Translating Patient Priorities into JCA Success: Lessons from Early Reports

Why and how pharma needs to plan for comparative evidence around what matters to patients from the outset of clinical development

Translating Patient Priorities into JCA Success: Lessons from Early Reports

Understanding how a treatment changes daily life is central to demonstrating its value to patients and wider healthcare decision makers. For pharma, the challenge is to turn that lived experience into evidence: not only identifying what matters to patients but showing whether a treatment delivers meaningful patient benefit compared with the alternatives.

JCA and the need for comparative evidence

The Joint Clinical Assessment (JCA) framework brings this challenge into focus by providing a common EU approach to assessing how new treatments compare with existing therapies. In this approach EU Member States define how a treatment will be assessed through a PICO – populations, interventions, comparators and outcomes – framework, which specify the questions the evidence needs to address, including those concerning patient-relevant benefits.

In this article, we look at three selected published JCA reports – Ojemda, Imdylltra and Itvisma – and the lessons they offer for future patient evidence strategies. Notably, the evidence packages underpinning these early reports were largely shaped before the JCA framework became operational. Our focus is therefore on implications for future evidence planning, rather than evaluating development decisions made under different expectations.

Ojemda: the outcomes requested by JCA were broader than the evidence available.

The JCA of Ojemda in pediatric low-grade glioma sought to understand not only its effect on tumor growth, but also how patients feel and function. It therefore requested comparative evidence on outcomes including vision, neurological function, fatigue, and quality of life. The developer submitted a single-arm trial supplemented by indirect statistical comparisons against alternative treatments. However, suitable data were not available to assess many of the requested outcomes in these comparisons, and no comparative quality-of-life data were provided. The assessment therefore highlighted substantial statistical uncertainty and evidence gaps regarding long-term comparative benefits and patient well-being. The Ojemda example thus amplifies the need to identify early where the clinical evidence package may leave important patient-benefit questions unanswered, and not to rely on the assumption that evidence on the primary endpoint will sufficiently address them, nor that historical data can easily fill these gaps via indirect statistical modeling.

Imdylltra: collecting patient-reported data is a starting point, not the end of the evidence task.

For Imdylltra in extensive-stage small-cell lung cancer, the JCA requested robust, long-term comparative data on patient-reported outcomes (PROs) in addition to other clinical and safety outcomes, specifically tracking health-related quality of life alongside lung cancer symptoms like cough, dyspnea, and chest pain. While the developer successfully submitted direct randomized Phase III trial evidence alongside indirect treatment models to cover all requested scopes, the open-label nature of the trial heavily compromised the reliability of the patient evidence. The JCA concluded that shortened observation periods, highly imbalanced patient questionnaire completion rates, and asymmetric tracking across study arms completely undermined the validity of the PRO and quality-of-life findings. The example of Imdylltra demonstrates a critical planning implication for developers when preparing PRO data: even with a large-randomized trial, failing to secure rigorous, symmetric, and long-term compliance for patient-reported data collections can lead to the dismissal of vital patient evidence.

Itvisma: even disease-specific measures can miss what matters most to patients.

For the Itvisma gene therapy assessment for spinal muscular atrophy for patients 2 years and older, the JCA requested robust, comparative data on long-term survival, motor function, and caregiver quality of life. While trials demonstrated improvements in primary motor outcomes, they showed highly inconsistent, multidirectional results regarding caregiver burden. The developer relied heavily on a disease-specific caregiver proxy scale (ACEND) that focused on macroscopic motor milestones rather than the everyday changes highlighted by caregiver input to the JCA, such as reduced fatigue, increased stamina, reduced contractures, farther hand reach, or being able to lift heavier items. Furthermore, by omitting direct, child-friendly patient-reported outcomes for the older majority of the trial population (mean age ~6 years), the developer missed a critical opportunity to capture those patients’ own daily lived experiences. The JCA concluded that this measurement mismatch, coupled with an over-reliance on unadjusted indirect treatment comparisons, left immense data gaps and unproven clinical equivalence. The conclusion from Itvisma is that developers should utilize targeted disease-specific instruments alongside direct patient-reported outcomes, co-created with patient experts early on to ensure the chosen framework captures what truly matters to patients and caregivers, and administer them symmetrically across all comparative arms.

Together, these cases highlight three essential questions for planning patient evidence: are the right patient-centered outcomes being measured to support robust comparisons, can the patient data collection remain balanced and complete over the long term, and do the selected metrics capture the everyday changes that truly matter to patients and their caregivers?

From patient priorities to evidence that can support decisions

The Patient Focused Medicines Development (PFMD) assessment of the first three JCA reports also highlights a persistent gap between collecting patient experience data and using it effectively in comparative clinical assessments. Patient input without robust plans and methods for evidence translation risks leaving patient priorities as background context. Conversely, measurement without patient input risks producing precise answers to questions of limited relevance. Closing that gap requires patient insight and evidence design to work together to identify which benefits matter, what meaningful change looks like, and how to demonstrate it against treatment alternatives.

This challenge requires navigating a difficult balancing act during trial design. For example, “maintaining independence” is not yet a usable clinical endpoint. Teams need to identify which daily activities matter most to patients, define what constitutes a meaningful improvement, and select tools capable of capturing those changes. Furthermore, as patient insights become increasingly important across healthcare decision-making, more measures will emerge that developers can select from. This presents a unique opportunity and challenge in clinical trial design. When planning a Phase II or Phase III trial, developers can choose to run prospective head-to-head trials, allowing them to apply modern, optimized patient-centric tools symmetrically across both arms. However, where a direct active-controlled trial is not feasible, such as when a comparator treatment faces geographic availability hurdles, developers must establish comparative efficacy by bridging to historical data. This often necessitates the inclusion of outdated questionnaire measures from past competitor trials alongside newer, potentially better tools that more accurately reflect current patient needs. Packing a trial with too many measures and questionnaires risks overwhelming patients, leading to incomplete or conflicting data – a challenge made even harder by the need to satisfy the different PICO criteria of multiple European countries under the JCA framework. Ultimately, teams must establish a sensible balance of breadth and depth of patient data collected, whether comparable data can be collected for alternative treatments, whether follow-up periods are long enough to demonstrate the benefit, and how missing responses could impact final conclusions.

Plan for comparative gaps – and other uses of patient evidence

While comparative data is gold standard in drug development, an inability to collect comparator data should not be a reason to stop generating patient evidence. It does, however, affect what that evidence can demonstrate. Data from one treatment alone can describe patient experience and changes over time but generally cannot establish greater benefit than an alternative. Where feasible, new comparative studies or comparative statistical approaches can address gaps; however, where existing comparator studies never measured the relevant outcomes, uncertainty may remain despite careful planning.

The uses of patient data by developers extend beyond JCA assessments. Evidence supporting improvements to activities of daily life, caregiver impact, patient/caregiver preferences and treatment burden may support national HTA, shared treatment decisions and a credible path to adoption, even where it cannot establish comparative clinical benefit. Furthermore, while early JCAs have primarily focused on oncology and ATMPs, the critical importance of these patient-centric outcomes will be significantly amplified as the framework expands into broader therapeutic areas, particularly those with more subjective or harder-to-define clinical endpoints. Developers must take the lessons learned from these initial oncology and innovative therapy examples and proactively extrapolate them to their own pipelines before development strategies are locked in. The aim is not to make every piece of patient evidence answer every question. It is to define its intended use, understand its limitations and prioritize the gaps that matter most.

Three priorities for pharma leaders

ur earlier article, Closing the Patient Evidence Gap, explored why ‘patient insight’ often fails to become decision-relevant evidence. These JCA examples make the practical consequences more tangible. For pharma leaders, the implication is to integrate patient evidence into planning before consequential development choices are fixed, with shared ownership across Clinical Development, HEOR, Market Access, Medical Affairs and Patient Affairs. Three priorities turn that principle into action.

  1.  Translate patient priorities into evidence choices.
    Patient Affairs and patient communities can help define what evidence generation should capture. Those insights should inform endpoints, populations and follow-up and should not stop at an insights report.
  2.  Test plans against likely assessment needs.
    Identify gaps in populations, comparators and outcomes while there is still time to act. Focus on reasonably foreseeable assessment questions and where comparator data could limit the conclusions. Where timing allows, developers should leverage the framework's parallel Joint Scientific Consultation (JSC) process early in development to seek aligned guidance from both regulators and HTA bodies on acceptable patient-centric metrics and comparative trial designs.
  3.  Prioritize investment across functions.
    Not every priority requires a new study, and not every gap can be closed. Prioritize investment by importance to patients, decision relevance, feasibility and timing, with clear ownership.

From patient priorities to decision-relevant evidence

The ultimate pharma leadership question is not simply whether patient evidence is being collected, but whether it is designed to inform the decisions ahead. This means translating patient priorities into robust comparative evidence wherever feasible, while recognizing what other patient data can and cannot contribute when comparisons remain incomplete. Patient Affairs brings essential understanding of what matters to patients; the broader cross-functional leadership task is to turn that understanding into early choices about study design, evidence investment and intended use.  

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Meike Wenzel

Meike Wenzel

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