A key hurdle facing 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 diabetes mellitus (DM) marketplace for example, is becoming 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.
Approached by a pharmaceutical company to run a one-day workshop for their outcomes team, our task was to demonstrate how data derived from patient reported outcomes (PROs) measures can provide added value in supporting key biomedical endpoints and how this can be done using PRO measures within the context of existing regulatory requirements.
Our main objective of the workshop was:
To provide a sound and practical methodological framework to support the outcomes team in selecting an appropriate PRO for a clinical trial through which treatment effectiveness could be demonstrated by the development of an explicit measurement strategy.
Key elements of the workshop were:
- An introduction to generic and disease-specific PROs – their strengths and weaknesses
- Developing an explicit measurement strategy
- The importance of defining the study’s secondary endpoint(s) e.g. reduction in anxiety
- The relationship between the PRO’s conceptual framework and the secondary endpoint(s) and its importance in selecting the appropriate PRO
What is a measurement strategy?
An effective way of establishing the link between the measured outcome such as the patient’s health status or quality of life following an intervention programme is the development of a measurement strategy, which requires a clear understanding of the disease and the relevant outcomes.
A PRO measurement strategy provides a framework to support the selection of an appropriate PRO for a clinical trial through which treatment effectiveness in terms of health status or quality of life for example, can be demonstrated.
Components of each of the key stages of the strategy are shown below which makes explicit the expected treatment effects e.g. primary biomedical endpoint(s) AND IMPORTANTLY the secondary endpoints such as reduced anxiety to be measured by the PRO.
A critical aspect of the measurement strategy is selecting the appropriate PRO that captures the benefits of the primary physiological endpoint of treatment i.e. secondary endpoint(s). However, outcome teams are frequently faced with a plethora of potential PROs each purporting to measure – often without a sound theoretical or measurement model – specific health constructs such as health status or quality of life. As a consequence the choice of a PRO is often made according to:
- the instrument having been used in previous studies
- its name appears to be appropriate for the intended use
- The psychometric supporting data looks o.k.
There is however, the tendency for those conducting clinical trials to treat the more commonly measured health constructs such as quality of life (QoL), health-related quality of life (HRQoL) and health status as interchangeable in the selection process – they are not. Furthermore, there is no universally accepted definition of QoL for example, but there is the general consensus that it is based on the individual’s subjective evaluation of the psychological, physical and social aspects of their life.
Quality of life also 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. The focus of these measures is on the quality of health including the biological and physiological dysfunctioning, symptoms and functional impairment. While such outcomes can impact on patients’ QoL they cannot be accurately described as indicators of QoL.
During the workshop components of each of the key stages of the strategy were introduced including, the importance of making explicit the expected treatment effects e.g. primary biomedical endpoint(s) and the resulting secondary endpoint(s) articulated through the endpoint model in order to identify outcome domains relevant to the patient and disease from which the most appropriate PRO can be selected. For an example of a simple endpoint model see below.
A key feature of the measurement strategy includes the necessity as part of the PRO selection process, the careful consideration of the relationship between the PRO’s item content, the expected primary treatment and secondary endpoint to be measured by the PRO. Here the importance of the PROs conceptual framework as part of the measurement strategy was stressed.
What What is a PRO conceptual framework?
The PROs conceptual framework shows the item content in relation to the specified concepts the instrument is purported to measure. Therefore, if the selected PRO was purported to measure the various dimensions of sleep disturbance , then the items should relate directly to those dimensions relating to sleep disturbance. For an example of a conceptual framework see below.
Selecting the most appropriate PRO to provide evidence of treatment effectiveness based on the patient’s perspective is a complex process. The aim of this one-day workshop was to provide the H&D Outcomes Team a deeper insight into the concepts and tools 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 Outcomes Team were able to distinguish more clearly between the different endpoints measured by PROs such as QoL health status, wellbeing etc. The Outcomes Team also gained a clearer understanding of the importance of ensuring a strong link between the item content of the PRO, what it is purported to measure and the objectives of the study for identifying potential treatment benefits.
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Categories: Patient reported outcomes