42 research outputs found
Validation of a model to investigate the effects of modifying cardiovascular disease (CVD) risk factors on the burden of CVD: the rotterdam ischemic heart disease and stroke computer simulation (RISC) model.
BACKGROUND: We developed a Monte Carlo Markov model designed to investigate the effects of modifying cardiovascular disease (CVD) risk factors on the burden of CVD. Internal, predictive, and external validity of the model have not yet been established. METHODS: The Rotterdam Ischemic Heart Disease and Stroke Computer Simulation (RISC) model was developed using data covering 5 years of follow-up from the Rotterdam Study. To prove 1) internal and 2) predictive validity, the incidences of coronary heart disease (CHD), stroke, CVD death, and non-CVD death simulated by the model over a 13-year period were compared with those recorded for 3,478 participants in the Rotterdam Study with at least 13 years of follow-up. 3) External validity was verified using 10 years of follow-up data from the European Prospective Investigation of Cancer (EPIC)-Norfolk study of 25,492 participants, for whom CVD and non-CVD mortality was compared. RESULTS: At year 5, the observed incidences (with simulated incidences in brackets) of CHD, stroke, and CVD and non-CVD mortality for the 3,478 Rotterdam Study participants were 5.30% (4.68%), 3.60% (3.23%), 4.70% (4.80%), and 7.50% (7.96%), respectively. At year 13, these percentages were 10.60% (10.91%), 9.90% (9.13%), 14.20% (15.12%), and 24.30% (23.42%). After recalibrating the model for the EPIC-Norfolk population, the 10-year observed (simulated) incidences of CVD and non-CVD mortality were 3.70% (4.95%) and 6.50% (6.29%). All observed incidences fell well within the 95% credibility intervals of the simulated incidences. CONCLUSIONS: We have confirmed the internal, predictive, and external validity of the RISC model. These findings provide a basis for analyzing the effects of modifying cardiovascular disease risk factors on the burden of CVD with the RISC model.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are
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Parent-Reported Clinical Utility of Pediatric Genomic Sequencing.
Background and objectivesGenomic sequencing (GS) is increasingly used for diagnostic evaluation, yet follow-up care is not well understood. We assessed clinicians' recommendations after GS, parent-reported follow-up, and actions parents initiated in response to learning their child's GS results.MethodsWe surveyed parents of children who received GS through the Clinical Sequencing Evidence Generating Research consortium ∼5 to 7 months after return of results. We compared the proportion of parents who reported discussing their child's result with a clinician, clinicians' recommendations, and parents' follow-up actions by GS result type using χ2 tests.ResultsA total of 1188 respondents completed survey measures on recommended medical actions (n = 1187) and/or parent-initiated actions (n = 913). Most parents who completed recommended medical actions questions (n = 833, 70.3%) reported having discussed their child's GS results with clinicians. Clinicians made recommendations to change current care for patients with positive GS results (n = 79, 39.1%) more frequently than for those with inconclusive (n = 31, 12.4%) or negative results (n = 44, 11.9%; P < .001). Many parents discussed (n = 152 completed, n = 135 planned) implications of GS results for future pregnancies with a clinician. Aside from clinical recommendations, 13.0% (n = 119) of parents initiated changes to their child's health or lifestyle.ConclusionsIn diverse pediatric clinical contexts, GS results can lead to recommendations for follow-up care, but they likely do not prompt large increases in the quantity of care received
Performance of Framingham cardiovascular disease (CVD) predictions in the Rotterdam Study taking into account competing risks and disentangling CVD into coronary heart disease (CHD) and stroke
AbstractBackgroundTo evaluate the performance of Framingham predictions of cardiovascular disease (CVD) risk corrected for the competing risk of non-CVD death, in an independent European cohort of older individuals and subsequently extend the predictions by disentangling CVD into coronary heart disease (CHD) and stroke separately.MethodsWe used the Rotterdam Study data, a prospective cohort study of individuals aged 55years and older (N=6004), to validate the Framingham predictions of CVD, defined as first occurrence of myocardial infarction, coronary death or stroke during 15years of follow-up, corrected for the competing risk of non-CVD death. We subsequently estimated the risks of CHD and stroke separately, and used the sum as a predictor for the total CVD risk. Calibration plots and c-statistics were used to evaluate the performance of the models.ResultsPerformance of the Framingham predictions was good in the low- to intermediate risk (≤30%, 15-year CVD risk) (17.5% observed vs. 16.6% expected) but poorer in the higher risk (>30%) categories (36.3% observed vs. 44.1% expected). The c-statistic increased from 0.66 to 0.69 after refitting. Separately estimating CHD and stroke revealed considerable heterogeneity with regard to the contribution of CHD and stroke to total CVD risk.ConclusionsFramingham CVD risk predictions perform well in the low- to intermediate risk categories in the Rotterdam Study. Disentangling CVD into CHD and stroke separately provides additional information about the individual contribution of CHD and stroke to total individual CVD risk
Cost-Effectiveness Frameworks for Comparing Genome and Exome Sequencing Versus Conventional Diagnostic Pathways: A Scoping Review and Recommended Methods
PURPOSE: Methodological challenges have limited economic evaluations of genome sequencing (GS) and exome sequencing (ES). Our objective was to develop conceptual frameworks for model-based cost-effectiveness analyses (CEAs) of diagnostic GS/ES.
METHODS: We conducted a scoping review of economic analyses to develop and iterate with experts a set of conceptual CEA frameworks for GS/ES for prenatal testing, early diagnosis in pediatrics, diagnosis of delayed-onset disorders in pediatrics, genetic testing in cancer, screening of newborns, and general population screening.
RESULTS: Reflecting on 57 studies meeting inclusion criteria, we recommend the following considerations for each clinical scenario. For prenatal testing, performing comparative analyses of costs of ES strategies and postpartum care, as well as genetic diagnoses and pregnancy outcomes. For early diagnosis in pediatrics, modeling quality-adjusted life years (QALYs) and costs over ≥20 years for rapid turnaround GS/ES. For hereditary cancer syndrome testing, modeling cumulative costs and QALYs for the individual tested and first/second/third-degree relatives. For tumor profiling, not restricting to treatment uptake or response and including QALYs and costs of downstream outcomes. For screening, modeling lifetime costs and QALYs and considering consequences of low penetrance and GS/ES reanalysis.
CONCLUSION: Our frameworks can guide the design of model-based CEAs and ultimately foster robust evidence for the economic value of GS/ES
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Sex differences in lifetime risk and first manifestation of cardiovascular disease: prospective population based cohort study
Objective: To evaluate differences in first manifestations of cardiovascular disease between men and women in a competing risks framework. Design: Prospective population based cohort study. Setting: People living in the community in Rotterdam, the Netherlands. Participants: 8419 participants (60.9% women) aged ≥55 and free from cardiovascular disease at baseline. Main outcome measures First diagnosis of coronary heart disease (myocardial infarction, revascularisation, and coronary death), cerebrovascular disease (stroke, transient ischaemic attack, and carotid revascularisation), heart failure, or other cardiovascular death; or death from non-cardiovascular causes. Data were used to calculate lifetime risks of cardiovascular disease and its first incident manifestations adjusted for competing non-cardiovascular death. Results: During follow-up of up to 20.1 years, 2888 participants developed cardiovascular disease (826 coronary heart disease, 1198 cerebrovascular disease, 762 heart failure, and 102 other cardiovascular death). At age 55, overall lifetime risks of cardiovascular disease were 67.1% (95% confidence interval 64.7% to 69.5%) for men and 66.4% (64.2% to 68.7%) for women. Lifetime risks of first incident manifestations of cardiovascular disease in men were 27.2% (24.1% to 30.3%) for coronary heart disease, 22.8% (20.4% to 25.1%) for cerebrovascular disease, 14.9% (13.3% to 16.6%) for heart failure, and 2.3% (1.6% to 2.9%) for other deaths from cardiovascular disease. For women the figures were 16.9% (13.5% to 20.4%), 29.8% (27.7% to 31.9%), 17.5% (15.9% to 19.2%), and 2.1% (1.6% to 2.7%), respectively. Differences in the number of events that developed over the lifespan in women compared with men (per 1000) were −7 for any cardiovascular disease, −102 for coronary heart disease, 70 for cerebrovascular disease, 26 for heart failure, and −1 for other cardiovascular death; all outcomes manifested at a higher age in women. Patterns were similar when analyses were restricted to hard atherosclerotic cardiovascular disease outcomes, but absolute risk differences between men and women were attenuated for both coronary heart disease and stroke. Conclusions: At age 55, though men and women have similar lifetime risks of cardiovascular disease, there are considerable differences in the first manifestation. Men are more likely to develop coronary heart disease as a first event, while women are more likely to have cerebrovascular disease or heart failure as their first event, although these manifestations appear most often at older ages
Separate prediction of intracerebral hemorrhage and ischemic stroke
OBJECTIVES: To develop and validate 10-year cumulative incidence functions of intracerebral hemorrhage (ICH) and ischemic stroke (IS).
METHODS: We used data on 27,493 participants from 3 population-based cohort studies: the Atherosclerosis Risk in Communities Study, median age 54 years, 45% male, median follow-up 20.7 years; the Rotterdam Study, median age 68 years, 38% male, median follow-up 14.3 years; and the Cardiovascular Health Study, median age 71 years, 41% male, median follow-up 12.8 years. Among these participants, 325 ICH events, 2,559 IS events, and 9,909 nonstroke deaths occurred. We developed 10-year cumulative incidence functions for ICH and IS using stratified Cox regression and competing risks analysis. Basic models including only established nonlaboratory risk factors were extended with diastolic blood pressure, total cholesterol/high-density lipoprotein cholesterol ratio, body mass index, waist-to-hip ratio, and glomerular filtration rate. The cumulative incidence functions' performances were cross-validated in each cohort separately by Harrell C-statistic and calibration plots.
RESULTS: High total cholesterol/high-density lipoprotein cholesterol ratio decreased the ICH rates but increased IS rates (p for difference across stroke types <0.001). For both the ICH and IS models, C statistics increased more by model extension in the Atherosclerosis Risk in Communities and Cardiovascular Health Study cohorts. Improvements in C statistics were reproduced by cross-validation. Models were well calibrated in all cohorts. Correlations between 10-year ICH and IS risks were moderate in each cohort.
CONCLUSIONS: We developed and cross-validated cumulative incidence functions for separate prediction of 10-year ICH and IS risk. These functions can be useful to further specify an individual's stroke risk
Establishing the value of genomics in medicine: the IGNITE Pragmatic Trials Network.
PURPOSE: A critical gap in the adoption of genomic medicine into medical practice is the need for the rigorous evaluation of the utility of genomic medicine interventions. METHODS: The Implementing Genomics in Practice Pragmatic Trials Network (IGNITE PTN) was formed in 2018 to measure the clinical utility and cost-effectiveness of genomic medicine interventions, to assess approaches for real-world application of genomic medicine in diverse clinical settings, and to produce generalizable knowledge on clinical trials using genomic interventions. Five clinical sites and a coordinating center evaluated trial proposals and developed working groups to enable their implementation. RESULTS: Two pragmatic clinical trials (PCTs) have been initiated, one evaluating genetic risk APOL1 variants in African Americans in the management of their hypertension, and the other to evaluate the use of pharmacogenetic testing for medications to manage acute and chronic pain as well as depression. CONCLUSION: IGNITE PTN is a network that carries out PCTs in genomic medicine; it is focused on diversity and inclusion of underrepresented minority trial participants; it uses electronic health records and clinical decision support to deliver the interventions. IGNITE PTN will develop the evidence to support (or oppose) the adoption of genomic medicine interventions by patients, providers, and payers
Long-term Predictions of Incident Coronary Artery Calcium to 85 Years of Age for Asymptomatic Individuals With and Without Type 2 Diabetes
OBJECTIVE: To examine the utility of repeated computed tomography (CT) coronary artery calcium (CAC) testing, we assessed risks of detectable CAC and its cardiovascular consequences in individuals with and without type 2 diabetes ages 45-85 years. RESEARCH DESIGN AND METHODS: We included 5,836 individuals (618 with type 2 diabetes, 2,972 without baseline CAC) from the Multi-Ethnic Study of Atherosclerosis. With logistic and Cox regression we evaluated the impact of type 2 diabetes, diabetes treatment duration, and other predictors on prevalent and incident CAC. We used time-dependent Cox modeling of follow-up data (median 15.9 years) for two repeat CT exams and cardiovascular events to assess the association of CAC at follow-up CT with cardiovascular events. RESULTS: For 45 year olds with type 2 diabetes, the likelihood of CAC at baseline was 23% vs. 17% for those without. Median age at incident CAC was 52.2 vs. 62.3 years for those with and without diabetes, respectively. Each 5 years of diabetes treatment increased the odds and hazard rate of CAC by 19% (95% CI 8-33) and 22% (95% CI 6-41). Male sex, White ethnicity/race, hypertension, hypercholesterolemia, obesity, and low serum creatinine also increased CAC. CAC at follow-up CT independently increased coronary heart disease rates. CONCLUSIONS: We estimated cumulative CAC incidence to age 85 years. Patients with type 2 diabetes develop CAC at a younger age than those without diabetes. Because incident CAC is associated with increased coronary heart disease risk, the value of periodic CAC-based risk assessment in type 2 diabetes should be evaluated
Do different methods of modeling statin treatment effectiveness influence the optimal decision?
Purpose. Modeling studies that evaluate statin treatment for the prevention of cardiovascular disease (CVD) use different methods to model the effect of statins. The aim of this study was to evaluate the impact of using different modeling methods on the optimal decision found in such studies. Methods. We used a previously developed and validated Monte Carlo-Markov model based on the Rotterdam study (RISC model). The RISC model simulates coronary heart disease (CHD), stroke, cardiovascular death, and death due to other causes. Transition probabilities were based on 5-year risks predicted by Cox regression equations, including (among others) total and high-density lipoprotein (HDL) cholesterol as covariates. In a cost-effectiveness analysis of implementing the ATP-III guidelines, we evaluated the impact of using 3 different modeling methods of statin effectiveness: 1) through lipid level modification: statins lower total cholesterol and increase HDL cholesterol, which through the covariates in the Cox regression equations leads to a lower incidence of CHD and stroke events; 2) fixed risk reduction of CVD events: statins decrease the odds of CHD and stroke with an associated odds ratio that is assumed to be the same for each individual; 3) risk reduction of CVD events proportional to individual change in low-density lipoprotein (LDL) cholesterol: the relative risk reduction with statin therapy on the incidence of CHD and stroke was assumed to be proportional to the absolute reduction in LDL cholesterol levels for each individual. The probability that the ATP-III strategy was cost-effective, compared to usual care as observed in the Rotterdam study, was calculated for each of the 3 modeling methods for varying willingness-to-pay thresholds. Results. Incremental cost-effectiveness ratios for the ATP-III strategy compared with the reference strategy were €56,642/quality-adjusted life year (QALY), €21,369/QALY, and €22,131/QALY for modeling methods 1, 2, and 3, respectively. At a willingness-to-pay threshold of €50,000/QALY, the probability that the ATP-III strategy was cost-effective was about 40% for modeling method 1 and more than 90% for both met