, Sam Salek2 and Stuart Walker3
(1)
Centre of Regulatory Excellence, Duke-NUS Graduate Medical School, Singapore, Singapore
(2)
Department of Pharmacy, University of Hertfordshire, Hatfield, UK
(3)
Centre for Innovation in Regulatory Sciences, London, UK
The regulation of medicines is essentially conducted to ensure patients’ accessibility to medicines that fulfill the criteria of quality, safety, and efficacy. As patients are not equipped to make a scientific assessment, regulators play an important role in controlling the access to safe and effective medicines. Two of the key elements highlighted by the World Health Organization (WHO 2003) for effective regulation of medicines included strong cooperation and collaboration between stakeholders and transparency and accountability. The latter is deemed critical for the communication of the basis of decisions and building public confidence. In the WHO’s strategic directions for medicines (WHO 2010), new policy and guidance was developed to ensure transparency and good governance in pricing, procurement, and regulation.
The review of medicines by regulatory agencies is largely based on the submission of clinical data collected from clinical trial phases I to IV. The US FDA may occasionally be involved in the developmental phases of a product through investigational new drug (IND) applications, where the trial data generated will subsequently feed into the new drug application (NDA) for a marketing authorization. The assessment of clinical efficacy of a medicine is supported by studies which are statistically designed to provide a reliable and robust conclusion through the scientific investigation of suitable endpoints. It is expected that these measured endpoints would be translated to meaningful benefits to the patients intended for the treatment. However, due to practical reasons to conduct and complete a trial in a timely manner for generating the required clinical data, these measured endpoints may be surrogates of the actual clinical benefits on the basis of the observed effect on these endpoints. These types of endpoints include parameters like blood pressure, cholesterol levels, or microbial eradication which may not translate to reduced cardiovascular events or a faster recovery from an infection. To establish the utility of a medicine, some trials are required to produce clinical endpoints that could directly benefit a patient, such as overall survival, reduction in hospital stay, or an improved quality of life from a chronic debilitating disease. However, a clinical trial is limited by its scientific robustness in taking into account the many other factors that would constitute a benefit to a patient. Indeed the definition of a benefit may differ among physicians, patients, and between diseases. This may be due to differences in the severity of the disease itself and the subjective perception of the expectations arising from the treatment. Moreover, a benefit should also take into account the trade-off incurred from the potential adverse effects of the treatment. As a result, the endpoints from a well-designed clinical trial may not always produce a meaningful beneficial treatment for the patient. A proven clinical efficacy in a study therefore may not always translate into a benefit for the patient.
In the assessment of risk or harm, safety data are collected alongside the conduct of the clinical studies which are primarily designed for the purpose of proving clinical efficacy. As such, there could be more subjectivity in the perception and conclusion of risks to the patients and how the safety information may be rationalized into objective outcomes (Slovic et al. 2004). In a study conducted by the EMA as part of the benefit–risk methodology project, the variability in the individual risk perception of regulators was reviewed (EMA 2011a). The differences appeared to be related to gender, years of regulatory experience, the medicine itself, and specific benefit and risk dimensions. It was recommended that a tool be included as part of a benefit–risk assessment framework to increase the awareness of this subjective component in decision-making and therefore introduce transparency and consistency into the process. Moreover, the number of patients in a clinical trial could not always elucidate the rare adverse effects which could be medically severe and significant. At the point of a product approval for market authorization, there is only limited information on the potential risks. This is mitigated by post-marketing risk management plans and pharmacovigilance activities to further monitor the safe use of the product, so as not to further impede the timely access of a potentially useful medicine.
In a discussion of the changing role of clinical pharmacology on drug development (Zineh and Woodcock 2013), it was commented that given the review staff at US FDA had a different preference for strategies, a robust framework is now needed to help them understand if their review strategy is appropriate for the medicine. This is to help reduce the uncertainties relating to their decisions that may have contributed to an observed excessive aversion to risks. This may also contribute to an understanding and addressing the current issue of the huge financial investment in drug development and an unexpected high failure rate during development.
Given the limitations and uncertainties in confirming the individual benefits and risks to patients, it will be a challenging task to justify the likely outcomes to a patient. In making any decision, it should always entail the perspectives of expected advantages and the potential disadvantages that may be incurred. Likewise, for exploring options in managing the medical condition, the treatment should be viewed in terms of the benefits, risks, and uncertainties involved. The traditional method of assessing efficacy and safety separately could not be logically collated to provide a balanced view. It can be assumed that agencies would have gone through much deliberation on the trade-offs between the benefits and risks, but these are generally not documented or made known to the public.
Breckenridge (2010) shared his views on the challenges in the assessment of benefits and risks of medicines, where the shift is mainly to review the overall balance between the benefits of a drug and the associated risks rather than the individual impact. This balance could be expressed in a transparent manner using a structured framework which aids in the communication of the differences in opinions between regulators and the drug developers. Indeed, for the regulatory challenges to be adequately addressed, there must be further integration among the stakeholders.
This shift in paradigm had already been observed much earlier, when there was a movement from safety, efficacy, and quality to relative safety, comparative efficacy, and relative quality. In moving from a risk-centric approach, the risk management strategy assesses the identified potential safety issue in the light of an overall change in the benefit–risk balance, as well as exploring new benefits in addition to managing the risks (CMR 2002). The EMA (2008) realized the importance of reviewing both benefits and risks as an overall balance in their regulatory decision-making and therefore produced a reflection paper on the benefit–risk assessment of medicines. This movement added to the ICH final concept paper (ICH 2010) to review the current periodic safety update reports (PSUR) and focus on benefit–risk evaluation, leading to the current periodic benefit–risk evaluation report (PBRER). It is however noted that the benefit–risk evaluation can be carried out qualitatively without the need for a formal mathematical or quantitative tool. In early 2013, EMA put the PBRER into effect (EMA 2013a), supporting this initiative as there is now greater emphasis on risk management planning and recognizing that new safety information can only be meaningfully assessed in the context of the medicine’s benefits.
A study of clinical practice guidelines to assess how well patient preferences are incorporated showed that current practice guidelines did not integrate patient preferences (Chong et al. 2009). Given the differences in the understanding of scientific evidence and values in decision-making, there is an expected variability in the contribution (Umscheid 2009). Yet we know that the regulation of medicines is moving towards being patient centric so that decisions are made in the view of the wide-ranging needs of patients which can only be obtained if communications with stakeholders is part of the process (Walker and Moors 2006). Indeed the increasing importance of patients’ perspectives in the form of patient-reported outcomes in clinical trials can complement the traditional efficacy endpoints (Hareendran et al. 2012). With various examples of how patient decisions had influenced the availability of some medicines including HIV drugs and monoclonal antibodies, it is only prudent to include the views of the patients in expressing the benefit–risk balance (Breckenridge 2011).
Both EMA and US FDA have indicated their plans to incorporate stakeholders’ views into their benefit–risk assessment and decision-making process. In a workshop conducted to review the patient’s role in benefit–risk assessment (CIRS 2012a), it was proposed that patients’ preferences and their values be brought into the regulatory decision-making system through public hearings, patient representation, or incorporation of such measures into clinical trials. In another workshop on framework development, patient inputs were identified as important when the medical condition involves subjective benefits and risks (CIRS 2011). The US FDA alluded to the agency’s plans, as part of the Prescription Drug User Fee Act (PDUFA) V (FDA 2012a, 2013a, 2013b, 2013c, 2013d, 2013e), to obtain patient perspectives on disease severity and unmet medical needs. Therefore, it is expected that a framework for the assessment of benefits and risks should be able to reflect the contribution of patients’ perspectives in the benefit–risk balance and the final regulatory decision.
In a study on the effect of format on understanding the benefits and risks of clinical trials, it was found that pictographs are superior in providing an adequate overall understanding (Tait et al. 2010). The use of graphics and other visual displays are being used more often and also as an adjunct to verbal and numerical communications of risks (Lipkus 2007). In a workshop to discuss the development of a framework that informs stakeholder perspective and clarity of decision-making (CIRS 2011), it was agreed that visualization tools could provide a focus for benefit–risk discussions on critical issues, identifying gaps and exposing overlapping benefits and harms and providing a succinct summary of the information needed to make benefit–risk decisions. Hence it would be appropriate for a framework that assesses benefits and risks to incorporate visualization of the outcomes to facilitate the communication to stakeholders.
Recent Significant Contributions by Various Stakeholders
Academia
Mussen et al. (2007a, 2009), in the course of their published works for developing a systematic approach to decision-making during the assessment of medicines, reviewed benefit and risk criteria through identifying these from the ICH’s Common Technical Document (CTD), EMA’s European Product Assessment Report (EPAR), and US FDA’s Medical Review. The identified criteria were subsequently verified through a survey and refined in a workshop conducted by CMR (CMR 2008) and produced recommendations for a future framework. The following efficacy parameters should be included in a benefit–risk framework:
Magnitude of treatment effect as observed in the pivotal studies
Clinical relevance of the observed magnitude
Statistical significance
Relevance of primary endpoints and studied population of the pivotal studies
Discussions on dose and comparators
Methodology and study design issues
Validation of scales and outcome measures
Evidence of efficacy in relevant subgroups
Confirmation of efficacy by secondary endpoints and supporting studies
Patient-reported outcomes
Patient compliance
The framework should also include the following safety parameters:
Overall incidence of serious side effects
Discontinuation rates due to adverse effects
Incidence, seriousness, and duration of specific adverse effects
Extrapolation of safety profile to intended population for the indication
Adverse effects of the pharmacological class and other related classes
Safety in subgroups
Concerns arising from nonclinical evaluation
Overall incidence of adverse effects by categories
Drug–drug and drug–food interactions
Potential for off-label use and safety concerns
Risk mitigation plans and strategies
In constructing a benefit–risk balance, Mussen et al. (2009) recommended the following parameters as part of the framework:
Description of alternative therapies or interventions
Calculation of uncertainties on benefits and risks
Direct comparison of gains versus harms in terms of lives saved or lost or clinical events
Evaluation of acceptable risk with regard to the clinical benefit in the specified context
Evolution of the benefit–risk balance over time
Evaluation of benefit–risk in major subgroups
Identification of outstanding issues and potential post-marketing commitments
Consideration of different regulatory options for approval
In a review of the benefit–risk assessment models, Mussen et al. (2009) reviewed three general models, namely, “principle of threes” (Edwards et al. 1996), evidence-based model (Beckmann 1999), and Transparent Uniform Risk–Benefit Overview (TURBO) (CIOMS 1998). They were found unable to balance the benefits and risks and did not meet his criteria for a framework to assess benefits and risks. These models did not define clearly the type, quality, and relative importance of the data required. The models were simple, could not account for different attributing factors, and were not validated in practice. However, these models would collate the thoughts and considerations of the assessment and hence contribute to decision-making. Mussen et al. proceeded to develop a new framework which would function as a model for decision analysis. The MCDA (Belton and Stewart 2001) formed the foundation of this framework, as it allowed the balancing of multiple criteria, namely, the different benefits and risks of treatment with the medicine being assessed. This is a process described in the multi-criteria analysis (MCA) manual (Dodgson et al. 2009) which aimed at exploring the individual contributing aspects of the decision-making process before collating the outcomes to form the basis of the decision. There are three key phases of the MCDA process. The problem is first identified and structured, secondly the decision maker’s preferences are taken into account, and lastly, action plans are developed.
A final seven-step framework based on the MCDA principles was eventually developed (CMR 2010). The assessment of the benefit–risk balance was recommended to be carried out as follows:
1.
Establish the background and context of the decision.
2.
Identify the options to be considered (treatment, placebo, or active comparator).
3.
Identify the criteria (benefits and risks) and arrange these into a value tree.
4.
Establish scales for the criteria and score the options on the criteria.
5.
Assign weights for each criterion.
6.
Normalize the weights and calculate the weighted scores and overall preference score for each option.
7.
Examine the results and conduct sensitivity analysis by varying the weights of the criteria.
A framework uses a set of underlying principles to provide an overarching structure in which essential processes can be carried out to achieve its objectives. Therefore, despite the use of values and weights, both the MCDA and the above seven-step approach should be considered as frameworks rather than quantitative methodologies, in recognition of the underlying MCA principles described above.
Part of the framework development involved participants in two CMR workshops (CMR 2004, 2005) who applied the framework in two clinical settings. The first involved the use of a new recombinant necrosis factor receptor inhibitor compared against methotrexate in managing rheumatoid arthritis and the other a hypothetical drug with cardiovascular safety concerns for treating schizophrenia. One utility of the framework was the provision of a platform for structured conversation and decision conferencing, which allowed an agreement despite a divergence in the opinions of the data. In addition, the workshops demonstrated that use of values and weights is required to provide a complete judgment on the benefits and risks. The framework was also applied to various other clinical scenarios (Mussen et al. 2007b). The final conceptual framework was adopted by CIRS (2009, 2010) and further refined through future workshops.
As part of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Risk–Benefit Management Working Group, Guo et al. (2010) conducted a literature review on quantitative methodologies for the assessment of benefits and risks of medicines. The search was not limited to a single stakeholder’s perspective and thus included tools used by regulatory agencies, pharmaceutical companies, and academia. They identified and reviewed 12 quantitative benefit–risk assessment models, which included the Quality-Adjusted Time Without Symptoms and Toxicity (Q-TWiST) (Gelber et al. 1993; Cole et al. 2004), number needed to treat (NNT)/number needed to harm (NNH) (Holden et al. 2003a, b; Laupacis et al. 1988; Cook and Sackett 1995), incremental net health benefit (INHB) (Garrison et al. 2007; Lynd et al. 2010), probabilistic simulation method (PSM) and Monte Carlo simulation (Lynd and O’Brien 2004; Shaffer and Watterberg 2006), multi-criteria decision analysis (MCDA), and stated preference method (SPM) (Ryan et al. 1998; Gan et al. 2004). Some models like the NNT used subjective weighting and allow a non-statistical or qualitative assessment, and others like the MCDA and SPM were useful in allowing joint assessment of both benefits and risks. Simple methods like the NNT and NNH are widely used, but it could not account for the quantum or value of the benefits and harms or allow the contribution of several relevant benefits and harms into the same context for decision-making. In addition, MCDA was found to be capable of handling missing data and uncertainties through use of relevant modeling tools and application of weights, as well as exploring the robustness of the outcomes through sensitivity analyses. While MCDA could account for the various factors contributing to the decision-making, it is nonetheless a relatively new and intensive tool that may be limited to more complex evaluations. The SPM is a theoretical tool that could incorporate patients’ preferences and the evaluation of benefit–risk trade-offs. This method would require the collection of patients’ treatment preferences, for which the current best practice to achieve this is still being developed. However, the SPM may be considered by healthcare professionals as it involves the opinions of the patients. Overall, it appeared that the reviewed methodologies were not adopted by the agencies and companies and were primarily for research purposes. Guo et al. (2010) concluded that some of these methodologies would be helpful to lessen concerns over the subjective component of assessment and provide the required transparency, but all have their own set of limitations. None was found to be able to function across all scenarios, and it was recommended that various tools be used to appropriately profile the benefit–risk balance. Due to the limited published information for net clinical benefit analysis, the principle of threes, and the net-benefit-adjusted-for-utility analysis, these methods were not reviewed.
Regulatory Agencies
As expectations of stakeholders change with the rapid advancement of science, regulatory agencies make plans to adapt and meet these changing needs. In EMA’s roadmap to 2015, they identified one of the strategic areas to be facilitating the access of medicines through reinforcing the benefit–risk balance assessment model, to be achieved through a set of priority activities (EMA 2011b). These included looking at appropriate quantitative tools, improving the quality and consistency of the outcomes, reviewing the EPARs to improve communication of benefit–risk decisions to stakeholders, and increasing the involvement of patients, academia, and healthcare professionals in the assessment of medicines to ensure their views are taken into consideration. A CHMP working group was formed in 2006 to look into methods to improve the transparency, consistency, and communication of benefit–risk assessment. A preliminary review of NNT/NNH, “principles of three,” Transparent Uniform Risk–Benefit Overview (TURBO), and MCDA was conducted, and the advantages and limitations of each were discussed. In their report, they emphasized that qualitative evaluation and expert judgment are not to be replaced by quantitative benefit–risk assessment. They recommended that a model for benefit–risk assessment should be structured and, of a qualitative approach, be able to describe explicitly the importance of benefits and risks in the context of the decision and the impact of the uncertainties on the benefit–risk assessment (EMA 2007). This led to the reflection paper for benefit–risk assessment of medicines as mentioned above and also the benefit–risk methodology project.
The benefit–risk methodology project was aimed at looking at tools and processes that provide aid to regulatory decision-making, training of assessors, and communicating benefit–risk decisions to stakeholders (EMA 2009), through a series of five work packages. The first work package (EMA 2011c) was to describe the practices of benefit–risk assessment within the EU for the centralized procedure. The key findings steered the movement of the remaining work packages, and these findings appeared to be reflective of the global environment. Among the key findings were:
1.
Variability in the understanding and definitions of “benefit” and “risk.”
2.
The benefit–risk balance is assessed mainly intuitively and by matter of expert judgment or extensive discussion.
3.
Importance of consistency in decisions and the process of decision-making.
4.
There is no system or model currently used by any agency, and many felt there could be improvement made for the existing processes.
In addition, the EMA produced a set of five criteria to verify a model’s applicability for benefit–risk assessment. These include logical soundness, comprehensiveness, acceptability of results, practicality, and generativeness.
As part of their benefit–risk methodology project, twenty-one approaches were reviewed, including three qualitative frameworks (BRAT, CMR framework, and US FDA’s benefit–risk framework) and 18 quantitative models in the second work package (EMA 2010). This was conducted with the above five criteria for a benefit–risk assessment model. In response to the observation in the first work package, they attempted to redefine benefits as favorable effects, harms or risks as unfavorable effects, and uncertainties as variations, bias, flaws, and deficiencies of the above types of effects. With regard to the qualitative frameworks, these were still under development at the time of the review, and hence limited comments were made. It was highlighted, however, that the uncertainties of benefits and risks, being of concern to regulators, should be addressed by these frameworks. The quantitative approaches were reviewed according to four broad categories based on their functions, namely, simulation, models, statistics, and measurements. Some of the approaches reviewed included the Markov processes (Sonnenberg and Beck 1993), TURBO, principles of three, QALYs/disability-adjusted life years (DALYs), Kaplan–Meier estimators (Kaplan and Meier 1958), and conjoint analysis (Johnson 2006). They concluded that four approaches, namely, the qualitative framework, MCDA, Bayesian statistics (O’Hagan et al. 2006; Ashby and Smith 2000), and decision trees (Goodwin and Wright 2009; Stonebraker 2002), would be useful to regulators and can comprehensively quantify a benefit–risk balance. A qualitative framework would be required to support any quantitative model and may be used for simple decision-making. Again, it was recommended that a combination of tools would be useful in selected situations involving magnitude, seriousness, and uncertainty of the effects. With the findings and understanding of the potential of the MCDA in this area, EMA proposed their own benefit–risk framework which consists of eight steps, the PrOACT-URL (Table 1.1). This is meant to be a flexible framework that can accommodate the various scientific methodologies for assessing benefits and risks, as well as a graphical representation of the outcomes of assessment.
Table 1.1
The proposed qualitative framework from EMA’s PrOACT-URL
Steps | Actions | |
---|---|---|
1 | Problem | Determine the nature of the problem and its context |
Frame the problem | ||
2 | Objectives | Establish objectives that indicate the overall purposes to be achieved |
Identify criteria of favorable and unfavorable effects | ||
3 | Alternatives | Identify the options to be evaluated against the criteria |
4 | Consequences | Describe how the alternatives perform for each of the criteria, that is, the magnitudes of all effects and their desirability or severity and the incidence of all effects |
5 | Trade-offs | Assess the balance between favorable and unfavorable effects |
6 | Uncertainty | Assess the uncertainty associated with the favorable and unfavorable effects Consider how the balance between favorable and unfavorable effects is affected by uncertainty |
7 | Risk tolerance | Judge the relative importance of the decision makers’ risk attitude for this product and indicate how this affected the balance |
8 | Linked decisions | Consider the consistency of this decision with similar past decisions and assess whether taking this decision could impact future decisions |
The PrOACT-URL was subsequently applied to the third and fourth work packages. In the third work package (EMA 2011d), the framework guided the review of selected quantitative approaches conducted retrospectively using the European Public Assessment Reports (EPAR). The products reviewed were Acomplia® (rimonabant), Cimzia® (certolizumab), Sutent® (sunitinib), and Tykerb® (lapatinib) using a combination of MCDA, probabilistic simulation (PSM), Markov model, and decision tree. The use of the framework and the quantitative approaches allowed for different perspectives to be tested, reviewed the impact of uncertainties, as well as provided a structure to the review and communicated explicitly the objectives and trade-offs. However, this current method would be labor intensive and require the availability of suitable software to conduct the various analyses. Moreover, justifications for clinical judgment were not accounted for as the outcomes were to be quantified.
The ability of the PrOACT-URL to accommodate a quantitative aspect of benefit–risk assessment shown in this work package was reported and published by Phillips (Phillips et al. 2011). The fourth work package (EMA 2012) continued to support the findings in the third work package, the use of PrOACT-URL framework, and the value of graphical displays. It was recommended that the effects table be used for simpler cases and a full MCDA approach be employed for contentious cases. The last work package would be the development of training materials which have not been published at the time of this research. On top of the work to identify benefit–risk methodologies, EMA has also extended its transparency movement to include publication and public access to clinical trial data (EMA 2013b).
Since 2009 the US FDA has taken initiatives to explore systematic approaches to assess and communicate benefits and risks, in tandem with the efforts taken at the EU. The initiatives included the development of a framework to characterize and provide a structure for the benefit–risk assessment already existing in their decision-making processes, as well as communicate the reasoning behind the decision to all stakeholders (FDA 2012a). This led to the current five-step benefit–risk framework which was put together after a pilot project in 2012. The five steps are related to the five key areas to be discussed in the assessment of the medicine, namely, the analysis of the condition, the medical need for the product, clinical benefit, risk, and risk management (FDA 2013a). The strength of the evidence and its uncertainties would be considered during the assessment, with the reasons provided for the conclusion of each of the five areas. The outcomes of these five areas would then be cumulatively discussed, leading to the overall benefit–risk conclusion. The framework would also look into current treatment options, a summary of the submitted evidence for the benefits and risks and risk management plans. With the development of this initial framework, the US FDA embarked on the 5-year plan, starting 2013 till 2017, for a structured approach to benefit–risk assessment, which was part of the larger PDUFA V program. During this period they will further refine the framework and how this might be worked into their current clinical reviews to facilitate communication. Mullin of the US FDA, during a workshop conducted by CIRS (2011), commented that this structured framework had the potential to improve the predictability and consistency of decision-making as it is capable of clearly outlining both the available evidence and the uncertainties. It would also articulate the consideration and clinical judgment taken for the benefit–risk decision and hence improve the transparency of the decision-making process.
The US FDA acknowledged that the existing programs to facilitate patient representation may be inadequate, and thus they are committed to a new initiative, Patient-Focused Drug Development. This aims to obtain the patients’ perspective on the medical condition and the currently available therapies for a set of disease areas and runs till 2017. For each disease area, FDA conducts a public meeting and invites participation from FDA staff, the relevant patient advocates, and other interested stakeholders. Diseases covered thus far include chronic fatigue syndrome and myalgic encephalomyelitis (FDA 2013b), human immunodeficiency virus (HIV) (FDA 2013c), lung cancer (FDA 2013d), and narcolepsy (FDA 2013e). Other diseases planned for 2014 and 2015 include fibromyalgia and sickle cell disease. The US FDA has also published its own user’s guide on communicating benefits and risks (FDA 2011), which provides the expectations and standards of communicating risks.
In the MHRA’s corporate plan for 2013–2018 (MHRA 2013a), it was indicated that benefit–risk decisions should be made more informed by the experiences and perspectives of patients and views from other stakeholders. This is to be achieved through initiatives like more stakeholder partnerships to increase the understanding of benefits and risks of medicines and a better representation of patient and public views in regulatory decisions.
Through their new initiatives for the next 3 years, TGA will be focusing on increasing transparency and engaging stakeholders with a new framework for communications which is committed to relaying the benefits versus risks approach in their regulation of medicines (TGA 2013). This is to be achieved through information that is easily understood by patients and consumers and received and shared by healthcare professionals. TGA aims to provide accessible, clear, and consistent relevant information through various multimedia platforms. In addition, consumers would be consulted for the labeling changes. The stakeholder engagement is also extended to the healthcare professionals, in improving the awareness and accessibility to relevant information.
Pharmaceutical Companies
To a similar extent, the pharmaceutical industry has been also taking an initiative to address the need for an improved benefit–risk assessment by developing a structured, systematic, and transparent framework. Led by the Pharmaceutical Research and Manufacturers of America (PhRMA), the Benefit–Risk Action Team (BRAT) Framework sought to incorporate all relevant aspects of benefits and risks and focused on both qualitative and quantitative analyses, for the purpose of communication between the companies and regulatory agencies. The framework aimed to advance the reproducibility, transparency, and communication of the basis of the benefit–risk decisions (Coplan et al. 2011). This six-step framework (Table 1.2) is a flexible structure which allows the use of appropriate scientific tools to analyze the outcomes.
Table 1.2
The Benefit–Risk Action Team (BRAT) framework
Steps | |
---|---|
1 | Define the decision context |
2 | Identify outcomes |
3 | Identify and extract source data |
4 | Customize the framework |
5 | Assess outcome importance |
6 | Display and interpret key benefit–risk metrics |
In a workshop organized by CIRS (2011), Hughes from Pfizer reviewed the steps of the BRAT framework and the history of its development. The process of BRAT framework starts with defining the decision context (including the formulation, indication, patient population, comparators, and decision perspective). Next, the benefit and risk outcomes are identified and selected, followed by the creation of an initial value tree which determines the preliminary set of outcome measures. In step three, source data are extracted to support outcome measures and input into summary tables. The framework is then customized and the value tree reexamined and revised to incorporate any additional clinical context. In step five, the outcome is assessed for its importance, with informal or formal weighting methodologies being employed to determine the relative importance of all outcomes. Finally, the key measures and data are summarized in a visual format to aid the interpretation and decision, information gaps are filled in, and sensitivity analyses are conducted.
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