| 1. |
- Hageman, S., et al.
(författare)
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SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe
- 2021
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Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 42:25, s. 2439-2454
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Ostergaard, H. B., et al.
(författare)
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Development and Validation of a Lifetime Risk Model for Kidney Failure and Treatment Benefit in Type 2 Diabetes 10-Year and Lifetime Risk Prediction Models
- 2022
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Ingår i: Clinical Journal of the American Society of Nephrology. - : Ovid Technologies (Wolters Kluwer Health). - 1555-9041 .- 1555-905X. ; 17:12, s. 1783-1791
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Tidskriftsartikel (refereegranskat)abstract
- Background and objectives: Individuals with type 2 diabetes are at a higher risk of developing kidney failure. The objective of this study was to develop and validate a decision support tool for estimating 10-year and lifetime risks of kidney failure in individuals with type 2 diabetes as well as estimating individual treatment effects of preventive medication. Design, setting, participants, & measurements: The prediction algorithm was developed in 707,077 individuals with prevalent and incident type 2 diabetes from the Swedish National Diabetes Register for 2002-2019. Two Cox proportional regression functions for kidney failure (first occurrence of kidney transplantation, long-term dialysis, or persistent eGFR < 15 ml/min per 1.73 m(2)) and all-cause mortality as respective end points were developed using routinely available predictors. These functions were combined into life tables to calculate the predicted survival without kidney failure while using all-cause mortality as the competing outcome. The model was externally validated in 256,265 individuals with incident type 2 diabetes from the Scottish Care Information Diabetes database between 2004 and 2019. Results: During a median follow-up of 6.8 years (interquartile range, 3.2-10.6), 8004 (1%) individuals with type 2 diabetes in the Swedish National Diabetes Register cohort developed kidney failure, and 202,078 (29%) died. The model performed well, with c statistics for kidney failure of 0.89 (95% confidence interval, 0.88 to 0.90) for internal validation and 0.74 (95% confidence interval, 0.73 to 0.76) for external validation. Calibration plots showed good agreement in observed versus predicted 10-year risk of kidney failure for both internal and external validation. Conclusions: This study derived and externally validated a prediction tool for estimating 10-year and lifetime risks of kidney failure as well as life years free of kidney failure gained with preventive treatment in individuals with type 2 diabetes using easily available clinical predictors.
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| 3. |
- Ostergaard, H. B., et al.
(författare)
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Estimating individual lifetime risk of incident cardiovascular events in adults with Type 2 diabetes: an update and geographical calibration of the DIAbetes Lifetime perspective model (DIAL2)
- 2023
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Ingår i: European Journal of Preventive Cardiology. - : Oxford University Press (OUP). - 2047-4873 .- 2047-4881. ; 30:1, s. 61-69
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Tidskriftsartikel (refereegranskat)abstract
- Aims The 2021 European Society of Cardiology cardiovascular disease (CVD) prevention guidelines recommend the use of (lifetime) risk prediction models to aid decisions regarding intensified preventive treatment options in adults with Type 2 diabetes, e.g. the DIAbetes Lifetime perspective model (DIAL model). The aim of this study was to update the DIAL model using contemporary and representative registry data (DIAL2) and to systematically calibrate the model for use in other European countries. Methods and results The DIAL2 model was derived in 467 856 people with Type 2 diabetes without a history of CVD from the Swedish National Diabetes Register, with a median follow-up of 7.3 years (interquartile range: 4.0-10.6 years) and comprising 63 824 CVD (including fatal CVD, non-fatal stroke and non-fatal myocardial infarction) events and 66 048 non-CVD mortality events. The model was systematically recalibrated to Europe's low- and moderate-risk regions using contemporary incidence data and mean risk factor distributions. The recalibrated DIAL2 model was externally validated in 218 267 individuals with Type 2 diabetes from the Scottish Care Information-Diabetes (SCID) and Clinical Practice Research Datalink (CPRD). In these individuals, 43 074 CVD events and 27 115 non-CVD fatal events were observed. The DIAL2 model discriminated well, with C-indices of 0.732 [95% confidence interval (CI) 0.726-0.739] in CPRD and 0.700 (95% CI 0.691-0.709) in SCID. Conclusion The recalibrated DIAL2 model provides a useful tool for the prediction of CVD-free life expectancy and lifetime CVD risk for people with Type 2 diabetes without previous CVD in the European low- and moderate-risk regions. These long-term individualized measures of CVD risk are well suited for shared decision-making in clinical practice as recommended by the 2021 CVD ESC prevention guidelines.
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| 4. |
- Hageman, Steven H. J., et al.
(författare)
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Estimation of recurrent atherosclerotic cardiovascular event risk in patients with established cardiovascular disease : the updated SMART2 algorithm
- 2022
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Ingår i: European Heart Journal. - : Oxford University Press. - 0195-668X .- 1522-9645. ; 43:18, s. 1715-1727
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Tidskriftsartikel (refereegranskat)abstract
- Aims The 10-year risk of recurrent atherosclerotic cardiovascular disease (ASCVD) events in patients with established ASCVD can be estimated with the Secondary Manifestations of ARTerial disease (SMART) risk score, and may help refine clinical management. To broaden generalizability across regions, we updated the existing tool (SMART2 risk score) and recalibrated it with regional incidence rates and assessed its performance in external populations.Methods and results Individuals with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms were included from the Utrecht Cardiovascular Cohort-SMART cohort [n = 8355; 1706 ASCVD events during a median follow-up of 8.2 years (interquartile range 4.2-12.5)] to derive a 10-year risk prediction model for recurrent ASCVD events (non-fatal myocardial infarction, non-fatal stroke, or cardiovascular mortality) using a Fine and Gray competing risk-adjusted model. The model was recalibrated to four regions across Europe, and to Asia (excluding Japan), Japan, Australia, North America, and Latin America using contemporary cohort data from each target region. External validation used data from seven cohorts [Clinical Practice Research Datalink, SWEDEHEART, the international REduction of Atherothrombosis for Continued Health (REACH) Registry, Estonian Biobank, Spanish Biomarkers in Acute Coronary Syndrome and Biomarkers in Acute Myocardial Infarction (BACS/BAMI), the Norwegian COgnitive Impairment After STroke, and Bialystok PLUS/Polaspire] and included 369 044 individuals with established ASCVD of whom 62 807 experienced an ASCVD event. C-statistics ranged from 0.605 [95% confidence interval (CI) 0.547-0.664] in BACS/BAMI to 0.772 (95% CI 0.659-0.886) in REACH Europe high-risk region. The clinical utility of the model was demonstrated across a range of clinically relevant treatment thresholds for intensified treatment options.Conclusion The SMART2 risk score provides an updated, validated tool for the prediction of recurrent ASCVD events in patients with established ASCVD across European and non-European populations. The use of this tool could allow for a more personalized approach to secondary prevention based upon quantitative rather than qualitative estimates of residual risk.
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| 5. |
- Berkelmans, G. F. N., et al.
(författare)
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Population median imputation was noninferior to complex approaches for imputing missing values in cardiovascular prediction models in clinical practice
- 2022
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Ingår i: Journal of Clinical Epidemiology. - : Elsevier BV. - 0895-4356. ; 145, s. 70-80
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: To compare the validity and robustness of five methods for handling missing characteristics when using cardiovascular disease risk prediction models for individual patients in a real-world clinical setting.& nbsp;Study design and setting: The performance of the missing data methods was assessed using data from the Swedish National Diabetes Registry (n = 419,533) with external validation using the Scottish Care Information ? diabetes database (n = 226,953). Five methods for handling missing data were compared. Two methods using submodels for each combination of available data, two imputation methods: conditional imputation and median imputation, and one alternative modeling method, called the naive approach, based on hazard ratios and populations statistics of known risk factors only. The validity was compared using calibration plots and c-statistics.& nbsp;Results: C-statistics were similar across methods in both development and validation data sets, that is, 0.82 (95% CI 0.82-0.83) in the Swedish National Diabetes Registry and 0.74 (95% CI 0.74-0.75) in Scottish Care Information-diabetes database. Differences were only observed after random introduction of missing data in the most important predictor variable (i.e., age).& nbsp;Conclusion: Validity and robustness of median imputation was not dissimilar to more complex methods for handling missing values, provided that the most important predictor variables, such as age, are not missing. (C)& nbsp;2022 Elsevier Inc. All rights reserved.
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| 6. |
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| 7. |
- Fischer, Joern, et al.
(författare)
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Reframing the Food-Biodiversity Challenge
- 2017
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Ingår i: Trends in Ecology & Evolution. - : Elsevier BV. - 0169-5347 .- 1872-8383. ; 32:5, s. 335-345
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Forskningsöversikt (refereegranskat)abstract
- Given the serious limitations of production-oriented frameworks, we offer here a new conceptual framework for how to analyze the nexus of food security and biodiversity conservation. We introduce four archetypes of social-ecological system states corresponding to win-win (e.g., agroecology), win-lose (e.g., intensive agriculture), lose-win (e.g., fortress conservation), and lose-lose (e.g., degraded landscapes) outcomes for food security and biodiversity conservation. Each archetype is shaped by characteristic external drivers, exhibits characteristic internal social-ecological features, and has characteristic feedbacks that maintain it. This framework shifts the emphasis from focusing on production only to considering social-ecological dynamics, and enables comparison among landscapes. Moreover, examining drivers and feedbacks facilitates the analysis of possible transitions between system states (e.g., from a lose-lose outcome to a more preferred outcome).
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