Key Takeaways:
- Endpoints drive cardiovascular research forward: From traditional mortality measures to composite outcomes and surrogate biomarkers, the selection and validation of cardiovascular endpoints are essential to capturing meaningful therapeutic effects and advancing regulatory decision-making.
- Real-world data transforms cardiovascular research: Electronic health records, claims databases, and disease registries provide longitudinal endpoint data across diverse populations, complementing traditional randomized trials and enabling post-approval surveillance and supporting potential label expansions.
- NashBio accelerates cardiovascular research: NashBio integrates structured and unstructured clinical data from a deeply-phenotyped longitudinal biorepository to provide critical cardiovascular endpoints that drive discovery.
Introduction
Cardiovascular clinical trials rely on a well-defined set of outcomes to determine whether a therapy (drug or device) improves patient health. While traditional endpoints like morbidity and mortality events remain a gold standard, the landscape of cardiovascular disease research is rapidly evolving. Advances in real-world data analytics, computational biology, and bioanalytical methods are expanding the ability to study disease mechanisms and predict clinical outcomes with increased precision. NashBio is positioned to accelerate cardiovascular research discovery through its deeply-phenotyped longitudinal biorepository and advanced analytical capabilities for extracting endpoints from unstructured text.
Endpoint Selection and Interpretation in Cardiovascular Clinical Trials
Rigorously defined endpoints in cardiovascular disease research encompass clinical outcomes, functional assessments, biomarkers, and patient-reported measures, each representing a distinct facet of disease manifestation and therapeutic response. The systematic selection, standardization, and validation of these endpoints are critical to ensuring the clarity, comparability, and interpretability of clinical trial results.1 Alongside mortality, major morbidity, and functional outcomes, endpoint frameworks may also incorporate composite measures and surrogate indicators to capture broader or earlier signals of clinical effect.
Composite endpoints combine multiple clinical events into a single outcome measure, often including cardiovascular death, myocardial infarction, stroke, and coronary revascularization.2 The major adverse cardiovascular event (MACE) composite has become a frequent primary endpoint in cardiovascular outcomes trials.2 While composite endpoints enhance statistical efficiency by increasing event rates, they require careful construction to ensure that components are of similar clinical importance and occur with comparable frequency.3
Surrogate endpoints, like blood pressure and LDL cholesterol levels, serve as substitutes for clinical outcomes in cardiovascular trials, offering advantages like reduced sample sizes and shorter follow-up periods.4 However, their validity requires strong correlation with true clinical endpoints and demonstration that treatment effects on surrogates reliably predict effects on outcomes.4 The relationship between surrogates and clinical endpoints can be complex, as interventions may affect biomarkers without improving patient outcomes.4
The Importance of Choosing an Endpoint
Selecting appropriate endpoints is central to the success of cardiovascular clinical trials. Historical examples illustrate how endpoint selection can shape trial outcomes and regulatory decisions.
For example, in the SOLVD Prevention trial of enalapril, all-cause mortality effects were modest. However, the trial demonstrated important reductions in heart failure-related outcomes, including hospitalizations, which contributed to FDA approval.5
Similarly, early carvedilol trials focused on functional outcomes such as exercise tolerance, which did not reach statistical significance in several trials. Subsequent pooled analyses, however, revealed a significant reduction in mortality and heart failure-related outcomes. These findings prompted regulatory discussion about how to interpret clinically meaningful effects that were not prespecified as primary endpoints and ultimately contributed to approval.6,7
These cases underscore the need for continued validation of cardiovascular endpoints and their association with meaningful clinical outcomes to improve trial design and reduce costly failures.
Real-World Data and Endpoints Beyond Clinical Trials
Laboratory measurements, diagnostic imaging results, and physiological assessments routinely collected during clinical care can provide valuable endpoint data that correlate with disease presence, progression, and severity.8 Electronic health records, administrative claims databases, and disease registries capture longitudinal patient information across diverse populations and real-world clinical settings, complementing the highly controlled environment of randomized clinical trials.8 There is increasing recognition of the potential for real-world data to generate real-world evidence that can inform regulatory decision-making, particularly for post-approval safety surveillance, label expansion studies, and in circumstances where randomized trials are impractical or unethical.9
Real-world data sources are particularly valuable for endpoint research because many clinically meaningful outcomes, such as hospitalizations, imaging findings, or functional classifications, are documented during routine care but not always systematically collected in traditional clinical trials.
Supporting Innovation in Cardiovascular Research with NashBio
NashBio offers a uniquely comprehensive resource for cardiovascular research through its deeply characterized patient population with longitudinal metabolite profiles and detailed clinical phenotypes captured in structured data. Its all-comers design, encompassing both diseased and healthy individuals, provides a significant advantage for population-based and comparative studies. Additionally, NashBio has developed advanced natural language processing methods to extract cardiovascular endpoints that appear only in unstructured clinical data, including New York Heart Association (NYHA) Functional Classification scores, echocardiogram and electrocardiogram findings, and other clinically relevant measures.
The combination of structured longitudinal data, comprehensive population coverage, and advanced data extraction capabilities positions NashBio as a valuable partner for cardiovascular clinical research. The team’s skilled experts can develop and refine scalable methods for extracting complex clinical variables, enabling researchers to conduct more comprehensive analyses that would otherwise be limited by data accessibility. By bridging the gap between structured and unstructured clinical information, NashBio enhances researchers’ ability to identify novel cardiovascular biomarkers and therapeutic targets, ultimately accelerating scientific discovery and improving research productivity.
References
- Hicks KA, Mahaffey KW, Mehran R, et al. 2017 Cardiovascular and Stroke Endpoint Definitions for Clinical Trials. J Am Coll Cardiol. 2018;71(9):1021-1034. doi:10.1016/j.jacc.2017.12.048
- Bosco E, Hsueh L, McConeghy KW, Gravenstein S, Saade E. Major adverse cardiovascular event definitions used in observational analysis of administrative databases: a systematic review. BMC Med Res Methodol. 2021;21(1):241. doi:10.1186/s12874-021-01440-5
- McCoy CE. Understanding the Use of Composite Endpoints in Clinical Trials. West J Emerg Med. 2018;19(4):631-634. doi:10.5811/westjem.2018.4.38383
- Bikdeli B, Punnanithinont N, Akram Y, et al. Two Decades of Cardiovascular Trials With Primary Surrogate Endpoints: 1990-2011. J Am Heart Assoc. 2017;6(3). doi:10.1161/JAHA.116.005285
- Yusuf S, Pitt B, Davis CE, Hood WBJ, Cohn JN. Effect of enalapril on mortality and the development of heart failure in asymptomatic patients with reduced left ventricular ejection fractions. N Engl J Med. 1992;327(10):685-691. doi:10.1056/NEJM199209033271003
- Packer M, Bristow MR, Cohn JN, et al. The effect of carvedilol on morbidity and mortality in patients with chronic heart failure. U.S. Carvedilol Heart Failure Study Group. N Engl J Med. 1996;334(21):1349-1355. doi:10.1056/NEJM199605233342101
- Fisher LD. Carvedilol and the Food and Drug Administration (FDA) approval process: the FDA paradigm and reflections on hypothesis testing. Control Clin Trials. 1999;20(1):16-39. doi:10.1016/s0197-2456(98)00054-3
- Blonde L, Khunti K, Harris SB, Meizinger C, Skolnik NS. Interpretation and Impact of Real-World Clinical Data for the Practicing Clinician. Adv Ther. 2018;35(11):1763-1774. doi:10.1007/s12325-018-0805-y
- U.S. Food & Drug Administration. Framework for FDA’s Real-World Evidence Program. December 2018. Accessed February 23, 2026. https://www.fda.gov/media/120060/download
