Lisa Pennells

AIMS: The aim of this study was to develop, validate, and illustrate an updated prediction model (SCORE2) to estimate 10-year fatal and non-fatal cardiovascular disease (CVD) risk in individuals without previous CVD or diabetes aged 40-69 years in Europe. METHODS AND RESULTS: We derived risk prediction models using individual-participant data from 45 cohorts in 13 countries (677 684 individuals, 30 121 CVD events). We used sex-specific and competing risk-adjusted models, including age, smoking status, systolic blood pressure, and total- and HDL-cholesterol. We defined four risk regions in Europe according to country-specific CVD mortality, recalibrating models to each region using expected incidences and risk factor distributions. Region-specific incidence was estimated using CVD mortality and incidence data on 10 776 466 individuals. For external validation, we analysed data from 25 additional cohorts in 15 European countries (1 133 181 individuals, 43 492 CVD events). After applying the derived risk prediction models to external validation cohorts, C-indices ranged from 0.67 (0.65-0.68) to 0.81 (0.76-0.86). Predicted CVD risk varied several-fold across European regions. For example, the estimated 10-year CVD risk for a 50-year-old smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/L, and HDL-cholesterol of 1.3 mmol/L, ranged from 5.9% for men in low-risk countries to 14.0% for men in very high-risk countries, and from 4.2% for women in low-risk countries to 13.7% for women in very high-risk countries. CONCLUSION: SCORE2-a new algorithm derived, calibrated, and validated to predict 10-year risk of first-onset CVD in European populations-enhances the identification of individuals at higher risk of developing CVD across Europe.

BACKGROUND: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. METHODS: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40-80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. FINDINGS: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629-0·741) to 0·833 (0·783-0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40-64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. INTERPRETATION: We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. FUNDING: World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research.

IMPORTANCE: The prevalence of cardiometabolic multimorbidity is increasing. OBJECTIVE: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity. DESIGN, SETTING, AND PARTICIPANTS: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. EXPOSURES: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI). MAIN OUTCOMES AND MEASURES: All-cause mortality and estimated reductions in life expectancy. RESULTS: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy. CONCLUSIONS AND RELEVANCE: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.

AIMS: The aim of this study was to derive and validate the SCORE2-Older Persons (SCORE2-OP) risk model to estimate 5- and 10-year risk of cardiovascular disease (CVD) in individuals aged over 70 years in four geographical risk regions. METHODS AND RESULTS: Sex-specific competing risk-adjusted models for estimating CVD risk (CVD mortality, myocardial infarction, or stroke) were derived in individuals aged over 65 without pre-existing atherosclerotic CVD from the Cohort of Norway (28 503 individuals, 10 089 CVD events). Models included age, smoking status, diabetes, systolic blood pressure, and total- and high-density lipoprotein cholesterol. Four geographical risk regions were defined based on country-specific CVD mortality rates. Models were recalibrated to each region using region-specific estimated CVD incidence rates and risk factor distributions. For external validation, we analysed data from 6 additional study populations {338 615 individuals, 33 219 CVD validation cohorts, C-indices ranged between 0.63 [95% confidence interval (CI) 0.61-0.65] and 0.67 (0.64-0.69)}. Regional calibration of expected-vs.-observed risks was satisfactory. For given risk factor profiles, there was substantial variation across the four risk regions in the estimated 10-year CVD event risk. CONCLUSIONS: The competing risk-adjusted SCORE2-OP model was derived, recalibrated, and externally validated to estimate 5- and 10-year CVD risk in older adults (aged 70 years or older) in four geographical risk regions. These models can be used for communicating the risk of CVD and potential benefit from risk factor treatment and may facilitate shared decision-making between clinicians and patients in CVD risk management in older persons.

Importance: It is uncertain whether depressive symptoms are independently associated with subsequent risk of cardiovascular diseases (CVDs). Objective: To characterize the association between depressive symptoms and CVD incidence across the spectrum of lower mood. Design, Setting, and Participants: A pooled analysis of individual-participant data from the Emerging Risk Factors Collaboration (ERFC; 162 036 participants; 21 cohorts; baseline surveys, 1960-2008; latest follow-up, March 2020) and the UK Biobank (401 219 participants; baseline surveys, 2006-2010; latest follow-up, March 2020). Eligible participants had information about self-reported depressive symptoms and no CVD history at baseline. Exposures: Depressive symptoms were recorded using validated instruments. ERFC scores were harmonized across studies to a scale representative of the Center for Epidemiological Studies Depression (CES-D) scale (range, 0-60; ≥16 indicates possible depressive disorder). The UK Biobank recorded the 2-item Patient Health Questionnaire 2 (PHQ-2; range, 0-6; ≥3 indicates possible depressive disorder). Main Outcomes and Measures: Primary outcomes were incident fatal or nonfatal coronary heart disease (CHD), stroke, and CVD (composite of the 2). Hazard ratios (HRs) per 1-SD higher log CES-D or PHQ-2 adjusted for age, sex, smoking, and diabetes were reported. Results: Among 162 036 participants from the ERFC (73%, women; mean age at baseline, 63 years [SD, 9 years]), 5078 CHD and 3932 stroke events were recorded (median follow-up, 9.5 years). Associations with CHD, stroke, and CVD were log linear. The HR per 1-SD higher depression score for CHD was 1.07 (95% CI, 1.03-1.11); stroke, 1.05 (95% CI, 1.01-1.10); and CVD, 1.06 (95% CI, 1.04-1.08). The corresponding incidence rates per 10 000 person-years of follow-up in the highest vs the lowest quintile of CES-D score (geometric mean CES-D score, 19 vs 1) were 36.3 vs 29.0 for CHD events, 28.0 vs 24.7 for stroke events, and 62.8 vs 53.5 for CVD events. Among 401 219 participants from the UK Biobank (55% were women, mean age at baseline, 56 years [SD, 8 years]), 4607 CHD and 3253 stroke events were recorded (median follow-up, 8.1 years). The HR per 1-SD higher depression score for CHD was 1.11 (95% CI, 1.08-1.14); stroke, 1.10 (95% CI, 1.06-1.14); and CVD, 1.10 (95% CI, 1.08-1.13). The corresponding incidence rates per 10 000 person-years of follow-up among individuals with PHQ-2 scores of 4 or higher vs 0 were 20.9 vs 14.2 for CHD events, 15.3 vs 10.2 for stroke events, and 36.2 vs 24.5 for CVD events. The magnitude and statistical significance of the HRs were not materially changed after adjustment for additional risk factors. Conclusions and Relevance: In a pooled analysis of 563 255 participants in 22 cohorts, baseline depressive symptoms were associated with CVD incidence, including at symptom levels lower than the threshold indicative of a depressive disorder. However, the magnitude of associations was modest.