Should real-world evidence contribute to pain management ?
In recent years , a greater emphasis has been placed on the evidence generated from real-world studies . Such studies are invaluable in therapy areas such as chronic pain , largely because of their longer duration , allowing for a greater evaluation of the impact on a condition over time
João Parracho da Costa MD PhD Associate Professor of Clinical Pharmacology and Therapeutics ; Deputy Director , Center for Evidence-Based Medicine ( CEMBE ); Principal Investigator , Instituto de Medicina Molecular , Faculdade de Medicina da Universidade de Lisboa , Portugal
A well-designed randomised controlled trial
( RCT ) is the most rigorous way of determining whether a cause – effect relationship exists between a treatment and patient outcomes through balancing the intervention and control groups which minimises bias . Thus , for many stakeholders , RCT represents the most reliable barometer of the potential value with regards to efficacy of a therapeutic intervention in the treatment landscape . While RCTs are key for regulatory and approval purposes , they can only partly provide the necessary data required for full assessment of the true value of a therapeutic intervention .
All RCTs are to some degree biased , in particular due to sample and measurement bias . Nevertheless , in many circumstances , including at the point of care level between physician and patient , RCTs represent the most robust evidence to inform our decisions . This is a judgement that should take into consideration that the strength of evidence behind the value of a therapeutic intervention is determined by its internal validity and then its generalisability ( how useful the results are in practice for a particular patient in its particular setting ). Decisions on disease management should balance the data hierarchy with the quality of the design ( confounding factors , generalisability , missing data , valid data elements ). In fact , a well-designed non-randomised trial might provide a higher certainty in the findings than a poorly designed RCT .
Notwithstanding the enormous costs involved , RCTs are associated with limitations which constrain the generalisability of the findings to everyday clinical practice . 1 One of the reasons being that most Phase II and Phase III trials recruit patients that are typically highly homogenous and data collected is closely controlled and monitored . These RCTs inherent limitations could be exacerbated by biases in design , recruitment , sample populations and data analysis . 2 Therefore , data from RCTs pose some effectiveness challenges for disease management , including : 1 ) the population studied ( could be not consistent with the population for which we are planning to give the intervention and / or uncertainty exists about treatment effects in subgroups based on pivotal trial populations ); 2 ) the intervention ( study medication schedule [ dose , dose titration / escalation , frequency , route of administration , monitoring ]) can be inconsistent with routine practice and / or effectiveness is likely impacted by adherence [ to the intervention and / or comparators ] in routine practice ); 3 ) the control arm ( study comparator / s ) may not include current standard of care for the target population and / or indirect comparisons are uncertain due to a small number of trials from which to form a valid network ; and 4 ) the outcomes measured in RCTs usually do not evaluate the impact of the intervention in the main categories of patient health outcomes : humanistic – impact of an intervention on patient-reported endpoints ; clinical – measurable changes in patient health status due to an intervention ; and economic – impact of an intervention on budgets . In addition , hospitals need guidance on pathways and protocol decision-making ( hospitalisation rate , impact on economics ).
As a consequence , there is increasing use of what has been termed real-world data ( RWD ), generally defined as data capturing patient-level information used for decision-making that are not collected in conventional RCTs . 3 RWD can serve as the basis for real-world evidence ( RWE ), defined by the US Food and Drug Administration ( FDA ), as “ clinical evidence regarding the usage and potential benefits or risks of a medicinal product derived from analysis of real world data .” 4 In reality , both sources of evidence should be considered as complementary : an RCT will demonstrate the effect of a treatment in a controlled environment whereas RWE might show the effectiveness of the treatment in a wider and more generalised population . Effectiveness data should therefore be considered in the process of clinical decision-making and managing mostly when the clinical field is heterogeneous as in the case of pain .
The value of RWE One of the main advantages of RWE is that it is produced from data generated outside the confines of an RCT and is thus more likely to reflect everyday clinical practice . For instance , RWE is gathered from a wider patient demographic including individuals from more ethnically diverse backgrounds as well as those with comorbidities excluded from the original RCTs . Additionally , RWE provides an estimation of the efficacy of a treatment when used alongside a patient ’ s concomitant medication or on the economic burden of a disease or a treatment for healthcare systems . Sources of RWE are varied and include clinical disease registries , administrative claims data , electronic health records , patient surveys and either retrospective or prospective observational studies . A further source of RWE are pragmatic clinical trials , which are designed to provide answers to the real-life questions faced by patients , clinicians and policy makers and combine the rigour of an RCT with the real-world nature of an observational study . 5
There is a growing interest in RWE especially from the pharmaceutical industry as regulators are beginning to consider such evidence in drug
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