Equipoise and the technology curve
نویسندگان
چکیده
520 Freely available online open Access bJr bJr elimination of bias is a core element of high quality clinical trials. 1 In addition to selection, detection, attrition, reporting and spectrum bias, 2 a further type of bias has been reported, known as 'design bias'. 3 this occurs before the trial is begun and is inconsistent with the principle of 'equipoise' and has relevance for surgical trials in a different manner to the bias described in drug trials. equipoise is defined as the 'even balance of weight or other forces', or alternatively as an 'equilib-rium'. equipoise is an important concept in clinical trials, not only from an ethical standpoint but also with regards to feasibility and recruitment on the part of both the clinicians involved and the patients who may be recruited. 'clinical equipoise' exists "if there is genuine uncertainty within the expert medical community – not necessarily on the part of the individual investigator – about the preferred treatment ". 4,5 A clinician or researcher enrolling and/or consenting patients into a prospective ran-domised clinical trial must believe that the available evidence does not indicate that the new treatment or intervention being studied is either superior or inferior to the existing standard treatment. 6 However, an individu-al's equipoise can be altered by personal experience, anecdotal evidence or even by single case studies. thus the term clinical equipoise is used to reflect the views of the wider medical community, rather than the individual clinician. In order for patients to agree to participate in a clinical trial, they need to be well informed and understand there is equipoise, otherwise this will inevitably result in inadequate recruitment. When a new treatment is introduced whether it is a new drug or implant, the point of uncertainty within the medical community is not constant and fluctuates with time from the point of introduction. this can be compared with the introduction to other new technologies, such as 3D printing. For these innovations, the uptake of these new devices has been described as the technology life cycle or 'hype' curve, which has five phases (Fig. 1). the technology curve can be adapted to the uptake of medical interventions and follows the levels of evidence of research available , as well as the evolution of data for a given subject area. the first phase is the 'technology trigger' when a new intervention appears on the market and there is …
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