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- 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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| 2. |
- 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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| 3. |
- 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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