Evidence-based medicine at the IOZK

The fundamental goal of healthcare 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, explicit, and judicious use of current best evidence in making decisions about the care of individual patients" and integrates clinical experience and patient values with the best available scientific evidence (Sackett 1997).

The Oxford Centre for Evidence-Based Medicine has defined evidence classes. These are considered the standard for assessing the quality of the scientific evaluation of a particular clinical measure. 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 of costs (Jones 2015). For various reasons, this is a short-sighted approach that certainly does not align with the above definition of evidence-based medicine.

  • 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 (planning and conducting such studies takes years), this means that half of the patients are deprived of the potentially effective intervention. In the context of potentially fatal tumor diseases, this can lead to relevant ethical problems (Nardini 2014; Kyr 2021).
  • Conventional clinical studies yield average values for specific target parameters based on an evaluation of large cohorts. They can indicate statistical probabilities but cannot explain why a therapy is effective or ineffective in a particular situation. Accordingly, they do not allow any conclusions to be drawn about the prospects of success for individual patients. Significantly, however, these are of greatest interest to clinicians and of greatest benefit to patients (Sackett 1996; Ellis 2014).
  • Conventional clinical trials involve large populations and tend to increase their size in order to optimize the reliability of the results. On the other hand, modern biology divides cancer into increasingly smaller subgroups. Conventional approaches are therefore not suitable for evaluating therapies for diseases with an incidence of a few hundred patients per year, known as "rare diseases" (Deaton 2018).
  • The results of conventional clinical trials may not be generalizable, as they often exclude patients at higher risk of adverse effects (Jin 2015).
  • Conventional 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. Therefore, smaller, shorter, and more targeted approaches are needed (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. Since unpublished data cannot be included, it is not possible to make a balanced assessment of the overall clinical evidence (EUnetHTA, 2015).

With the aim of increasing treatment effectiveness, there is growing interest in tailored examinations and interventions that are better suited 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 EU Commission for Economy, Science, and Quality of Life are therefore calling for a review of the current clinical trial-based decision-making process. Among other things, they recommend that data not collected in randomized controlled trials and well-designed retrospective studies should be taken into account in future decision-making (FDA 2017; Couespel 2020). Such data, collected at the individual level, provides important evidence that can be used for healthcare decision-making, treatment improvement, or further development of concepts. This data, commonly referred to as real-world data (RWD), can be considered valid scientific data and therefore used to support regulatory measures (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 produce a good outcome, justifying reimbursement of the treatment by insurers (Marshall, 2006).

However, for some metastatic tumor types, standard of care oncology treatments are associated with a mortality rate of over 90 percent after two years, despite a large number of conventional studies (Stewart, 2013). Therefore, the current paradigm for designing clinical trials needs to be rethought. This is possible because we have entered a new era in which new insights are leading to new, more effective treatment options with higher success rates. These include options for advanced malignant diseases that improve health-related quality of life, are less toxic, are tailored to specific patient and disease characteristics, and are occasionally more cost-effective. The introduction of such new trial designs is slow but feasible. This requires innovation and so-called precision oncology to offer the right drug to the right patient at the right time (Subbiah 2018).

Evidence-based medicine at the IOZK

At the IOZK, we treat a wide range of rare, often advanced diseases with individualized multimodal immunotherapy. In addition, we report on our research findings ("real-world data") in retrospective studies. Publications originating from clinical work at the IOZK correspond to scientific evidence level 1c (case series) and, in view of the considerations outlined above, represent the highest level of evidence available for this type of disease and clinical intervention (Schirrmacher 2020).

At the IOZK, we are at the forefront of modern evidence-based medicine: providing robust evidence to support clinical decision-making and 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-1 Trials 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 Challenges: a Lancet Oncology Commission. Lancet Oncology, 2022; online November 15, available athttps://doi.org/10.1016/S1470-2045(22)00540-X

Marshall, JL. The Standard of Care in Oncology is Unacceptable. Oncology, 2006;20:No7. Available at 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 it is 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.