Catherine (Golics) Bottomley and Angela Rylands from pH Associates Ltd (An OPEN Health company) discuss 'Measuring the outcomes that matter to patients in the real world' in this article. They believe that demonstrating value through patient centred evidence in the real world is critical throughout a product life-cycle.
The possibilities and benefits associated with the collection of real world data can often be overlooked amidst the many guidelines and gold standard documents(1,2) for patient-centered outcome (PCO) data collection in clinical trials. The gathering of healthcare data from real world populations to support data from randomised clinical trials is growing in importance. Stakeholders are recognising the value of PCO data that is critical to the drug life-cycle strategies from the early to late stages of drug development. As such, stakeholders are requiring evidence from more representative samples of the patient population, collected over longer periods of time and outside the highly selected clinical trial populations.
What is the value of collecting real world PCO data?
Access to real world patient populations provides a unique and cost-effective opportunity for the collection of PCO evidence to support the value of a drug. Traditionally, real world settings have been instrumental in collecting patient reported data using direct-to-patient methodologies, typically patient surveys. This can include patient-reported ‘hidden cost’ data associated with a disease or treatment, patient-reported experience or satisfaction with a treatment or service, and patient-reported real time data on treatment adherence. These methodologies have been historically considered low-cost, and when conducted robustly and with careful consideration and selection of both the patient population and survey content, provide rich and reliable data that is critical for the value proposition of the drug.
Whilst a robust PCO strategy is important during the early drug development phases for regulatory requirements, real world PCO data can enhance the value proposition by providing invaluable pre-launch evidence that demonstrates the burden of disease or an unmet need in the target patient population. Similarly PCO data, post-launch, can provide evidence that further bolsters the drug’s market place and value to stakeholders. PCO data identifies and highlights the issues and outcomes that matter to patients. The PCO specific assessments are most likely to demonstrate real world clinical effectiveness of a drug by describing quality of life, symptoms or impacts on daily living by including the patient voice either directly from the patient (patient reported outcome, PRO), via the clinician (clinician reported outcome, ClinRO) or via an informer, e.g. a caregiver (observer reported outcome, ObsRO).
PCO data can be collected quantitatively, using relevant and validated outcome assessments, and in the event that more in-depth understanding of both the components and impact of a disease area is required, richer data can be collected through the use of robust qualitative methodologies and thematic analyses. A broader picture of the burden of illness can thus be demonstrated through the inclusion of healthcare professionals and caregivers, to best understand the outcomes that matter to patients (directly from patients or indirectly from caregivers and clinicians) outside of the clinical trial setting.
What PCO data can be collected in a real world setting?
In the real world, PCO assessments are used routinely in some areas of clinical practice and this data can be collected retrospectively from databases, registries or patient medical notes. However, more often than not, data collected through these methods can be of poor quality with high incidence of missing data, which in turn leads to the need for further PCO data from prospective real world studies in the target patient population.
Patient preference data to support the value of a new or existing treatment can be best collected in a real world setting using treatment-experienced patients. Traditional PCO assessments often overlook patient preferences for treatment attributes (e.g. mode of administration of a drug). There is a movement towards increasing the perceived value of a measurement of patient preference by developing individualised PCO instruments seeking to measure the domains of health of importance to each individual and create a more ‘personal’ picture of the patient’s health. HTA bodies are moving towards more explicit, transparent consideration of patient preference data in their regulatory review processes. The EMA recently conducted a pilot study on how patient preference data can be incorporated into the regulatory review process(3) and NICE announced funding of a two year methodological study to explore the most effective means of capturing patient preferences, and how they can be incorporated effectively into HTA(4). Patient preference data are particularly important for understanding the strength of preference for individual treatment attributes and the key drivers of preference, rather than a direct comparison between two named treatments.
Quality of life data for demonstrating cost-effectiveness is another critical piece of evidence which is often best collected in the real world setting, particularly health utility data associated with key health states in an economic model that is valuable for payer stakeholders.
Key considerations of PCO data collection in the real world
For prospective studies collecting PCO data, careful consideration is required around study design, selection of a valid and disease-specific PCO assessment, methodology for patient recruitment and the timing of assessments. Data should be reflective of the target patient population, with the most appropriate method for patient recruitment selected. This may vary depending on whether the patient group is in regular contact with health services, or is a patient population in remission or self-managing their condition. Researchers must also be confident patients are representative of the health state in question, for example, patients with certain health conditions (e.g. Alzheimer’s disease) may not be capable of self-diagnosis or be able to self-report the impact of their symptoms, such that a proxy method of PCO assessment is required.
Critically, the key stakeholders and reasons for data collection must be considered, and the most appropriate and robust methods for capturing such data must meet the relevant stakeholder requirements.
PCO data plays a significant role in drug approval processes, influencing key stakeholders throughout the drug lifecycle, such that collection of high quality and robust data can result in better decision making.
For pharmaceutical and device companies, there is a more compelling need than ever to consider the role of the real world setting in the capture and analysis of PCO data.