Evidence-based medicine at the IOZK

The fundamental aim of the healthcare system is to improve public health and provide better healthcare for individuals at a reasonable cost. The basis for this system is commonly referred to as "evidence-based medicine".

Evidence-based medicine is defined as "the conscientious, deliberate, careful and judicious use of modern best evidence in making decisions about the care of individual patients" and integrates patients' clinical experience and values with the best available scientific evidence (Sackett 1997).

The Oxford Center for Evidence-Based Medicine has defined evidence classes. These are used as a standard for assessing the quality of the scientific evaluation of a particular clinical intervention. The levels range from 5 (based on expert opinion or basic research) to 1 (randomized clinical trials, RCT) (Centre for Evidence-Based Medicine 2009).

Decision-makers tend to accept only Level 1 evidence (randomized clinical trials) for setting standards of care and the associated reimbursement or coverage (Jones 2015). For a variety of reasons, this is a short-sighted approach that is certainly not consistent with the definition of evidence-based medicine cited above.

  • Conventional study designs test hypotheses by comparing an experimental group (e.g. therapeutic intervention) with a control group (no intervention, placebo). Apart from the financial and logistical implications (it takes years to plan and conduct such studies), this means that half of the patients are deprived of the potentially effective intervention. With regard to potentially fatal tumor diseases, this can lead to relevant ethical problems (Nardini 2014; Kyr 2021).
  • Conventional clinical studies produce average values for certain target parameters on the basis of an evaluation of large cohorts. They can indicate statistical probabilities but cannot clarify why a therapy is effective or ineffective in a particular situation. Accordingly, they do not allow any statement to be made about the prospects of success for the individual patient. Significantly, however, they are of the greatest interest to clinicians and of the greatest benefit to patients (Sackett 1996; Ellis 2014).
  • Conventional clinical trials are based on large populations and tend to enlarge them in order to optimize the reliability of the results. On the other hand, modern biology divides cancer into smaller and smaller subgroups. Conventional approaches are therefore not suitable for evaluating therapies for diseases with an incidence of a few hundred patients per year, so-called "rare diseases" (Deaton 2018).
  • The results of conventional clinical trials may not be generalizable as they often exclude patients with a higher risk of adverse effects (Jin 2015).
  • Traditional clinical trials cannot keep pace with the rapid advances in biology and the rapid development of innovative therapies, including immunotherapy, due to their long duration. Smaller, shorter and more targeted approaches are therefore required (Rodon, 2015; Catani, 2017).
  • To ensure evidence-based medicine, all data should be available, both published and unpublished. In studies funded by pharmaceutical companies, adverse results may not be published. As unpublished data cannot be included, a balanced assessment of all clinical evidence is not possible (EUnetHTA, 2015).

With the aim of increasing treatment effects, there is growing interest in customized studies and interventions that are better tailored to individual needs (Schork 2015; Kyr 2020; Lawler 2022). Leading authorities such as the U.S. Department of Health and Human Services - Food and Drug Administration (U.S. FDA, responsible for all clinical trial approvals in the U.S.) and the European Commission for Economy, Science and Quality of Life, are therefore calling for a review of the current process of decision-making based on clinical trials. Among other things, they recommend that data not collected in randomized controlled trials and in well-designed retrospective studies should be considered in future decision-making (FDA 2017; Couespel 2020). Such data collected at the individual level provide important evidence that can be used to inform healthcare decision-making, improve treatment or refine approaches. This data, commonly referred to as real-world data (RWD), can be considered valid scientific data and therefore used to support regulatory action (Ismail, 2022).

Innovation beyond the standard of care

Originally, the term "standard of care" was used to define a minimum level of care that was considered acceptable without committing malpractice. Over time, the term has evolved to mean "appropriate" and best care, a level of care that balances risk and benefit, outcomes and costs or legal risks, and is based on scientific data. As such, it has become the gold standard for treatments that are likely to result in a good outcome, justifying reimbursement of the treatment by insurers (Marshall, 2006).

However, for some metastatic tumor types, oncology treatments that meet the "standard of care" are associated with a mortality rate of over 90 percent at two years, despite a large number of conventional trials (Stewart, 2013). Therefore, the current paradigm for designing clinical trials needs to be reconsidered. This is possible because we have entered a new era where new evidence is leading to new, more effective treatment options with higher success rates. This includes options for advanced malignancies that improve health-related quality of life, are less toxic, are tailored to specific patient and disease characteristics and are sometimes less expensive. The introduction of such new trial concepts is slow, but feasible. This requires innovation and so-called precision oncology to provide the right drug for the right patient at the right time (Subbiah 2018).

Evidence-based medicine at the IOZK

At the IOZK, we treat a large number of rare, often advanced diseases with individualized multimodal immunotherapy. In addition, we report on our research results in retrospective studies ("real world data"). Publications that originate from clinical work at the IOZK correspond to scientific evidence level 1c (case series) and represent the highest level of evidence available for these types of diseases and clinical interventions in view of the considerations outlined above (Schirrmacher 2020).

At the IOZK, we are at the forefront of modern evidence-based medicine: robust evidence to support clinical decision-making to answer clinically relevant questions.

You can find our publications at: https://www.iozk.de/iozk-publikationen/

 

References

Catani, JPP, Riechelmann, RP, Adjemian, S, et al. Near Future of Tumor Immunology: Anticipating Resistance Mechanisms to Immunotherapies, a Big Challenge for Clinical Trials. Human Vaccines & Immunotherapeutics, 2017;13:1109-1111.

Centre for Evidence-Based Medicine. Oxford Centre for Evidence-Based Medicine: Levels of Evidence. University of Oxford, 2009. Available at https://www.cebm.ox.ac.uk/resources/levels-of-evidence/oxford-centre-for-evidence-based-medicine-levels-of-evidence-march-2009.

Couespel, N, Price, R. Strengthening Europe in the Fight Against Cancer - Going Further, Faster. European Parliament's Committee on the Environment, Public Health and Food Safety, 2020. Available at http://www.europarl.europa.eu/supporting-analyses.

Deaton, A, Cartwright, N. Understanding and Misunderstanding Randomized Controlled Trials. Social Science & Medicine, 2018;210:2-21.

Ellis, LM, Bernstein, DS, Voest, EE, et al. American Society of Clinical Oncology Perspective: Raising the Bar for Clinical Trials by Defining Clinically Meaningful Outcomes. Journal of Clinical Oncology, 2014; 32:1277-1283.

EUnetHTA JA2 Authoring Team. Levels of Evidence - Applicability of Evidence for the Context of a Relative Effectiveness Assessment. Guidance Document. Diemen (NED): EUnetHTA; 2015. Available at https://www.eunethta.eu/

Food and Drug Administration (FDA). Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices. Guidance Document. FDA, 2017. available at http://www.fda.gov/BiologicsBloodVaccines/GuidanceComplianceRegulatoryInformation/Guidances/default.htm.

Ismail RK, Real-World Data in Cancer Treatment. Bridging the Gap between Trials and Clinical Practice. Utrecht, 2022: Available at https://www.globalacademicpress.com/ebooks/rawa_ismail/.

Jin, S, Pazdur, R, Sridhara R. Re-evaluating Eligibility Criteria for Oncology Clinical Trials; Analysis of Investigational New Drug Applications in 2015. Journal of Clinical Oncology, 2017;35:3745-3752.

Jones DS, Podolsky, SH. The History and Fate of the Gold Standard. Lancet 2015;385:1502-1503.

Kyr, M, Klement, GL, Zdrazilova-Dubska L, et al. Editorial: Precision/Personalized Pediatric Oncology and Immune Therapies: Rather Customize than Randomize. Frontiers in Oncology, 2020;10:377.

Kyr, M, Svobodnik, A, Stepanova, R, et al. N-of-1Trials in Pediatric Oncology: From a Population-Based Approach to Personalized Medicine-A Review. Cancers, 2021, 13, 5428.

Lawler, M, Davies, L, Oberst, S, et al. European Groundshot - Addressing Europe's Cancer Research Cahllenges: a Lancet Oncology Commission. Lancet Oncology, 2022; online November 15, Retrieved fromhttps://doi.org/10.1016/S1470-2045(22)00540-X

Marshall, JL. The Standard of Care in Oncology is Unacceptable. Oncology, 2006;20:No7. Retrieved from https://www.cancernetwork.com/journals/oncology/oncology-vol-20-no-7.

Nardini, C. The Ethics of Clinical Trials. eCancer, 2014;8:387.

Rodon, J, Soria, JC, Berger, R, et al. Challenges in Initiating and Conducting Personalized Cancer Therapy Trials: Perspectives from WINTHER, a Worldwide Innovative Network (WIN) Consortium Trial. Annals in Oncology, 2015;26:1791-1798.

Sackett, DL, Rosenberg, WM, Gray JA, et al. Evidence-Based Medicine: What is it and What it isn't. British Medical Journal, 1996;312,71-72.

Sackett, DL, Evidence-based Medicine. Seminars in Perinatology, 1997;21:3-5.

Schirrmacher, V, Sprenger T, Stücker, W, et al. Evidence-Based Medicine in Oncology: Commercial versus Patient Benefit. Biomedicines, 2020;8:237-253.

Schork, N.J. Personalized Medicine: Time for One-Person Trials. Nature, 2015;520:609-611.

Stewart DJ, Kurzrock R. Fool's Gold, Lost Treasures, and the Randomized Clinical Trial. BMC Cancer. 2013;13:193

Subbiah, V, Kurzrock, R. Challenging Standard-of-Care Paradigms in the Precision Oncology Era. Trends in Cancer, 2018;4:101-109.