Evidence Based Medicine
The fundamental aim of healthcare is to provide better health for the population, better healthcare for individuals, and at affordable cost. The foundation for this system is largely referred to as „Evidence Based Medicine “.
Evidence Based Medicine is defined as the „conscientious, explicit, judicious and reasonable use of modern, best evidence in making decisions about the care of individual patients “, and integrates clinical experience and patient values with the best available research information (Sackett, 1997).
The Oxford Centre for Evidence-Based Medicine has defined Levels of Evidence. These are regarded as standard to assess the quality of scientific evaluation for any given clinical intervention. The levels range from 5 (expert opinion without critical appraisal, or based on physiology, bench research or „first principles “) to 1 (randomized clinical trials, RCT) (Centre for Evidence-Based Medicine, 2009).
Policy makers tend to only accept level 1 evidence (randomized clinical trials) for decision-making on standards of care, and subsequent reimbursements or coverage of costs (Jones, 2015). For different reasons, this is a short-sighted view, and surely not in line with the definition of evidence-based medicine cited above.
- Traditional clinical trial designs focus on hypothesis testing by comparing an experimental arm (e.g., therapeutic intervention) to a control arm (no intervention, placebo). Aside the financial and logistical complications (such trials take years to design and run), it implies that half of the patients do not receive the possibly beneficial tested intervention. In the context of possibly fatal tumors this is a pertinent ethical concern (Nardini, 2014; Kyr, 2021).
- Traditional clinical trials produce averaged results based on large cohorts for a given outcome variable. They state a statistical probability but do not answer questions related to why therapies work in some situations and not in others. Thus, they can never provide information about the outcome referring to a particular patient. Ironically, these questions are of most interest to clinicians and of most benefit to patients (Sackett, 1996; Ellis, 2014).
- Traditional clinical trials focus on large populations, with a tendency to get larger in order to optimise the reliability of the results. On the flip side, modern biology is slicing and dicing cancer into ever smaller subsets. So, traditional approaches by default are not designed to solve questions to evaluate therapies for diseases with an incidence of a few hundred patients per year, so-called „rare diseases“ (Deaton, 2018).
- Results of traditional clinical trials may not be generalizable as they tend to exclude patients at higher risk of adverse effects (Jin, 2015).
- Conventional clinical trials cannot keep up with the rapid advances in biology and the rate at which innovative therapies – including immunotherapy – are being developed, because of their long duration. This calls for smaller, shorter, and more focused approaches (Rodon, 2015; Catani, 2017).
- To be able to support evidence-based medicine, all evidence should be available, both published and non-published. In trials funded by pharmaceutical groups disadvantageous results may not be published. Not being able to assess unpublished data does not allow for a balanced assessment of all clinical evidence (EUnetHTA, 2015).
With the objective of increasing treatment effects, there is steadily growing interest in tailoring assessments and interventions to better match individual needs (Schork, 2015; Kyr, 2020; Lawler, 2022). Lead authorities such as the U.S. Department of Health and Human Services – Food and Drug Administration (U.S. FDA, responsible for all approvals of clinical studies in the US) and the EU Policy Department for Economic, Scientific and Quality of Life Policies, therefore call for a review of the current decision-making process on the basis of clinical trials. They recommend – amongst others – that data collected in a non-RCT setting and in well-designed retrospective studies should be considered in future decision making (FDA, 2017; Couespel, 2020). Such data collected at an individual level provide critical evidence that can be used to inform health care decisions, improve treatment, or refine theories. Commonly referred to as real-world data (RWD), such data may constitute valid scientific evidence, and therefore can be used to support regulatory decisions (Ismail, 2022).
Innovation beyond the Standard of Care
The original intent of the term „Standard of Care“ was to define a minimum level of care, considered acceptable and without committing malpractice. Over time, the term has evolved to be considered the „appropriate“ and best care, a level of care that balances risk and benefit, outcomes and costs or legal risks, and that is based on scientific evidence. As such, it became the gold standard for treatments that will likely have a good outcome, rendering the justification for reimbursement of treatment by insurers (Marshall, 2006).
Yet, for some metastatic cancers the oncology treatments meeting the „Standard of Care“ are associated with over 90 percent mortality at two years, despite a multitude of traditional trials (Stewart, 2013). So, the current clinical trial design paradigm needs to be revisited. This is possible as we have entered into a new era, with new insights leading to new, more effective treatment options, with higher success rates. Including opportunities for advanced malignancies, that improve health-related quality of life, that are less toxic, that are tailored to specific patient and disease characteristics, and that are occasionally less expensive. The introduction of such new study concepts is progressing slowly, but it is feasible. This calls for innovation and so-called precision-oncology „to offer the right drug for the right patient at the right time“ (Subbiah, 2018).
Evidence Based Medicine at the IOZK
At the IOZK, we treat multiple rare, often advanced, diseases in a personalized way by means of individualized multimodal immunotherapy. In addition, we engage in reporting our findings (real world data) through retrospective studies. Publications, derived from the clinical work at the IOZK, match level 1c scientific evidence (case series), and given the reflections made above, are the highest level of evidence available for this type of disease and clinical intervention (Schirrmacher, 2020).
So, at IOZK we are at the forefront of modern Evidence Based Medicine: strong evidence in support of clinical decision making to answer clinically relevant questions.
You find our publication record under: https://www.iozk.de/iozk-publikationen/
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 from 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 from 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 from 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 from 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 from 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, https://doi.org/10.1016/S1470-2045(22)00540-X
Marshall, JL. The Standard of Care in Oncology is Unacceptable. Oncology, 2006;20:No7. Available 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.