This editorial refers to ‘ Applying novel methods to assess clinical outcomes: insights from the TRILOGY ACS trial’[†][1], by J. A. Bakal et al. , on page 385 Though a seemingly simple notion, defining a clear research question or hypothesis at the conception of a clinical study can be a daunting task for investigators. Through the TRILOGY ACS study,1 Bakal and colleagues2 illustrate that subtle changes in the primary outcome definition for a clinical trial may result in substantial changes in the analytical methods, altering the overall interpretation of the study's result. Perhaps as an unintended consequence, their article also emphasizes a pitfall of post-hoc analyses. This editorial is intended to provide some insight into the statistical considerations in their article. In doing so, it aggregates their ideas to provide recommendations for appropriate analytical techniques driven by specific research questions. Most disease progressions are associated with the realization of multiple complications. Cardiovascular disease, for example, may have elevated blood pressure, atherosclerosis, altered perfusion, ischaemia, changes in activities of daily living, etc. From a clinical perspective, a myocardial infarction resulting in death may be more important than reduced cardiopulmonary function that only limits a patient's activities of daily living. That said, these extreme examples are intrinsically linked in a common disease process and represent different aspects of disease progression. These inter-relationships, when simultaneously modelled, often introduce the need for more sophisticated statistical analyses. These analyses can sometimes obfuscate … [1]: #fn-2