With the COVID-19 pandemic, the investigative clinical studies have been launched in the spotlight. The discussions, experts have about methodology, usually kept in the narrow circle of insiders, generated a lot of interest among politicians and general public. Some decisions of banning treatments were based on a study with a so poor methodology and using so suspicious data that later the authors withdrew their article.
Of course, fraudulent studies always existed but they were quickly forgotten and they rarely generated interest outside the medical field. Driven by these public debates, journalists seized the topic and asked questions to the expert. Thus, recently, a French news magazine published an irreverent article on the clinical studies: “comment des études cliniques peuvent être faussées”. (how clinical studies can be flawed). Criticism is easy, and it is always possible to find severe examples. But this criticism reveals after all, if the evidence-based medicine, mandatory to prove that a drug, a medical device or a treatment brings ratio benefits/risk is favorable to the patient, it failed to perfectly describe what is going to happen in a large patient population. In particular, because in order to limit the number of parameters to investigate in the data analysis or to optimize the outcome of the clinical study, the population is carefully selected by chosen the inclusion or exclusion criteria. Thus, a significative part of the patient population that could benefit from the treatment is excluded. By reducing the targeted population, some biases or limitations are introduced limiting the scope of the results. Thus, these latter are not systematically transposable to the whole population. To reduce this risk, statisticians are gathering several studies with different protocols to perform a meta-analysis, with the goal of eliminating the biases linked to one study. But this is assuming that several studies are already available and that all have been conducted with a methodology robust enough to allow an analysis.
Experts know these limitations. Therefore, after the concept of Evidence Based Medicine, the complementary one of Real-World Data appeared. The analysis is not only restricted to controlled randomized clinical studies but it is taking into account other available data such as observational or retrospective studies, register and even surveys among patients. Often discredited, these studies are bringing a complementary point of view on the product in a more diverse and large population. They are contributing to prove clinical efficacy and safety based on experience. This concept of Real-World data is generating more and more interest among Health Authorities such as the FDA (see Real World Evidence Program).
These two approaches of clinical investigation should not be opposed as it is sometime done by their advocates, they are really complementary. Indeed, an effective use of these studies allows to collect important information on marketed products. Thus, effects that were not observed in controlled randomized studies could be detected in observational studies (for example, see the study of Cooper intitled: « Stenting and Medical Therapy for Atherosclerotic Renal-Artery Stenosis »).
In parallel, the new European Regulation on Medical Devices (MDR 2017/745) requires to strengthen the surveillance after commercialization (article 83 and following).
These studies are not only an excellent tool to fulfill the regulatory requirements but they also allow to better understand your product, to improve it and to promote it.
Calicéos is at your disposal to support you in this step by helping you to define your strategy and implement the studies: contact@caliceos.com