A key hurdle facing outcome teams as with the entire pharmaceutical industry is non-adherence by patients to medication. This problem is only likely to be surmounted if patients believe that taking medication will lead to immediate benefits through reduction of symptoms, improvement in physiological functioning and quality of life.
The DM (diabetes mellitus) marketplace is saturated with multiple medications in both the insulin and pre-insulin space, particularly as analogues start to lose their patents. Differentiation in clinical outcomes within classes is often unclear or minimal. This means that differentiation of therapeutic options is likely to focus more on frequency, mode and method of administration, as opposed to statistically significant differences in glucose control, which are clinically relevant.
There is no consensus in the pharmaceutical industry on the most appropriate population-based balance between diabetes-related physiological outcomes such as blood glucose levels (HbA1c) and measurement of quality of life (QoL).
DHP Research developed a workshop for our client’s Outcomes Team to demonstrate that data derived from patient reported outcome (PROs) measures can provide added value in supporting key biomedical endpoints.
The key challenge was to present the case for investment in the selection and implementation of PROs for clinical trials through the development of an effective PRO measurement strategy which was mindful of the current regulatory concerns.
Outcome teams are faced with a plethora of PROs, each purporting to measure – often without a sound theoretical or measurement model – a range of health outcomes.
As a consequence outcome teams often make their choice of a PRO according to whether it has been used in previous studies or its name appears to be appropriate for the intended use. There is also the tendency in the industry to treat the more commonly measured health outcomes such as QoL and health status as interchangeable in the selection process – they are not.
There is no universally accepted definition of QoL for example, but there is the general consensus that it is based on the individual’s own subjective evaluation of the psychological, physical and social aspects of their life.
Measurement of QoL contrasts with the commonly used measures of health-status such as the SF-36 and EQ-5D which are frequently referred to as indicators of QoL, which they arte not.
The Outcome Team was very aware of these potential pitfalls in the selection of PROs, in Phase III trials. Prior to any consideration of investment in expenditure in a programme of PRO implementation, their main requirement was for their Outcome Team to have a much clearer insight into best practice. This would enable them to provide evidence of treatment effectiveness, and benefit from the patients’ perspective across the DM product’s life cycle within the context of new regulatory requirements.
A one-day workshop was convened for the Outcome Team, the primary aim of which was to provide them with a practical measurement strategy which would assist in the selection of appropriate PROs for their Phase III & late phase DM studies. The workshop addressed three specific questions posed by H&D which were:
- What is achievable using a PRO?
- How can we distinguish between the different measured endpoints?
- How can we understand a PRO score in relation to clinical endpoints?
The workshop was initiated with a comprehensive and interactive overview of the benefits to the outcome team through the patient’s perspective using PROs. This was followed by an in-depth exploration of key stages of the strategy including:
- Making explicit the expected treatment effects e.g. primary biomedical endpoint(s).
- Linking these – through the articulation of an endpoint model – to outcome domains relevant to the patient and disease from which the most appropriate PRO can be selected.
Differentiation between the different secondary endpoints was also extensively explored, e.g. does the EQ-5D and SF-36 measure QoL or health status?
The PRO’s conceptual framework – the linkage between the PRO’s item content and its specific measurement domains – was emphasised to the team, as was its relationship with the expected primary treatment outcome(s) and study objectives.
Generic and disease-specific PROs, together with their strengths and weaknesses, were also explored. Ways to increase and aid interpretation of the relationships between clinical endpoints and PRO scores were also taken into consideration.
Selecting the most appropriate PRO to provide evidence of treatment effectiveness, based on the patient’s perspective, is a complex process. PROs are frequently and inappropriately selected on the basis of what they appear to be measuring.
The aim of this one-day workshop was to provide the Outcome Team with a deeper insight into the concepts and tools needed to develop an explicit and successful measurement strategy, to enable the selection of an appropriate PRO to meet the requirements of a specific clinical trial.
As a result of the workshop the Outcome Team was able to differentiate more clearly between the endpoints purported to be measured by PROs such as QoL health status, HRQoL, etc. and select the most appropriate for a given purpose.
The team also gained a clearer understanding of the importance of developing an explicit endpoint model to ensure a strong link between the PRO’s item content, what it should measure and the objectives of the study for identifying potential treatment benefits.