Risk estimation for the primary prevention of cardiovascular disease: considerations for appropriate risk prediction model selection.

Cardiovascular diseases remain the number one cause of death globally. Cardiovascular disease risk scores are an integral tool in primary prevention, being used to identify individuals at the highest risk and guide the assignment of preventive interventions. Available risk scores differ substantially in terms of the population sample data sources used for their derivation and, consequently, in the absolute risks they assign to individuals. Differences in cardiovascular disease epidemiology between the populations contributing to the development of risk scores, and the target populations in which they are applied, can result in overestimation or underestimation of cardiovascular disease risks for individuals, and poorly informed clinical decisions. Given the wide plethora of cardiovascular disease risk scores available, identification of an appropriate risk score for a target population can be challenging. This Review provides an up-to-date overview of guideline-recommended cardiovascular disease risk scores from global, regional, and national contexts, evaluates their comparative characteristics and qualities, and provides guidance on selection of an appropriate risk score.

Evolving Evidence-Based Value Assessment of One-Time Therapies: Tisagenlecleucel as a Case Study.

BACKGROUND: Economic evaluation of one-time therapies during reimbursement decision-making is challenging due to uncertain long-term outcomes. The availability of 5-year outcome data from the ELIANA trial and real-world evidence of tisagenlecleucel, the first chimeric antigen receptor T-cell (CAR-T) therapy, presents an opportunity to re-evaluate the predictions of prior cost-effectiveness analyses (CEAs). OBJECTIVE: To conduct a systematic literature review (SLR) of prior CEAs of tisagenlecleucel for pediatric/young adult relapsed or refractory acute lymphoblastic leukemia (r/r ALL) and evaluate the impact of recently available 5-year efficacy data from ELIANA and advances in CAR-T manufacturing in an updated CEA model. METHODS: OVID MEDLINE/Embase and health technology assessment (HTA) databases were searched for full-text economic evaluations in English reporting cost-effectiveness results for tisagenlecleucel for r/r ALL. Evaluations with publicly reported incremental cost-effectiveness ratios (ICERs) were included in the SLR. Study screening and data abstraction were conducted following PRISMA guidelines. Data extracted included the country/currency, perspective, clinical trial evidence, model structures, long-term efficacy extrapolation approaches (i.e., overall survival [OS]), time horizon, discount rates, and outcomes (i.e., life years [LY], quality-adjusted LY [QALY], and ICERs). The CEA model reported in Wakase et al. was updated using 5-year OS data from ELIANA and the CAR-T infusion rate informed by real-world practice. RESULTS: Sixteen records corresponding to 15 unique studies were included in the SLR (11 publications and 5 HTA reports); all were conducted from the health care system perspective of the respective countries. Most studies found tisagenlecleucel to be cost effective, but all studies' projected 3- and 5-year OS rates for tisagenlecleucel were lower than the observed 3- and 5-year rates, respectively, derived from 5-year ELIANA data. When applying updated OS projections from the most recent ELIANA data cut and higher infusion rates of 92.5% (per the real-world infusion rate)-96.0% (per the manufacturer success rate) to the CEA of Wakase et al., the associated QALYs for tisagenlecleucel increased from 11.6 to 14.6-15.0, and LYs increased from 13.3 to 17.0-17.5. Accordingly, the ICERs for tisagenlecleucel decreased from ¥2,035,071 to ¥1,787,988-¥1,789,048 versus blinatumomab and from ¥2,644,702 to ¥2,257,837-¥2,275,181 versus clofarabine combination therapy in the updated CEA model. CONCLUSIONS AND RELEVANCE: Projections at launch of the likely cost effectiveness of tisagenlecleucel appear to have underestimated its ultimate economic value given more recent trial and real-world data. To balance uncertainty in initial valuation with the need to provide access to novel oncology therapies, payers can consider flexible reimbursement policies alongside ongoing assessments as new data emerge.

Evaluation of Atherosclerotic Cardiovascular Risk Prediction Models in China: Results From the CHERRY Study.

Background: Updated American or Chinese guidelines recommended calculating atherosclerotic cardiovascular disease (ASCVD) risk using the Pooled Cohort Equations (PCE) or Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) models; however, evidence on performance of both models in Asian populations is limited. Objectives: The authors aimed to evaluate the accuracy of the PCE or China-PAR models in a Chinese contemporary cohort. Methods: Data were extracted from the CHERRY (CHinese Electronic health Records Research in Yinzhou) study. Participants aged 40 to 79 years without prior ASCVD at baseline from 2010 to 2016 were included. ASCVD was defined as nonfatal or fatal stroke, nonfatal myocardial infarction, and cardiovascular death. Models were assessed for discrimination and calibration. Results: Among 226,406 participants, 5362 (2.37%) adults developed a first ASCVD event during a median of 4.60 years of follow-up. Both models had good discrimination: C-statistics in men were 0.763 (95% confidence interval [CI]: 0.754-0.773) for PCE and 0.758 (95% CI: 0.749-0.767) for China-PAR; C-statistics in women were 0.820 (95% CI: 0.812-0.829) for PCE and 0.811 (95% CI: 0.802-0.819) for China-PAR. The China-PAR model underpredicted risk by 20% in men and by 40% in women, especially in the highest-risk groups. However, PCE overestimated by 63% in men and inversely underestimated the risk by 34% in women with poor calibration (both P < 0.001). After recalibration, observed and predicted risks by recalibrated PCE were better aligned. Conclusions: In this large-scale population-based study, both PCE and China-PAR had good discrimination in 5-year ASCVD risk prediction. China-PAR outperformed PCE in calibration, whereas recalibration equalized the performance of PCE and China-PAR. Further specific models are needed to improve accuracy in the highest-risk groups.

Multimorbidity of cardiometabolic diseases: prevalence and risk for mortality from one million Chinese adults in a longitudinal cohort study.

OBJECTIVES: The evolution of multimorbidity describes the continuum from a healthy status to the development of a single disease and further progression to multimorbidity with additional diseases. We investigated the evolution of cardiometabolic multimorbidity and risk for mortality in a Chinese population. DESIGN: Longitudinal cohort study using data from the CHinese Electronic health Records Research in Yinzhou (CHERRY) study, with 5.43 million person-years follow-up (median 5.16 years). PARTICIPANTS: Data for 1 038 704 adults (total 22 750 deaths) were analysed. EXPOSURE: Cardiometabolic multimorbidity was defined as ever being diagnosed with two or more of three diseases: hypertension, diabetes and cardiovascular disease (CVD). PRIMARY AND SECONDARY OUTCOME MEASURES: Age-adjusted and sex-adjusted HRs were calculated for all-cause mortality. RESULTS: The cardiometabolic disease status of 105 209 (10.1%) individuals changed during the follow-up. The prevalence of cardiometabolic multimorbidity increased from 2.41% (95% CI: 2.38% to 2.44%) to 5.94% (95% CI: 5.90% to 5.99%). Baseline multimorbidity status showed the HR (95% CI) was 1.37 (1.33 to 1.42) in those with one disease, 1.71 (1.64 to 1.79) in those with two diseases and 2.22 (2.00 to 2.46) in those with three diseases. The highest HRs were observed for CVD only (3.31, 95% CI: 3.05 to 3.59) or diabetes and CVD (3.12, 95% CI: 2.37 to 4.11). Those with hypertension only had the lowest HR (1.26, 95% CI: 1.22 to 1.30). Longitudinal data showed the HRs (95% CI) in patients with one, two and three diseases were 1.36 (1.32 to 1.41), 2.03 (1.96 to 2.10) and 2.16 (2.05 to 2.29), respectively. CONCLUSIONS: The prevalence of cardiometabolic multimorbidity in a general Chinese population increased more than doubled over 5 years, indicating rapid evolution of cardiometabolic multimorbidity. A history of CVD dominates the risk for mortality. A complementary strategy for primary and secondary prevention of cardiometabolic diseases is needed in China.

Performance of atherosclerotic cardiovascular risk prediction models in a rural Northern Chinese population: Results from the Fangshan Cohort Study.

BACKGROUND: Performance of Pooled Cohort Equations (PCEs) for atherosclerotic cardiovascular disease (ASCVD) risks varied across populations. Whether the recently developed Prediction for ASCVD Risk in China (China-PAR) model could accurately predict cardiovascular risks in real practice remains unclear. METHODS: A population-based cohort study in rural Beijing in the "stroke belt" in North China was used to externally validate PCE and China-PAR models for 5-year ASCVD risk prediction. Expected 5-year prediction risk using China-PAR model was compared with PCE (white). The models were assessed for calibration, discrimination, and reclassification. RESULTS: Among 11,169 adults aged 40 to 79 years over a median 6.44 years of follow-up, 1,921 participants developed a first ASCVD event during total 70,951 person-years. China-PAR model fairly predicted ASCVD risk in men but overestimated by 29.4% risk in women (calibration χ2 = 81.4, P < .001). Underestimations were shown by PCE as 76.2% in men and 88.2% in women with poor calibration (both P < .001). However, discrimination was similar in both models: C-statistics in men were 0.685 (95% CI 0.660-0.710) for China-PAR and 0.675 (95% CI 0.649-0.701) for PCE; C-statistics in women were 0.711 (95% CI 0.694-0.728) for China-PAR and 0.714 (95% CI 0.697-0.731) for PCE. Moreover, China-PAR did not substantially improve accuracy of reclassification compared with PCE. CONCLUSIONS: China-PAR outperformed PCE in 5-year ASCVD risk prediction in this rural Northern Chinese population at average population risk level, fairly predicted risk in men, but overestimated risk in women; however, China-PAR did not meaningfully improve the accuracy of discrimination and reclassification at individual risk level.

Using big data to improve cardiovascular care and outcomes in China: a protocol for the CHinese Electronic health Records Research in Yinzhou (CHERRY) Study.

INTRODUCTION: Data based on electronic health records (EHRs) are rich with individual-level longitudinal measurement information and are becoming an increasingly common data source for clinical risk prediction worldwide. However, few EHR-based cohort studies are available in China. Harnessing EHRs for research requires a full understanding of data linkages, management, and data quality in large data sets, which presents unique analytical opportunities and challenges. The purpose of this study is to provide a framework to establish a uniquely integrated EHR database in China for scientific research. METHODS AND ANALYSIS: The CHinese Electronic health Records Research in Yinzhou (CHERRY) Study will extract individual participant data within the regional health information system of an eastern coastal area of China to establish a longitudinal population-based ambispective cohort study for cardiovascular care and outcomes research. A total of 1 053 565 Chinese adults aged over 18 years were registered in the health information system in 2009, and there were 23 394 deaths from 1 January 2009 to 31 December 2015. The study will include information from multiple epidemiological surveys; EHRs for chronic disease management; and health administrative, clinical, laboratory, drug and electronic medical record (EMR) databases. Follow-up of fatal and non-fatal clinical events is achieved through records linkage to the regional system of disease surveillance, chronic disease management and EMRs (based on diagnostic codes from the International Classification of Diseases, tenth revision). The CHERRY Study will provide a unique platform and serve as a valuable big data resource for cardiovascular risk prediction and population management, for primary and secondary prevention of cardiovascular events in China. ETHICS AND DISSEMINATION: The CHERRY Study was approved by the Peking University Institutional Review Board (IRB00001052-16011) in April 2016. Results of the study will be disseminated through published journal articles, conferences and seminar presentations, and on the study website (http://www.cherry-study.org).

Prevalence and Ethnic Pattern of Diabetes and Prediabetes in China in 2013.

Importance: Previous studies have shown increasing prevalence of diabetes in China, which now has the world's largest diabetes epidemic. Objectives: To estimate the recent prevalence and to investigate the ethnic variation of diabetes and prediabetes in the Chinese adult population. Design, Setting, and Participants: A nationally representative cross-sectional survey in 2013 in mainland China, which consisted of 170 287 participants. Exposures: Fasting plasma glucose and hemoglobin A1c levels were measured for all participants. A 2-hour oral glucose tolerance test was conducted for all participants without diagnosed diabetes. Main Outcomes and Measures: Primary outcomes were total diabetes and prediabetes defined according to the 2010 American Diabetes Association criteria. Awareness and treatment were also evaluated. Hemoglobin A1c concentration of less than 7.0% among treated diabetes patients was considered adequate glycemic control. Minority ethnic groups in China with at least 1000 participants (Tibetan, Zhuang, Manchu, Uyghur, and Muslim) were compared with Han participants. Results: Among the Chinese adult population, the estimated standardized prevalence of total diagnosed and undiagnosed diabetes was 10.9% (95% CI, 10.4%-11.5%); that of diagnosed diabetes, 4.0% (95% CI, 3.6%-4.3%); and that of prediabetes, 35.7% (95% CI, 34.1%-37.4%). Among persons with diabetes, 36.5% (95% CI, 34.3%-38.6%) were aware of their diagnosis and 32.2% (95% CI, 30.1%-34.2%) were treated; 49.2% (95% CI, 46.9%-51.5%) of patients treated had adequate glycemic control. Tibetan and Muslim Chinese had significantly lower crude prevalence of diabetes than Han participants (14.7% [95% CI, 14.6%-14.9%] for Han, 4.3% [95% CI, 3.5%-5.0%] for Tibetan, and 10.6% [95% CI, 9.3%-11.9%] for Muslim; P < .001 for Tibetan and Muslim compared with Han). In the multivariable logistic models, the adjusted odds ratios compared with Han participants were 0.42 (95% CI, 0.35-0.50) for diabetes and 0.77 (95% CI, 0.71-0.84) for prediabetes for Tibetan Chinese and 0.73 (95% CI, 0.63-0.85) for diabetes and 0.78 (95% CI, 0.71-0.86) for prediabetes in Muslim Chinese. Conclusions and Relevance: Among adults in China, the estimated overall prevalence of diabetes was 10.9%, and that for prediabetes was 35.7%. Differences from previous estimates for 2010 may be due to an alternate method of measuring hemoglobin A1c.