
- How does a new treatment compare with the optimal therapeutic option according to routine clinical practice?
- What are the clinical outcomes when the new treatment is administered in real-life cancer patients or in off-label indications?
- Would it be better to shift the focus to how to combine and/or sequence the new treatment with the existing therapeutic options?
- What is the optimal administration scheme/treatment duration and at which benefit/risk ratio?
- What are patient preferences regarding multiple therapeutic options?
- What are the long-term issues related to the treatment?
“Why is medicine the only field where we accept so much uncertainty?”
Driving in the dark
As participants at the STOA event heard, ‘driving in the dark’ hampers efforts to focus healthcare spending on treatments that can make a real difference, and avoid wasting limited resources on treatments that offer minimal or no benefit. Wim Goettsch, a health technology assessment specialist at the National Health Care Institute in the Netherlands, who spoke at the event, points out that cancer is a particular concern, as oncology drugs typically have the biggest impact on budgets, and need to show they deliver value for money. The issue of cost and value is becoming more acute because of the escalation in the number of treatments used in managing the disease. “We have focused in the past on single agents, but now there are more combinations and treatment lines, so they end up being more costly in use than you might expect,” he says. “We see expensive new treatments such as CAR-T being used in practice earlier than say the third line that it is supposed to be used at, and also such treatments are used with other costly procedures such as bone marrow transplants,” he adds. “And people can have treatments again when they relapse, so costs can be higher still. We need to look much more carefully at clinical practice as a result.” The key question is, what changes can realistically be made to give decision makers more direction on cost-effective practice. Previously, Cancer World has looked at the concept of real-world data – and how far it can be relied on to define the true benefit derived from treatments administered in clinical practice. There are a number of platforms in Europe and the US that are gathering such data, together with initiatives to improve data quality of cancer registries. There has also been progress in grading the value patients get from treatments, such as with the Magnitude of Clinical Benefit Scale developed by the European Society for Medical Oncology (ESMO). But the EORTC takes the view that the uncertainties are just too great to be solved with mining data. They argue for the need to ramp up so-called ‘pragmatic’ clinical trials ‒ trials designed to evaluate the effectiveness of interventions in real-life conditions of routine practice.The case for pragmatic trials
The idea of pragmatic trials is widespread in medicine, not just oncology. A simple definition is that they “are run in real-world settings, test interventions compared with usual care (rather than placebo), and are conducted in a way that seeks to enhance the generalisability of the results that they produce” (Haff N et al, JAMA Netw Open 2018). There are tools such as the Pragmatic Explanatory Continuum Indicator Summary 2 (PRECIS-2) that show whether a trial meets pragmatic ideals. But they can be hard to conduct and face challenges such as dropouts. In oncology, the emphasis on optimising treatment mainly concerns new agents in what is more broadly defined as applied clinical research (and in the context of personalised or precision treatments). Lacombe and colleagues put forward a lengthy discussion in a paper last year on the policy changes needed to create a continuum from basic biology to long-term population outcomes, in which an applied/pragmatic trial stage is a fundamental step, and not only for drugs but also for other oncology interventions (Lacombe D et al, Mol Oncol 2019).A framework for clinical development of new drugs

While much of the concern is about new agents there are examples of long-standing oncology practice that were eventually shown to be not effective and even harmfulAnother example was a strategy for managing advanced ovarian cancer with platinum-based drugs adopted in the late 1990s. Thanks to an independent validation trial published in 2017, oncologists now know that a protocol administered as a standard of care to many women did not extend overall survival, had significantly shorter progression-free survival and scored worse in quality of life. The role of such applied research extends widely in oncology, and not only to new agents, but the worry is that as latest treatments enter use they too may be found wanting after a long time.
Building consensus on the way forward
Since publishing the manifesto, the EORTC and STOA have engaged with stakeholders such as health technology agencies (HTAs), regulators, clinicians and patient advocates on how this could work. A survey by STOA asks questions such as:- How should such research be financed?
- Could it run in parallel with classical registrational trials, or only after marketing authorisation?
- How would regulatory agencies use the data?
The survey showed broad backing for regulatory measures to support treatment optimisationAsked for pluses and minuses, respondents mention, on the plus side, the use of clinically relevant outcome measures, cost savings, rewarding treatments that add clinical value, and more accurate prediction of real world side-effects. But there are questions about who will foot the bill, the lack of a framework for such studies, reluctance of clinicians and industry to take part, and potential ethical and legal issues. Three policy options for how treatment optimisation studies could fit within existing regulatory pathways are on the table:
- Making treatment optimisation studies part of the requirements that manufacturers have to satisfy to obtain a marketing authorisation
- Including such studies as part of industry’s post-authorisation commitments
- Using conditional reimbursement mechanisms to compel makers to carry out treatment optimisation studies.
Regulatory perspective
In March 2020, the European Medicines Agency (EMA) published its regulatory science strategy for the next five years. The document addresses many of the challenges that are raised in the EORTC manifesto and work of the STOA panel. Guido Rasi, the EMA’s executive director, accepts that cutting edge treatments such as CAR-T cell therapy raise fundamental questions about how they are assessed and valued. Speaking at the STOA event, Rasi mentioned the concept of ‘evidence by design’, recognising that new types of studies need to be planned, and requirements for post-licensing evidence generation specified, such as what data is collected by cancer registries. Rasi said he envisages a ‘rolling review’ of evidence revision, and essentially a new role for regulators ‘at the crossroads between science and healthcare systems’, acting as a ‘catalyst’ to enable translational research that fits into the reality of healthcare systems.Rasi envisages a ‘rolling review’ of evidence revision, and essentially a new role for regulators ‘at the crossroads between science and healthcare systems’The new strategy puts forward a lot of initiatives, and indicates a willingness to engage with the clinical optimisation agenda, but as yet has few hard facts. Among the promises are
- Developing a methodology to incorporate clinical care data sources in regulatory decision-making
- Providing guidance on the roles of patient preferences in therapeutic contexts and regulatory decisions
- Ensuring the evidence needed by HTAs and payers is incorporated early in drug development plans, including requirements for post-licensing evidence generation.
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