What is Evidence-Based Medicine in the Context of the Human Network?

Wikipedia’s definition: “Evidence-based medicine is an approach to medical practice intended to optimize decision-making by emphasizing the use of evidence from well-designed and well-conducted research.”

An article in the Journal of the Academy of Medical Sciences of Bosnia and Herzegovina has this definition: “Evidence based medicine is the conscientious, explicit, judicious and reasonable use of current best evidence in making decisions about the care of individual patients.”[1]

Mosby’s Medical Dictionary defines evidence-based medicine as “the practice of medicine in which the physician finds, assesses, and implements methods of diagnosis and treatment on the basis of the ‘best available’ current research, the physician’s clinical expertise and the needs and preferences of the patient.”

The website for www.Students4BestEvidence.net states: “The concept is about making sure that when decisions are made they are made on the basis of the most up-to-date, solid, reliable, scientific evidence. In the case of medicine or health care, these are the decisions about the care of individual patients.”

MedicineNet.com: “The judicious use of the best current available scientific research in making decisions about the care of patients. Evidence-based medicine (EBM) is intended to integrate clinical expertise with the research evidence and patient values.”

Journal of Athletic Training 2004: “Evidence-based medical practice has 5 components: defining a clinically relevant question, searching for the best evidence, appraising the quality of the evidence, applying the evidence to clinical practice, and evaluating the process. Evidence-based medicine integrates the research evidence, clinician's expertise, and patient's preferences to guide clinical decision making.”

Jeffrey Bland just published an article in the Journal of Integrative Medicine that turns these definitions on their heads.[2] He does so not because the concept is invalid – of course we want to gather the best possible evidence on which to base our decisions for patient care – but because the very foundation of the modern definition of evidence based medicine rests on the concept of the randomized placebo-controlled trial.

He states that “The randomized placebo-controlled trial (RCT) has achieved iconic status in the field of medical research.” The RCT has for decades represented the gold standard in the field of both scientific and medical research. However, even within the scientific community there are dissenting voices.[3]

Dr. Bland also states that the “randomized clinical trials” can be very beneficial when comparing the effect of one drug with another, or one surgical procedure with another, in a population of people with identical disease and identical genetics and lifestyle. However, the RCT is less than informative when we are faced with an individual with specific disease expression, specific genetics, specific lifestyle and specific toxic exposures.

In the article Dr. Bland affirms that “…the common diseases [that pharmaceutical] medications are designed to treat— depression, cardiovascular disease, inflammation, inflammatory bowel disease, Crohn’s disease, rheumatoid arthritis, esophageal reflux disorder, psoriasis, asthma, and schizophrenia—all have multiple triggering factors derived from the unique way that a person’s genes interact with lifestyle, diet, and environment.”

The concept of the “randomized controlled trial” has been used to compel the practice of “standard of care” medicine for many years. The problem with the whole concept is three-fold:

• randomization does not equalize everything other than the treatment in the treatment and control groups,
• it does not automatically deliver a precise estimate of the average treatment effect (ATE),
• and it does not relieve us of the need to think about (observed or unobserved) covariates.[4]

N-of-1 studies[5], by contrast, are designed to discover how an individual patient responds to a given therapy. Responses may be categorized as “positive”, “no response”, “negative” i.e. bad response, or “maybe”. If a patient has a good positive response, that may signal the end of the trial, and eventually reduce the cost of the clinical trials.

Nicholas Schork’s articles on evidence-based medicine stand out as bright lights in a grey sea of conformity.^{2, [6]} He states: “in biomedical and clinical practice settings, the contemporary concept of ‘personalized’ medicine (otherwise known as ‘individualized’ or ‘precision’ medicine) – in which interventions are tailored to patients based on those patients’ unique molecular, physiologic, environmental and behavioral profile(1, 2) – is in many ways antithetical to the suggestion that statistically significant differences in the average responses of others to an intervention relative to average responses to a comparator intervention is enough to compel the use of that drug in all patients going forward.”

No wonder the pharmaceutical companies are concerned – their income depends on large numbers of people using their particular drug for a broad variety of indications.

As Dr. Stark puts it: “The alternative to RCTs for advancing personalized medicine to be discussed is rooted in the concept of a data-based ‘learning system.’”

Dr. Schork describes the concept of “basket trials” for cancer therapy. In the usual RCT trial, the therapy being tested is given to a number of people with similar cancer diagnoses – e.g. colon cancer, or pancreatic cancer – and the drugs are chosen to determine which works better on that particular type of tumor. In a “basket trial” the therapy is based on a patient’s tumor genetics (e.g. pathogenic mutations). The patients are assigned to a “basket” of drugs known to affect those particular mutations. The control patients would then be given the “standard of care” drugs for their particular tumor type, and comparisons of outcome could be drawn, without violating ethical principles.

Dr. Bland states: “A foundational tenet that underlies network medicine is the recognition that conditions identified as “comorbidities” or “disease adjacencies” may actually be functional perturbations of the same underlying biological network expressed in different cells, tissues, or organs.” The concept of “network” so essential to those of us who practice functional and integrative medicine, is absent from the RCT school of thought which states that valid evidence may be obtained from using one modality of treatment (whether it be a drug, a vitamin or a psychologic factor) without regard to any other variable (e.g. diet, genetics, lifestyle) in a complex system (e.g. a human being).

We are a network. We and our microbiome form a single organism comprised of trillions of cells and individual entities (viruses, bacteria, fungi) that live symbiotically with us. How can changing a single variable in a system which is designed to stay in balance no matter what the perturbations possibly give us valid information about what that variable does in a population? The concept is antithetical to reason – unless that single variable is something like a bomb which overwhelms the system entirely.