Chronic Disease Data And Analysis: Current State Of the Field

Chronic disease usually spans years of a person’s lifetime and includes a disease free period, a preclinical, or latent period, where there are few overt signs of disease, a clinical period where the disease manifests and is eventually diagnosed, and a follow-up period where the disease might progress steadily or remain stable. It is often of interest to investigate the relationship between risk factors measured at a point in time (usually during the disease free or preclinical period), and the development of disease at some future point (e.g., 10 years later). We outline some popular designs for the identification of subjects and discuss issues in measurement of risk factors for analysis of chronic disease. We discuss some of the complexities in these analyses, including the time dependent nature of the risk factors and missing data issues. We then describe some popular statistical modeling techniques and outline the situations in which each is appropriate. We conclude with some speculation toward future development in the area of chronic disease data and analysis

Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies

Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after ‘recalibration’, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. Methods & Results: Using individual-participant data on 360737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at ‘high’ 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE overpredicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29–39% of individuals aged \u3e_40years as high risk. By contrast, recalibration reduced this proportion to 22–24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44–51 such individuals using original algorithms, in contrast to 37–39 individuals with recalibrated algorithms. Conclusions: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need

Association of Multiorgan Computed Tomographic Phenomap With Adverse Cardiovascular Health Outcomes: The Framingham Heart Study

Importance: Increased ability to quantify anatomical phenotypes across multiple organs provides the opportunity to assess their cumulative ability to identify individuals at greatest susceptibility for adverse outcomes. Objective: To apply unsupervised machine learning to define the distribution and prognostic importance of computed tomography-based multiorgan phenotypes associated with adverse health outcomes. Design, Setting, and Participants: This asymptomatic community-based cohort study included 2924 Framingham Heart Study participants between July 2002 and April 2005 undergoing computed tomographic imaging of the chest and abdomen. Participants are from the offspring and third-generation cohorts. Exposures: Eleven computed tomography-based measures of valvular/vascular calcification, adiposity, and muscle attenuation. Main Outcomes and Measures: All-cause mortality and cardiovascular disease (myocardial infarction, stroke, or cardiovascular death). Results: The median age of the participants was 50 years (interquartile range, 43-60 years), and 1422 (48.6%) were men. Principal component analysis identified 3 major anatomic axes: (1) global calcification (defined by aortic, thoracic, coronary, and valvular calcification); (2) adiposity (defined by pericardial, visceral, hepatic, and intrathoracic fat); and (3) muscle attenuation that explained 65.7% of the population variation. Principal components showed different evolution with age (continuous increase in global calcification, decrease in muscle attenuation, and U-shaped association with adiposity) but similar patterns in men and women. Using unsupervised clustering approaches in the offspring cohort (n = 1150), we identified a cohort (n = 232; 20.2%) with an unfavorable multiorgan phenotype across all 3 anatomic axes as compared with a favorable multiorgan phenotype. Membership in the unfavorable phenotypic cluster was associated with a greater prevalence of cardiovascular disease risk factors and with increased all-cause mortality (hazard ratio, 2.61; 95% CI, 1.74-3.92; P \u3c .001), independent of coronary artery calcium score, visceral adipose tissue, and 10-year global cardiovascular disease Framingham risk, and it provided improvement in metrics of discrimination and reclassification. Conclusions and Relevance: This proof-of-concept analysis demonstrates that unsupervised machine learning, in an asymptomatic community cohort, identifies an unfavorable multiorgan phenotype associated with adverse health outcomes, especially in elderly American adults. Future investigations in larger populations are required not only to validate the present results, but also to harness clinical, biochemical, imaging, and genetic markers to increase our understanding of healthy cardiovascular aging

Re-using Mini-Sentinel data following rapid assessments of potential safety signals via modular analytic programs

The U.S. Food and Drug Administration (FDA)\u27s Mini-Sentinel pilot has created a distributed data system with over 125 million lives and nearly 350 million person-years of observation time. The pilot allows the FDA to use modular analytic programs to assess suspected safety signals quickly. The FDA convened a committee to assess the implications of such rapid assessments on subsequent analyses of the same product-outcome pair using the same data. The committee offers several non-binding recommendations based on the strength of the knowledge of the suspected association before running the analysis: signal generation (an analysis with no prior), signal refinement (an analysis with a weak or moderate prior), and signal evaluation (an analysis with a strong prior). The committee believes that modular programs (MPs) are most useful for signal refinement. If MPs are used for analyses with no or weak/moderate priors, the committee members generally agree that the data may be re-used if certain conditions are met. When there is a strong prior, the committee recommends that a protocol-based assessment be used; Mini-Sentinel data may be analyzed by MPs and re-used only under very uncommon circumstances. The committee agrees that any subsequent assessment of the same product-outcome pair that follows an MP analysis should not be interpreted as independent confirmation of the association, such as would be established via replication of the same product-outcome association in two different populations. Instead, the follow-up assessment should be interpreted as an analysis that has reduced insofar as possible systematic errors that may have been present or residual in the original MP analysis. The committee also discussed how this general framework may apply to two completed rapid assessments of dabigatran and bleeding risk and of olmesartan and celiac disease risk

Early Rapid Decline in Kidney Function in Medically Managed Patients With Atherosclerotic Renal Artery Stenosis

Background Early rapid declines of kidney function may occur in patients with atherosclerotic renal artery stenosis with institution of medical therapy. The causes and consequences are not well understood. Methods and Results Patients enrolled in the medical therapy–only arm of the CORAL (Cardiovascular Outcomes With Renal Artery Lesions) study were assessed for a rapid decline (RD) in estimated glomerular filtration rate (eGFR), defined as a ≥30% decrease from baseline to either 3 months, 6 months, or both. In the medical therapy–only cohort, eGFR was available in 359 subjects at all time points, the subjects were followed for a median of 4.72 years, and 66 of 359 (18%) subjects experienced an early RD. Baseline log cystatin C (odds ratio, 1.78 [1.11–2.85]; P=0.02), age (odds ratio, 1.04 [1.00–1.07]; P\u3c0.05), and Chronic Kidney Disease Epidemiology Collaboration creatinine eGFR (odds ratio, 1.86 [1.15–3.0]; P=0.01) were associated with an early RD. Despite continued medical therapy only, the RD group had an improvement in eGFR at 1 year (6.9%; P=0.04). The RD and nondecline groups were not significantly different for clinical events and all‐cause mortality (P=0.78 and P=0.76, respectively). Similarly, renal replacement therapy occurred in 1 of 66 (1.5%) of the RD patients and in 6 of 294 (2%) of the nondecline patients. The regression to the mean of improvement in eGFR at 1 year in the RD group was estimated at 5.8±7.1%. Conclusions Early rapid declines in kidney function may occur in patients with renal artery stenosis when medical therapy is initiated, and their clinical outcomes are comparable to those without such a decline, when medical therapy only is continued

Stenting and Medical Therapy for Atherosclerotic Renal-Artery Stenosis

BACKGROUND Atherosclerotic renal-artery stenosis is a common problem in the elderly. Despite two randomized trials that did not show a benefit of renal-artery stenting with respect to kidney function, the usefulness of stenting for the prevention of major adverse renal and cardiovascular events is uncertain. METHODS We randomly assigned 947 participants who had atherosclerotic renal-artery stenosis and either systolic hypertension while taking two or more antihypertensive drugs or chronic kidney disease to medical therapy plus renal-artery stenting or medical therapy alone. Participants were followed for the occurrence of adverse cardiovascular and renal events (a composite end point of death from cardiovascular or renal causes, myocardial infarction, stroke, hospitalization for congestive heart failure, progressive renal insufficiency, or the need for renal-replacement therapy). RESULTS Over a median follow-up period of 43 months (interquartile range, 31 to 55), the rate of the primary composite end point did not differ significantly between participants who underwent stenting in addition to receiving medical therapy and those who received medical therapy alone (35.1% and 35.8%, respectively; hazard ratio with stenting, 0.94; 95% confidence interval [CI], 0.76 to 1.17; P = 0.58). There were also no significant differences between the treatment groups in the rates of the individual components of the primary end point or in all-cause mortality. During follow-up, there was a consistent modest difference in systolic blood pressure favoring the stent group (−2.3 mm Hg; 95% CI, −4.4 to −0.2; P = 0.03). CONCLUSIONS Renal-artery stenting did not confer a significant benefit with respect to the prevention of clinical events when added to comprehensive, multifactorial medical therapy in people with atherosclerotic renal-artery stenosis and hypertension or chronic kidney disease. (Funded by the National Heart, Lung and Blood Institute and others; ClinicalTrials.gov number, NCT00081731.