Empirical use of causal inference methods to evaluate survival differences in a real-world registry vs those found in randomized clinical trials.

With heighted interest in causal inference based on real-world evidence, this empirical study sought to understand differences between the results of observational analyses and long-term randomized clinical trials. We hypothesized that patients deemed "eligible" for clinical trials would follow a different survival trajectory from those deemed "ineligible" and that this factor could partially explain results. In a large observational registry dataset, we estimated separate survival trajectories for hypothetically trial-eligible vs ineligible patients under both coronary artery bypass surgery (CABG) and percutaneous coronary intervention (PCI). We also explored whether results would depend on the causal inference method (inverse probability of treatment weighting vs optimal full propensity matching) or the approach to combine propensity scores from multiple imputations (the "across" vs "within" approaches). We found that, in this registry population of PCI/CABG multivessel patients, 32.5% would have been eligible for contemporaneous RCTs, suggesting that RCTs enroll selected populations. Additionally, we found treatment selection bias with different distributions of propensity scores between PCI and CABG patients. The different methodological approaches did not result in different conclusions. Overall, trial-eligible patients appeared to demonstrate at least marginally better survival than ineligible patients. Treatment comparisons by eligibility depended on disease severity. Among trial-eligible three-vessel diseased and trial-ineligible two-vessel diseased patients, CABG appeared to have at least a slight advantage with no treatment difference otherwise. In conclusion, our analyses suggest that RCTs enroll highly selected populations, and our findings are generally consistent with RCTs but less pronounced than major registry findings.

I-CARE randomized clinical trial integrating depression and acute coronary syndrome care in low-resource hospitals in China: Design and rationale.

Depression and acute coronary syndromes (ACS) are both common public health challenges. Patients with ACS often develop depression, which in turn adversely affects prognosis. Low-cost, sustainable, and effective service models that integrate depression care into the management of ACS patients to reduce depression and improve ACS outcomes are critically needed. Integrating Depression Care in ACS patients in Low Resource Hospitals in China (I-CARE) is a multicenter, randomized controlled trial to evaluate the efficacy of an 11-month integrated care (IC) intervention compared to usual care (UC) in management of ACS patients. Four thousand inpatients will be recruited and then randomized in a 1:1 ratio to an IC intervention consisting of nurse-led risk factor management, group-based counseling supplemented by individual problem-solving therapy, and antidepressant medications as needed, or to UC. The primary outcomes are depression symptoms measured by the Patient Health Questionnaire-9 at 6 and 12 months. Secondary endpoints include anxiety measured by the Generalized Anxiety Disorder-7; quality of life measured by the EQ-5D at 6 and 12 months; and major adverse events including the combined end point of all-cause death, suicide attempts, nonfatal myocardial infarction, nonfatal stroke, and all-cause rehospitalization at yearly intervals for a median follow-up of 2 years. Analyses of the cost-effectiveness and cost-utility of IC also will be performed. I-CARE trial will be the largest study to test the effectiveness of an integrated care model on depression and cardiovascular outcomes among ACS patients in resource-limited clinical settings.

An evaluation of constrained randomization for the design and analysis of group-randomized trials with binary outcomes.

Group-randomized trials are randomized studies that allocate intact groups of individuals to different comparison arms. A frequent practical limitation to adopting such research designs is that only a limited number of groups may be available, and therefore, simple randomization is unable to adequately balance multiple group-level covariates between arms. Therefore, covariate-based constrained randomization was proposed as an allocation technique to achieve balance. Constrained randomization involves generating a large number of possible allocation schemes, calculating a balance score that assesses covariate imbalance, limiting the randomization space to a prespecified percentage of candidate allocations, and randomly selecting one scheme to implement. When the outcome is binary, a number of statistical issues arise regarding the potential advantages of such designs in making inference. In particular, properties found for continuous outcomes may not directly apply, and additional variations on statistical tests are available. Motivated by two recent trials, we conduct a series of Monte Carlo simulations to evaluate the statistical properties of model-based and randomization-based tests under both simple and constrained randomization designs, with varying degrees of analysis-based covariate adjustment. Our results indicate that constrained randomization improves the power of the linearization F-test, the KC-corrected GEE t-test (Kauermann and Carroll, 2001, Journal of the American Statistical Association 96, 1387-1396), and two permutation tests when the prognostic group-level variables are controlled for in the analysis and the size of randomization space is reasonably small. We also demonstrate that constrained randomization reduces power loss from redundant analysis-based adjustment for non-prognostic covariates. Design considerations such as the choice of the balance metric and the size of randomization space are discussed.

Statistical lessons learned for designing cluster randomized pragmatic clinical trials from the NIH Health Care Systems Collaboratory Biostatistics and Design Core.

BACKGROUND/AIMS: Pragmatic clinical trials embedded within health care systems provide an important opportunity to evaluate new interventions and treatments. Networks have recently been developed to support practical and efficient studies. Pragmatic trials will lead to improvements in how we deliver health care and promise to more rapidly translate research findings into practice. METHODS: The National Institutes of Health (NIH) Health Care Systems Collaboratory was formed to conduct pragmatic clinical trials and to cultivate collaboration across research areas and disciplines to develop best practices for future studies. Through a two-stage grant process including a pilot phase (UH2) and a main trial phase (UH3), investigators across the Collaboratory had the opportunity to work together to improve all aspects of these trials before they were launched and to address new issues that arose during implementation. Seven Cores were created to address the various considerations, including Electronic Health Records; Phenotypes, Data Standards, and Data Quality; Biostatistics and Design Core; Patient-Reported Outcomes; Health Care Systems Interactions; Regulatory/Ethics; and Stakeholder Engagement. The goal of this article is to summarize the Biostatistics and Design Core's lessons learned during the initial pilot phase with seven pragmatic clinical trials conducted between 2012 and 2014. RESULTS: Methodological issues arose from the five cluster-randomized trials, also called group-randomized trials, including consideration of crossover and stepped wedge designs. We outlined general themes and challenges and proposed solutions from the pilot phase including topics such as study design, unit of randomization, sample size, and statistical analysis. Our findings are applicable to other pragmatic clinical trials conducted within health care systems. CONCLUSION: Pragmatic clinical trials using the UH2/UH3 funding mechanism provide an opportunity to ensure that all relevant design issues have been fully considered in order to reliably and efficiently evaluate new interventions and treatments. The integrity and generalizability of trial results can only be ensured if rigorous designs and appropriate analysis choices are an essential part of their research protocols.

An evaluation of constrained randomization for the design and analysis of group-randomized trials.

In group-randomized trials, a frequent practical limitation to adopting rigorous research designs is that only a small number of groups may be available, and therefore, simple randomization cannot be relied upon to balance key group-level prognostic factors across the comparison arms. Constrained randomization is an allocation technique proposed for ensuring balance and can be used together with a permutation test for randomization-based inference. However, several statistical issues have not been thoroughly studied when constrained randomization is considered. Therefore, we used simulations to evaluate key issues including the following: the impact of the choice of the candidate set size and the balance metric used to guide randomization; the choice of adjusted versus unadjusted analysis; and the use of model-based versus randomization-based tests. We conducted a simulation study to compare the type I error and power of the F-test and the permutation test in the presence of group-level potential confounders. Our results indicate that the adjusted F-test and the permutation test perform similarly and slightly better for constrained randomization relative to simple randomization in terms of power, and the candidate set size does not substantially affect their power. Under constrained randomization, however, the unadjusted F-test is conservative, while the unadjusted permutation test carries the desired type I error rate as long as the candidate set size is not too small; the unadjusted permutation test is consistently more powerful than the unadjusted F-test and gains power as candidate set size changes. Finally, we caution against the inappropriate specification of permutation distribution under constrained randomization. An ongoing group-randomized trial is used as an illustrative example for the constrained randomization design.

Population impact of a high cardiovascular risk management program delivered by village doctors in rural China: design and rationale of a large, cluster-randomized controlled trial.

BACKGROUND: The high-risk strategy has been proven effective in preventing cardiovascular disease; however, the population benefits from these interventions remain unknown. This study aims to assess, at the population level, the effects of an evidence-based high cardiovascular risk management program delivered by village doctors in rural China. METHODS: The study will employ a cluster-randomized controlled trial in which a total of 120 villages in five northern provinces of China, will be assigned to either intervention (60 villages) or control (60 villages). Village doctors in intervention villages will be trained to implement a simple evidence-based management program designed to identify, treat and follow-up as many as possible individuals at high-risk of cardiovascular disease in the village. The intervention will also include performance feedback as well as a performance-based incentive payment scheme and will last for 2 years. We will draw two different (independent) random samples, before and after the intervention, 20 men aged≥50 years and 20 women aged≥60 years from each village in each sample and a total of 9,600 participants from 2 samples to measure the study outcomes at the population level. The primary outcome will be the pre-post difference in mean systolic blood pressure, analyzed with a generalized estimating equations extension of linear regression model to account for cluster effect. Secondary outcomes will include monthly clinic visits, provision of lifestyle advice, use of antihypertensive medications and use of aspirin. Process and economic evaluations will also be conducted. DISCUSSION: This trial will be the first implementation trial in the world to evaluate the population impact of the high-risk strategy in prevention and control of cardiovascular disease. The results are expected to provide important information (effectiveness, cost-effectiveness, feasibility and acceptability) to guide policy making for rural China as well as other resource-limited countries. TRIAL REGISTRATION: The trial is registered at ClinicalTrials.gov (NCT01259700). Date of initial registration is December 13, 2010.

Composite outcomes in coronary bypass surgery versus percutaneous intervention.

BACKGROUND: Recent observational studies show that patients with multivessel coronary disease have a long-term survival advantage with coronary artery bypass grafting (CABG) compared with percutaneous coronary intervention (PCI). Important nonfatal outcomes may also affect optimal treatment recommendation. METHODS: CABG was compared with percutaneous catheter intervention by using a composite of death, myocardial infarction (MI), or stroke. Medicare patients undergoing revascularization for stable multivessel coronary disease from 2004 through 2008 were identified in national registries. Short-term clinical information from the registries was linked to Medicare data to obtain long-term follow-up out to 4 years from the time of the procedure. Propensity scoring with inverse probability weighting was used to adjust for baseline risk factors. RESULTS: There were 86,244 CABG and 103,549 PCI patients. The mean age was 74 years, with a median 2.67 years of follow-up. At 4 years, the propensity-adjusted adjusted cumulative incidence of MI was 3.2% in CABG compared with 6.6% in PCI (risk ratio, 0.49; 95% confidence interval, 0.45 to 0.53). At 4 years, the cumulative incidence of stroke was 4.5% in CABG compared with 3.1% in PCI patients (risk ratio, 1.43; 95% confidence interval, 1.31 to 1.54). This difference was primarily due to the higher 30-day stroke rate for CABG (1.55% vs 0.37%). For the composite of death, MI, or stroke, the 4-year adjusted cumulative incidence was 21.6% for CABG and 26.7% for PCI (risk ratio, 0.81; 95% confidence interval, 0.78 to 0.83). CONCLUSIONS: The 4-year composite event rate of death, MI, and stroke favored CABG, whereas the risk of stroke alone favored PCI.

Angiographic validation of the American College of Cardiology Foundation-the Society of Thoracic Surgeons Collaboration on the Comparative Effectiveness of Revascularization Strategies study.

BACKGROUND: The goal of this study was to compare angiographic interpretation of coronary arteriograms by sites in community practice versus those made by a centralized angiographic core laboratory. METHODS AND RESULTS: The study population consisted of 2013 American College of Cardiology-National Cardiovascular Data Registry (ACC-NCDR) records with 2- and 3- vessel coronary disease from 54 sites in 2004 to 2007. The primary analysis compared Registry (NCDR)-defined 2- and 3-vessel disease versus those from an angiographic core laboratory analysis. Vessel-level kappa coefficients suggested moderate agreement between NCDR and core laboratory analysis, ranging from kappa=0.39 (95% confidence intervals, 0.32-0.45) for the left anterior descending artery to kappa=0.59 (95% confidence intervals, 0.55-0.64) for the right coronary artery. Overall, 6.3% (n=127 out of 2013) of those patients identified with multivessel disease at NCDR sites had had 0- or 1-vessel disease by core laboratory reading. There was no directional bias with regard to overcall, that is, 12.3% of cases read as 3-vessel disease by the sites were read as <3-vessel disease by the core laboratory, and 13.9% of core laboratory 3-vessel cases were read as <3-vessel by the sites. For a subset of patients with left main coronary disease, registry overcall was not linked to increased rates of mortality or myocardial infarction. CONCLUSIONS: There was only modest agreement between angiographic readings in clinical practice and those from an independent core laboratory. Further study will be needed because the implications for patient management are uncertain.

Prediction of long-term mortality after percutaneous coronary intervention in older adults: results from the National Cardiovascular Data Registry.

BACKGROUND: The purpose of this study was to develop a long-term model to predict mortality after percutaneous coronary intervention in both patients with ST-segment elevation myocardial infarction and those with more stable coronary disease. METHODS AND RESULTS: The American College of Cardiology Foundation CathPCI Registry data were linked to the Centers for Medicare and Medicaid Services 100% denominator file by probabilistic matching. Preprocedure demographic and clinical variables from the CathPCI Registry were used to predict the probability of death over 3 years as recorded in the Centers for Medicare and Medicaid Services database. Between 2004 and 2007, 343 466 patients (66%) of 518 195 patients aged ≥65 years undergoing first percutaneous coronary intervention in the CathPCI Registry were successfully linked to Centers for Medicare and Medicaid Services data. This study population was randomly divided into 60% derivation and 40% validation cohorts. Median follow-up was 15 months, with mortality of 3.0% at 30 days and 8.7%, 13.4%, and 18.7% at 1, 2, and 3 years, respectively. Twenty-four characteristics related to demographics, clinical comorbidity, prior history of disease, and indices of disease severity and acuity were identified as being associated with mortality. The C indices in the validation cohorts for patients with and without ST-segment elevation myocardial infarction were 0.79 and 0.78. The model calibrated well across a wide range of predicted probabilities. CONCLUSIONS: On the basis of the large and nationally representative CathPCI Registry, we have developed a model that has excellent discrimination, calibration, and validation to predict survival up to 3 years after percutaneous coronary intervention.

Predictors of long-term survival after coronary artery bypass grafting surgery: results from the Society of Thoracic Surgeons Adult Cardiac Surgery Database (the ASCERT study).

BACKGROUND: Most survival prediction models for coronary artery bypass grafting surgery are limited to in-hospital or 30-day end points. We estimate a long-term survival model using data from the Society of Thoracic Surgeons Adult Cardiac Surgery Database and Centers for Medicare and Medicaid Services. METHODS AND RESULTS: The final study cohort included 348 341 isolated coronary artery bypass grafting patients aged ≥65 years, discharged between January 1, 2002, and December 31, 2007, from 917 Society of Thoracic Surgeons-participating hospitals, randomly divided into training (n=174 506) and validation (n=173 835) samples. Through linkage with Centers for Medicare and Medicaid Services claims data, we ascertained vital status from date of surgery through December 31, 2008 (1- to 6-year follow-up). Because the proportional hazards assumption was violated, we fit 4 Cox regression models conditional on being alive at the beginning of the following intervals: 0 to 30 days, 31 to 180 days, 181 days to 2 years, and >2 years. Kaplan-Meier-estimated mortality was 3.2% at 30 days, 6.4% at 180 days, 8.1% at 1 year, and 23.3% at 3 years of follow-up. Harrell's C statistic for predicting overall survival time was 0.732. Some risk factors (eg, emergency status, shock, reoperation) were strong predictors of short-term outcome but, for early survivors, became nonsignificant within 2 years. The adverse impact of some other risk factors (eg, dialysis-dependent renal failure, insulin-dependent diabetes mellitus) continued to increase. CONCLUSIONS: Using clinical registry data and longitudinal claims data, we developed a long-term survival prediction model for isolated coronary artery bypass grafting. This provides valuable information for shared decision making, comparative effectiveness research, quality improvement, and provider profiling.

ACCF/AHA methodology for the development of quality measures for cardiovascular technology: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Performance Measures.

Consistent with the growing national focus on healthcare quality, the American College of Cardiology Foundation (ACCF) and the American Heart Association (AHA) have taken a leadership role over the past decade in developing measures of the quality of cardiovascular care by convening a joint ACCF/AHA Task Force on Performance Measures. The Task Force is charged with identifying the clinical topics appropriate for the development of performance measures and with assembling writing committees composed of clinical and methodological experts in collaboration with appropriate subspecialty societies. The Task Force has also created methodology documents that offer guidance in the development of process, outcome, composite, and efficiency measures. Cardiovascular performance measures using existing ACCF/AHA methodology are based on Class I or Class III guidelines recommendations, usually with Level A evidence. These performance measures, based on evidence-based ACCF/AHA guidelines, remain the most rigorous quality measures for both internal quality improvement and public reporting. However, many of the tools for diagnosis and treatment of cardiovascular disease involve advanced technologies, such as cardiac imaging, for which there are often no underlying guideline documents. Because these technologies affect the quality of cardiovascular care and also have the potential to contribute to cardiovascular health expenditures, there is a need for more critical assessment of the use of technology, including the development of quality and performance measures in areas in which guideline recommendations are absent. The evaluation of quality in the use of cardiovascular technologies requires consideration of multiple parameters that differ from other healthcare processes. The present document describes methodology for development of 2 new classes of quality measures in these situations, appropriate use measures and structure/safety measures. Appropriate use measures are based on specific indications, processes, or parameters of care for which high level of evidence data and Class I or Class III guideline recommendations may be lacking but are addressed in ACCF appropriate use criteria documents. Structure/safety measures represent measures developed to address structural aspects of the use of healthcare technology (e.g., laboratory accreditation, personnel training, and credentialing) or quality issues related to patient safety when there are neither guidelines recommendations nor appropriate use criteria. Although the strength of evidence for appropriate use measures and structure/safety measures may not be as strong as that for formal performance measures, they are quality measures that are otherwise rigorously developed, reviewed, tested, and approved in the same manner as ACCF/AHA performance measures. The ultimate goal of the present document is to provide direction in defining and measuring the appropriate use-avoiding not only underuse but also overuse and misuse-and proper application of cardiovascular technology and to describe how such appropriate use measures and structure/safety measures might be developed for the purposes of quality improvement and public reporting. It is anticipated that this effort will help focus the national dialogue on the use of cardiovascular technology and away from the current concerns about volume and cost alone to a more holistic emphasis on value.

ACCF/AHA methodology for the development of quality measures for cardiovascular technology: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Performance Measures.

Consistent with the growing national focus on healthcare quality, the American College of Cardiology Foundation (ACCF) and the American Heart Association (AHA) have taken a leadership role over the past decade in developing measures of the quality of cardiovascular care by convening a joint ACCF/AHA Task Force on Performance Measures. The Task Force is charged with identifying the clinical topics appropriate for the development of performance measures and with assembling writing committees composed of clinical and methodological experts in collaboration with appropriate subspecialty societies. The Task Force has also created methodology documents that offer guidance in the development of process, outcome, composite, and efficiency measures. Cardiovascular performance measures using existing ACCF/AHA methodology are based on Class I or Class III guidelines recommendations, usually with Level A evidence. These performance measures, based on evidence-based ACCF/AHA guidelines, remain the most rigorous quality measures for both internal quality improvement and public reporting. However, many of the tools for diagnosis and treatment of cardiovascular disease involve advanced technologies, such as cardiac imaging, for which there are often no underlying guideline documents. Because these technologies affect the quality of cardiovascular care and also have the potential to contribute to cardiovascular health expenditures, there is a need for more critical assessment of the use of technology, including the development of quality and performance measures in areas in which guideline recommendations are absent. The evaluation of quality in the use of cardiovascular technologies requires consideration of multiple parameters that differ from other healthcare processes. The present document describes methodology for development of 2 new classes of quality measures in these situations, appropriate use measures and structure/safety measures. Appropriate use measures are based on specific indications, processes, or parameters of care for which high level of evidence data and Class I or Class III guideline recommendations may be lacking but are addressed in ACCF appropriate use criteria documents. Structure/safety measures represent measures developed to address structural aspects of the use of healthcare technology (e.g., laboratory accreditation, personnel training, and credentialing) or quality issues related to patient safety when there are neither guidelines recommendations nor appropriate use criteria. Although the strength of evidence for appropriate use measures and structure/safety measures may not be as strong as that for formal performance measures, they are quality measures that are otherwise rigorously developed, reviewed, tested, and approved in the same manner as ACCF/AHA performance measures. The ultimate goal of the present document is to provide direction in defining and measuring the appropriate use-avoiding not only underuse but also overuse and misuse-and proper application of cardiovascular technology and to describe how such appropriate use measures and structure/safety measures might be developed for the purposes of quality improvement and public reporting. It is anticipated that this effort will help focus the national dialogue on the use of cardiovascular technology and away from the current concerns about volume and cost alone to a more holistic emphasis on value.

Secondary prevention after coronary artery bypass graft surgery: findings of a national randomized controlled trial and sustained society-led incorporation into practice.

BACKGROUND: Despite evidence supporting the use of aspirin, ß-blockers, angiotensin-converting enzyme inhibitors, and lipid-lowering therapies in eligible patients, adoption of these secondary prevention measures after coronary artery bypass grafting has been inconsistent. We sought to rigorously test on a national scale whether low-intensity continuous quality improvement interventions can be used to speed secondary prevention adherence after coronary artery bypass grafting. METHODS AND RESULTS: A total of 458 hospitals participating in the Society of Thoracic Surgeons National Cardiac Database and treating 361 328 patients undergoing isolated coronary artery bypass grafting were randomized to either a control or an intervention group. The intervention group received continuous quality improvement materials designed to influence the prescription of the secondary prevention medications at discharge. The primary outcome measure was discharge prescription rates of the targeted secondary prevention medications at intervention versus control sites, assessed by measuring preintervention and postintervention site differences. Prerandomization treatment patterns and baseline data were similar in the control (n=234) and treatment (n=224) groups. Individual medication use and composite adherence increased over 24 months in both groups, with a markedly more rapid rate of adherence uptake among the intervention hospitals and a statistically significant therapy hazard ratio in the intervention versus control group for all 4 secondary prevention medications. CONCLUSIONS: Provider-led, low-intensity continuous quality improvement efforts can improve the adoption of care processes into national practice within the context of a medical specialty society infrastructure. The findings of the present trial have led to the incorporation of study outcome metrics into a medical society rating system for ongoing quality improvement.

Delay from symptom onset to hospital presentation for patients with non-ST-segment elevation myocardial infarction.

BACKGROUND: Secular trends and factors associated with delay time from symptom onset to hospital presentation are known for patients with ST-segment elevation myocardial infarction (STEMI) but are less well-described for non-STEMI. METHODS: We studied 104 622 patients with non-STEMI enrolled at 568 hospitals participating in the Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes With Early Implementation of the American College of Cardiology/American Heart Association Guidelines (CRUSADE) National Quality Improvement Initiative from January 1, 2001, to December 31, 2006. We examined secular trends and factors associated with delay time and the association of delay time with in-hospital mortality. RESULTS: Median delay time from symptom onset to hospital presentation was 2.6 hours (interquartile range, 1.3-6.0) and has been stable from 2001 to 2006 (P value for trend, .16). After multivariable adjustment, factors associated with longer delay time included older age, female sex, nonwhite race, diabetes, and current smoking. In addition, compared with those who presented during weekday daytime (>8 am to 4 pm), patients who presented during weekday and weekend nights (>12 am to 8 am) had a 24.7% and 24.3% shorter delay time, respectively (P < .001). After multivariable adjustment, the odds ratio of in-hospital mortality for patients with delay times of 0 to 1 hour or less, more than 1 to 2 hours, more than 2 to 3 hours, and more than 3 to 6 hours compared with the reference group (delay time >6 hours) were 1.19 (95% confidence interval [CI], 1.08-1.30), 0.91 (95% CI, 0.83-1.00), 0.77 (95% CI, 0.69-0.88), and 0.90 (95% CI, 0.81-1.00), respectively. CONCLUSIONS: Long delay times are common and have not changed over time for patients with non-STEMI. Because patients cannot differentiate whether symptoms are due to STEMI or non-STEMI, early presentation is desirable in both instances.

Reclassification of cardiovascular risk using integrated clinical and molecular biosignatures: Design of and rationale for the Measurement to Understand the Reclassification of Disease of Cabarrus and Kannapolis (MURDOCK) Horizon 1 Cardiovascular Disease Study.

BACKGROUND: Clinical predictive models leave gaps in our ability to stratify cardiovascular risk. High-throughput molecular profiling promises to improve risk classification. METHODS: Horizon 1 of the Measurement to Understand the Reclassification of Disease of Cabarrus and Kannapolis (MURDOCK) Study was conceived to apply emerging molecular techniques to existing data sets to characterize mechanistic diversity underlying complex human diseases, response to therapy, and prognosis. No previous studies have applied multiple, complementary molecular techniques in combination with well-developed clinical risk models to refine cardiovascular risk prediction. The MURDOCK Cardiovascular Disease Study will assess molecular profiles integrated with clinical data in "clinomic" profiles for cardiovascular risk classification. CONCLUSION: Herein, we describe the design of and rationale for the MURDOCK Cardiovascular Disease Study.