Fanaroff, Alexander CAlexander CFanaroffCaliff, Robert MRobert MCaliffHarrington, Robert ARobert AHarringtonGranger, Christopher BChristopher BGrangerMcMurray, John J VJohn J VMcMurrayPatel, Manesh RManesh RPatelBhatt, Deepak LDeepak LBhattWindecker, StephanStephanWindeckerHernandez, Adrian FAdrian FHernandezGibson, C MichaelC MichaelGibsonAlexander, John HJohn HAlexanderLopes, Renato DRenato DLopes2024-09-022024-09-022020-08-04https://boris-portal.unibe.ch/handle/20.500.12422/37622Concerns about the external validity of traditional randomized clinical trials (RCTs), together with the widespread availability of real-world data and advanced data analytic tools, have led to claims that common sense and clinical observation, rather than RCTs, should be the preferred method to generate evidence to support clinical decision-making. However, over the past 4 decades, results from well-done RCTs have repeatedly contradicted practices supported by common sense and clinical observation. Common sense and clinical observation fail for several reasons: incomplete understanding of pathophysiology, biases and unmeasured confounding in observational research, and failure to understand risks and benefits of treatments within complex systems. Concerns about traditional RCT models are legitimate, but randomization remains a critical tool to understand the causal relationship between treatments and outcomes. Instead, development and promulgation of tools to apply randomization to real-world data are needed to build the best evidence base in cardiovascular medicine.enobservational studies randomized controlled trials real-world data surrogate endpoints600 - Technology::610 - Medicine & healtharticle10.7892/boris.1474533273193610.1016/j.jacc.2020.05.069