < 0.05) in both modeling and validation groups.

CONCLUSIONS

This study developed a prediction model for malnutrition in stroke patients. It has been proven that the model has good differentiation and calibration.

Epidemiology and current management of cardiovascular disease in China

The Annual Report on Cardiovascular Health and Diseases in China (2022) intricate landscape of cardiovascular health in China. This is the fourth section of the report with a specific focus on epidemiology and current management of cardiovascular disease (CVD) in China. This section of the report highlights the epidemiological trends of CVD in China. It reveal a concerning rise in prevalence, with approximately 330 million affected individuals, including significant numbers with stroke, coronary artery disease (CAD), heart failure, and other conditions. CVD stands as the primary cause of mortality among both urban and rural populations, accounting for nearly half of all deaths in 2020. Mortality rates are notably higher in rural areas compared to urban centers since 2009. While age-standardized mortality rates have decreased, the absolute number of CVD deaths has increased, primarily due to population aging. Ischemic heart disease, hemorrhagic and ischemic strokes are the leading causes of CVD-related deaths. Notably, the burden of atherosclerotic cardiovascular disease has risen substantially, with atherosclerotic cardiovascular disease-related deaths increasing from 1990 to 2016. The incidence of ischemic stroke and ischemic heart disease has shown similar increasing trends over the past three decades. CAD mortality, particularly acute myocardial infarction, has been on the rise, with higher mortality rates observed in rural areas since 2016. The prevalence of CAD has increased significantly, with over 11 million patients identified in 2013. Studies assessing hospital performance in managing acute coronary syndrome reveal gaps in adherence to guideline-recommended strategies, with disparities in care quality across hospitals. However, initiatives like the China Patient-centered Evaluative Assessment of Cardiac Events (PEACE)-Retrospective AMI Study and the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome (CCC-ACS) project aim to improve patient outcomes through enhanced care protocols. Moreover, advancements in medical technology, such as quantitative flow ratio-guided lesion selection during percutaneous coronary intervention, show promise in improving clinical outcomes for patients undergoing intervention.

Predictive value of 8-year blood pressure measures in intracerebral hemorrhage risk over 5 years

AIMS

The relationships between long-term blood pressure (BP) measures and intracerebral hemorrhage (ICH), as well as their predictive ability on ICH, were unclear. We aimed to investigate the independent associations of multiple BP measures with subsequent 5-year ICH risk, as well as the incremental value of these measures over a single-point BP measurement in ICH risk prediction.

METHODS

We included 12,398 participants from the China Kadoorie Biobank (CKB) who completed three surveys every four to five years. The following long-term BP measures were calculated: mean, minimum, maximum, standard deviation, coefficient of variation, average real variability, and cumulative BP exposure (cumBP). Cox proportional hazard models were used to examine the associations between these measures and ICH. The potential incremental value of these measures in ICH risk prediction was assessed using Harrell's C statistics, continuous net reclassification improvement (cNRI), and relative integrated discrimination improvement (rIDI).

RESULTS

The hazard ratios (95% confidence intervals) of incident ICH associated with per SD increase in cumSBP and cumDBP were 1.62 (1.25, 2.10) and 1.59 (1.23, 2.07), respectively. When cumBP was added to the conventional 5-year ICH risk prediction model, the C-statistic change was 0.009 (-0.001, 0.019), the cNRI was 0.267 (0.070, 0.464), and the rIDI was 18.2% (5.8%, 30.7%). Further subgroup analyses revealed a consistent increase in cNRI and rIDI in men, rural residents, and participants without diabetes. Other long-term BP measures showed no statistically significant associations with incident ICH and generally did not improve model performance.

CONCLUSION

The nearly 10-year cumBP was positively associated with an increased 5-year risk of ICH and could significantly improve risk reclassification for the ICH risk prediction model that included single-point BP measurement.

Association of household solid fuel use and long-term exposure to ambient air pollution with estimated 10-year high cardiovascular disease risk among postmenopausal women

This study aimed to explore the separate and joint effects of long-term ambient air pollution and household air pollution exposure on 10-year high cardiovascular disease (CVD) risk among postmenopausal women. A total of 4679 postmenopausal women from the China Health and Retirement Longitudinal Study (CHARLS) were included in this study. Information of fuel type was collected by standard questionnaires and use of solid fuel was considered as a proxy for household air pollution. Data of ambient air pollutants (PM1, PM2.5, PM10, SO2, NO2, CO, O3) were obtained from the ChinaHighAirPollutants (CHAP) datasets. Logistic regression models were performed to assess the separate and joint effects of long-term exposure to ambient air pollution and use of solid fuel on 10-year high CVD risk. We found use of solid fuel and its duration and ambient air pollutants (PM1, PM2.5, PM10, SO2, NO2) were all positively associated with 10-year high CVD risk among postmenopausal women (P < 0.05). Compared to those used clean fuel and exposed to low ambient air pollution levels, odds ratios (ORs) and 95% confidence intervals (CIs) for participants using solid fuels and exposed to high ambient air pollution levels (PM1, PM2.5, PM10, SO2, NO2, CO, O3) were 1.66 (1.35, 2.05), 1.66 (1.35, 2.04), 1.49 (1.22, 1.83), 1.28 (1.05, 1.57), 1.67 (1.34, 2.07), 1.28 (1.04, 1.57), 1.46 (1.18, 1.80), respectively. Moreover, significant additive interactions of solid fuel use with PM1 and PM2.5 on 10-year high CVD risk were observed, with approximately 18% and 23% of 10-year high risk of CVD attributable to the interaction. Overall, indoor and outdoor air pollution had separate and joint effects on 10-year high CVD risk among postmenopausal women. Therefore, simultaneously improving indoor and outdoor air quality are of great importance and could have a joint impact on prevention of CVD and improved health among postmenopausal women.

Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores: evidence from the China Kadoorie Biobank

BACKGROUND

Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population.

METHODS

Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training ( n = 28,490) and testing sets ( n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21-I23 and fatal I20-I25) and soft CAD (all fatal or nonfatal I20-I25) were analyzed separately.

RESULTS

In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19-1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (-0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4-6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model.

CONCLUSIONS

In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.

Associations of polygenic risk scores with risks of stroke and its subtypes in Chinese

BACKGROUND AND PURPOSE

Previous studies, mostly focusing on the European population, have reported polygenic risk scores (PRSs) might achieve risk stratification of stroke. We aimed to examine the association strengths of PRSs with risks of stroke and its subtypes in the Chinese population.

METHODS

Participants with genome-wide genotypic data in China Kadoorie Biobank were split into a potential training set (n=22 191) and a population-based testing set (n=72 150). Four previously developed PRSs were included, and new PRSs for stroke and its subtypes were developed. The PRSs showing the strongest association with risks of stroke or its subtypes in the training set were further evaluated in the testing set. Cox proportional hazards regression models were used to estimate the association strengths of different PRSs with risks of stroke and its subtypes (ischaemic stroke (IS), intracerebral haemorrhage (ICH) and subarachnoid haemorrhage (SAH)).

RESULTS

In the testing set, during 872 919 person-years of follow-up, 8514 incident stroke events were documented. The PRSs of any stroke (AS) and IS were both positively associated with risks of AS, IS and ICH (p<0.05). The HR for per SD increment (HRSD) of PRSAS was 1.10 (95% CI 1.07 to 1.12), 1.10 (95% CI 1.07 to 1.12) and 1.13 (95% CI 1.07 to 1.20) for AS, IS and ICH, respectively. The corresponding HRSD of PRSIS was 1.08 (95% CI 1.06 to 1.11), 1.08 (95% CI 1.06 to 1.11) and 1.09 (95% CI 1.03 to 1.15). PRSICH was positively associated with the risk of ICH (HRSD=1.07, 95% CI 1.01 to 1.14). PRSSAH was not associated with risks of stroke and its subtypes. The addition of current PRSs offered little to no improvement in stroke risk prediction and risk stratification.

CONCLUSIONS

In this Chinese population, the association strengths of current PRSs with risks of stroke and its subtypes were moderate, suggesting a limited value for improving risk prediction over traditional risk factors in the context of current genome-wide association study under-representing the East Asian population.