With the clinical trial landscape increasingly patient-centred, the inclusion of Clinical Outcome Assessments (COAs) has become a regulatory and scientific necessity. COAs offer vital insight into how patients feel and function within their condition, and in response to treatment—beyond what biomarkers or survival endpoints alone can show.

A well-integrated COA strategy can:

  • Strengthen primary and secondary endpoint justification
  • Improve trial relevance for regulatory and HTA audiences
  • Generate patient-focused evidence to support labelling, publications, and value communications

What COAs Are and Why They Matter

A Clinical Outcome Assessment (COA) measures outcomes from the patient’s perspective. These include:

  • PROs (Patient-Reported Outcomes): e.g. pain, fatigue, HRQoL
  • ObsROs (Observer-Reported Outcomes): typically used in paediatric or cognitively impaired populations
  • ClinROs (Clinician-Reported Outcomes): e.g. clinician-rated scales
  • PerfOs (Performance Outcomes): e.g. walking tests, cognitive assessments

These can serve as:

  • Primary endpoints (regulatory-driven)
  • Secondary endpoints (interpretive support)
  • Exploratory endpoints (HTA or scientific insight)

A Structured Framework for Strategic COA Planning

Effective COA integration requires more than selecting instruments late in protocol development. A deliberate, structured approach from the outset ensures the measures are meaningful, validated, and operationally feasible. We recommend a three-stage framework:

Stage 1: Define Concepts of Interest

  • Identify relevant symptoms, functional impacts, and HRQoL domains
  • Use qualitative research and literature review to ensure patient-centred concepts
  • Consider subgroup and cultural representativeness for generalisability

Stage 2: Review Available Instruments

  • Evaluate alignment of existing COAs with selected concepts
  • Screen for usability, e.g. clarity, burden, recall period, and language coverage
  • Use evidence from FDA/EMA labels, clinicaltrials.gov, and HTA assessments

Stage 3: Confirm Fit-for-Purpose and Identify Gaps

  • Assess psychometric validity, e.g. reliability, responsiveness, content validity
  • Evaluate acceptability and real-world feasibility
  • Recommend endpoints and outline additional research if needed—for example:
    • Discrete choice experiments to quantify patient preferences
    • Exit and in-trial interviews to clarify treatment experience and burden
    • Vignette studies to support utility value estimation for economic modelling

Practical Considerations

  • Don’t overload patients. Too many or complex instruments reduce data quality.
  • Select pragmatically. Regulatory and HTA needs must align with operational feasibility.
  • Think globally. Ensure instruments are translatable and culturally valid across trial geographies.
  • Plan for interpretation. Consider supporting interviews to contextualise PRO data.

COA strategy is not just a regulatory checkbox—it’s a core element of clinical trial design that shapes how your treatment is understood, valued, and ultimately accessed. Early and proactive integration helps avoid endpoint misalignment, missed insights, and missed opportunities to generate evidence on aspects of disease burden and treatment benefit that are both meaningful to patients and to regulatory and HTA decision-making.