Chapter 4

Evidence-Based Medicine and Ayurveda

Abstract

This chapter reviews the nature and application of evidence as a basis of practice for various systems of medicine. It describes the natural history of diseases, and the evolution of therapeutic intervention from intuitive practices to scientific, evidence-based medicine (EBM). The authors refer to major initiatives like Cochrane Collaboration, which contributed to the emergence of EBM. Every system, including CAM, needs an evidence base. Ayurveda, Yoga, and T&CM have an experiential evidence base, which by its nature is different from mere experimental base. Placebo response and other confounders are also discussed as issues related to bias and quality of evidence. The authors differentiate epistemologies of modern medicine, Ayurveda, and Yoga in order to address issues related to the value of clinical observations, randomized controlled trials, systematic reviews, and systematic analysis of published studies in the process of EBM. Finally, the authors try to configure a construct of evidence-based, integrative medicine for the future.

Keywords

Bias; Cause and effect; Evidence; Evidence-based health; Evidence-based medicine; Levels of evidence; Placebo; Randomized trials; Rationale

The absence of evidence is not the evidence of absence.

Carl Sagan, Cosmos

What Is Evidence?

Before addressing various aspects of evidence-based medicine (EBM), it is important to discuss the meaning of evidence. In his famous book The Idea of History, R.G. Collingwood rightly states “when we try to define evidence, we find it very difficult.” Evidence by definition is “the available body of facts or information indicating whether a belief or proposition is true or valid.” Scientific evidence relies on observations, and well-planned, controlled, and reproducible experimental results to support, refute, or modify a hypothesis or theory. In philosophy, evidence is closely tied to epistemology. In a way, evidence is proof. Methods of obtaining proof are connected to the nature of knowledge. Thus, scientific evidence is just one of the many forms of evidence, such as anecdotal evidence, intuition, personal experience, and testimonial cases.
Thus, the meaning of evidence is not straightforward. Evidentialism is a theory which mandates justification based on evidence. Evidence comes from repeatable and reproducible sets of observations, measurements, and reasoning. Obviously, the capacity to observe and measure, as well as the ways and means of reasoning, have a direct influence on the nature, quality, and reliability of evidence. Therefore, as scientific knowledge advances, and our understanding deepens, the acceptability of evidence also changes. This is how many notions or beliefs have been proved to be wrong in history. For example, a notion that all organisms were designed by an intelligent creator or God—known as design hypothesis—was shunned after the Darwinian hypothesis was scientifically accepted. Now, Darwin’s theory of biological evolution and the diversification of life is being challenged by new theories like biocentrism, which hypothesizes that life, and consciousness, are the keys to understanding the true nature of the universe.
Thus, as our knowledge expands, the nature of evidence also changes. Because science is dynamic, scientific evidence cannot be a static entity. Science only states that based on whatever is known, accepted, and reproducible at a given point of time, certain hypothesis, theories, observations, interpretations, analysis, or outcomes have a sufficient evidence base. The expectations and nature of evidence in jurisprudence may be different from those required for clinical practice.
Earlier in our discussion of the evolution of medicine, we went over how faith-dominant, primitive, shamanic treatments transmuted into scientific, modern medicine. The nature of diseases became better known with the development of etiopathology, and an understanding of the underlying biological processes. As a result, therapies also became more precise, dependable, rational, and scientific.
During the past century there was consistent progress in biomedical research. We have seen how several discoveries in medicine and surgery affected the quality of human life for the better. To keep pace of advancements in scientific research, and technological developments, medical education also underwent a huge transformation. Medical education had to move from mere bedside observations to laboratory-based investigations in order to bridge the gap between biomedical research and clinical practice. The transformation of the medical profession from one of clinical practitioners, to physician–scientists required a strong research base, and the experience of medical practice.
In 1910, the American physician and educationist, Abraham Flexner, published a landmark report that revolutionized medical education in the United States and propelled the rapid growth of biomedical research and development. Flexner’s report recommended the intensification of biomedical research and the development of a new cadre of medical professionals who were physician–scientists. Thus, excellent clinicians were exposed to systematic research, documentation, analysis, and applications. One of the positive impacts of this change in the medical education system is the substantial increase in the number of scientific publications in the field of modern medicine. For instance, in a scintometric analysis of the term medicine in Google Scholar, we get 4,810,000 hits, indicating the number of scientific, peer-reviewed papers, citations, and patents. These results refer to scientific publications or patents related to medicine. In the 100   years from 1810 to 1910, there were hardly 40,600 papers. From 1910 to 1950, there were 184,000 papers; from 1950 to 1970, there were 208,000 papers; from 1970 to 2000, there were 328,000 papers related to medicine; and from 2000 to 2013—just 13   years—there are 416,000 papers. The number of papers related to medicine from 2000 to 2013 is almost 10 times more than the total number of papers in the first 100   years [1] (Figure 4.1). While we grant some degree of overlap, and exclusion errors in the Google search engine, the sharp increase in the volume of scientific literature is very clear. Due to the impetus of advances in science, technology, research, and development there is an information overload of quality, scientific literature. On the one hand, this offers an unprecedented opportunity to update knowledge, and to improve the quality and precision of medicine; on the other, it can create a threat of a selective, biased, or vested interest-driven use of information. Therefore, for the best practice in medicine to be achieved, it is important to critically analyze the scientific information used in decision making.
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Figure 4.1 Sharp rise in scientific publications.
Earlier, medical practice was mainly based on clinical acumen, and not necessarily on available, and critically analyzed scientific evidence. The cause and effect relationships were known and practiced even before the emergence of EBM. However, there was no uniform system where available information could be scientifically analyzed, and used as a basis for clinical decision making. It is hard to believe that today’s gold standard method of randomized controlled trials (RCTs) was not on the horizon until the 1960s. It is surprising and satisfying to witness the fast paradigm shift in the practice of modern medicine, which was powered by the pace of research and technological advances. Many new concepts evolved, new hypothesis replaced old ones, and modern medicine began building a good scientific base. This was probably the beginning of the transformation of EBM from mere experience-based medicine. Interestingly, both terms have the acronym EBM; in this chapter we will use EBM to denote evidence-based medicine.
Medicine is ever evolving, both in its scope and methodology of application. For instance, in the pre-EBM era, the diagnosis of malaria was based on the symptomatology such as fever with rigors, body pain, and profuse sweating on remission of periodic fever. In addition, an experienced physician’s acumen, which allowed the clinician to feel the soft, enlarged tip of the spleen, was put to use in distinguishing malaria from other fevers. This diagnostic method was as valid as EBM practice. Later the actual identity of the malarial parasite in a blood film was used as confirmatory criteria. So in a way, the concept of EBM was not new. However, the new EBM has brought robust analysis of available scientific information through systematic reviews, meta-analysis, protocols, and systematic processes.

Cause and Effect Relationships
The quality and reliability of evidence depends on several factors. Systematic reviews and meta-analyses are valuable tools in evidence hierarchy. Today, scientists and professionals have to deal with information overload. In such a situation, systematic reviews come in handy for analysis, and in empowering rational decision making. Systematic reviews indicate if scientific findings are reliable and consistent, and if the outcomes can be generalized or if they differ according to subsets. In the decision-making process, meta-analyses add further value by identifying bias, increasing the power and precision of analysis, identifying possible risks, and improving the reliability and accuracy of conclusions [4]. Therefore, in evidence gathering, appropriate approaches and methods should be used, in accordance with the type of disease, and the nature of the ill patient. Against this background, the validity of clinical observations, case reports, and case studies might have limited value, because data of carefully monitored control groups is not available.
Renowned British epidemiologist and statistician, Sir Austin Bradford Hill, in a president’s address of the Royal Society of Medicine meeting on January 14, 1965, presented a detailed argument about the cause and effect hypothesis. He dwelt upon relationships between the observed association and a verdict of causation. He elaborated nine key aspects in relation to association and the most likely interpretation of its causation. These include strength, consistency, specificity, temporal relationship, biological gradient, plausibility, coherence, experimental evidence, and analogy. Thus, experimental evidence is just one of the nine key factors.
No formal statistical tests of significance can answer questions regarding association and causation. Such tests can indicate the chance of specific effects and its likely magnitude but cannot contribute to the proof of hypothesis. Tests of significance are valuable tools, but in many situations they are unnecessary because the difference might be clear and obvious, it is negligible, or it may not have any practical importance. When the experimental results need to be compared with standards, placebos, or other variables, statistical hypothesis tests are of great value. Statistics is the study of the collection, organization, analysis, interpretation, and presentation of data. It also deals with methods of data collection, sampling size, and confounding factors in the design of surveys and experiments. It offers probability, confidence limits, and levels of significance. By qualifying the result as statistically significant, statistical analysis rules out the possibility of any unlikely result as having occurred by chance. Statistical analysis is made according to a predetermined threshold of probability, and a certain significance level. Many such tests are used to prove or disprove the null hypothesis in reaching a logical and rational conclusion. The importance of statistical methods in the analysis of scientific data is certainly important. The p value and other tests of statistical significance, like t and x 2 tests, are extremely useful in scientific research. However, the nature of statistical hypotheses testing in clinical research has been questioned. A recent article published in Nature examines how p values cannot be always considered the gold standard of reliable measures of statistical analysis. A decision-making frame has been proposed for addressing this critique, and also for transcending ideological debates on probability [5].
We must remember that all observational or experimental scientific work is incomplete. It is always a work in progress. It can change with the advancement of knowledge. However, we cannot ignore the value of existing knowledge in today’s decision making. Thus, clinical judgment is a complex process, and has a lot of overlap with subjective and objective variables. The experience, knowledge, and acumen of the clinician drive the clinical judgment. There exists the possibility of bias, and the influence of other confounding factors. Therefore, there exists a need to bring more rationality, objectivity, and scientific support to strengthen clinical judgment.
The foundation of today’s EBM was laid in 1967 by the American physician and mathematician, Dr Alvan R. Feinstein, in his groundbreaking work, Clinical Judgment. Dr Archie Cochrane drew the attention of the scientific and medical communities to the collective ignorance of the effects of health care in his landmark publication of 1972, Effectiveness and Efficiency: Random Reflections on Health [6]. Dr Cochrane was a strong proponent of RCTs, and noted the need for a critical summary of RCTs. This became the foundation for systematic review, and meta-analysis. In honor of his contributions, The Cochrane Foundation was established.
Today, The Cochrane Collaboration is an international network of more than 2,800,000 dedicated people from over 100 countries. The Cochrane Foundation helps clinicians, physician–scientists, health care providers, policy makers, and patients to make well-informed decisions using state-of-the-art Cochrane reviews. Today, over 5000 such reviews have been published online and are available in the Cochrane Library. Such efforts played a major role in empowering physicians, clinicians, and researchers in informed decision making [7].
In 1985, The Cochrane Collaboration published the first classified bibliography of 3500 reports of controlled trials in perinatal medicine published between 1940 and 1984. In 1985, meta-analysis started gaining increasing acceptance as a method of summarizing the results of a number of randomized trials affecting the setting of treatment policy [8]. This led to a very powerful research and analysis tool in the form of systematic reviews, which were aggressively promoted, supported, and practiced by the Cochrane Collaboration. Even today, systematic reviews and meta-analyses are considered to be reliable and valuable evidence in guiding and supporting clinical practice.

Accessing Evidence

Significant contributions from many physician–scientists reinforced the importance of scientific evidence in clinical diagnosis and therapeutics. As a result, during the late 1980s and the early 1990s, McMaster University in Hamilton, Canada, formed a working group on EBM. This group proposed a new approach, mechanism, and process to bring more rational and analytical evidence for a research-based and research-backed practice of medicine [9]. The EBM process is described as an ability to assess the validity and importance of evidence before applying it to day-to-day clinical problems [10]. The scope of EBM was later expanded to include many professions allied to health and social care. Recently, The Journal of The American Medical Association (JAMA), together with McGraw-Hill Global Education, launched the initiative, JAMA Evidence. This online education portal provides access to the latest information, books, tools, and other resources for the study of EBM in the context of improving health care (http://jamaevidence.com).
EBM is a complex process; in general, there are five steps.
1. Critical questioning, study design, and levels of evidence
2. Systematic retrieval of the best evidence available
3. Critical appraisal of evidence for internal validity
4. Evidence-informed decisions, and practice
5. Continuous evaluation of practices
Assessment of internal validity involves studying systematic errors of selection bias, information bias, and confounding factors; quantitative aspects of diagnosis and treatment; the effect size, and precision; clinical importance of results; and external validity or generalizability in clinical practice. Evidence generation is not the ultimate goal of EBM. Evidence is a tool to upgrade practice and improve health indicators of society. Evidence can never remain static. It changes according to available data, practices, patients’ preferences, and circumstances. Like pharmacovigilance, evidence is also a continuous process of studying ongoing practices, and modifying them based on unbiased decisions. Thus, reducing bias, improving quality of research, disseminating evidence, and facilitating better decision making are processes included in EBM.
In previous times, medical practice was mainly based on observations from clinical experience, the value of diagnostic tests, and the efficacy of treatment. It also involved the study and understanding of the basic mechanisms of disease and pathophysiologic principles as a guide for clinical practice. Later, critically analyzed scientific information from preclinical and clinical studies—especially RCTs—received increased importance as body of evidence. Still, it was believed that a combination of rigorous medical training and experiential clinical acumen would be sufficient to evaluate new tests and treatments. It was also believed that content expertise and clinical experience are sufficient for good clinical practice. Clinicians used to have a number of options for addressing clinical situations. They could use their own experience, understanding of pathophysiology, clinical acumen, and judgment, or refer to textbooks and consult peer experts to decide the best course of clinical diagnosis and treatment. However, many scientists were not satisfied with this system; it was based on personal experiences, expertise, judgments, and opinions of physicians, and so it was prone to biases and errors. Scientists wanted to raise the bar of the evidence base so that it could be used in a systematic fashion, for more accurate and reliable prognosis, diagnosis, prevention, and treatment as part of clinical decision making.

Quality and Levels of Evidence
EBM categorizes different types of clinical evidence, and grades them according to the strength and quality of the evidence. The strongest evidence for therapeutic interventions is provided by the systematic review of randomized, triple-blind, placebo-controlled trials. Patient testimonials, case reports, and even expert opinions are not considered as strong evidence, because of the placebo effect and inherent biases. Most agencies, including the United Kingdom’s National Health Service (NHS), and the United States Preventive Services Task Force categorize evidence in four grades or levels. These levels are weighted; properly designed, RCTs have highest value. This is followed sequentially by nonrandomized controlled trials; well-designed cohort, case-control, multicentric studies; and multiple time series. The lowest weight is given to the opinions of authorities, clinical experience, descriptive studies, laboratory studies, and reports of expert committees. Depending on the strength of the evidence, and the balance between benefits and risks, evidence is categorized as good or fair. Any kind of conflicting evidence, where the risk-to-benefit balance cannot be assessed, is considered as insufficient, or poor-quality evidence. In 2000, an informal collaboration of people with an interest in reviewing health care grading systems formed a working group. This initiative is now known as the Grading of Recommendations Assessment, Development and Evaluation (GRADE) working group [11] (www.gradeworkinggroup.org). There are four general levels of quality of evidence according to GRADE guidelines: high, moderate, low, and very low quality of evidence.
Indeed, it is very difficult to reach correct judgments about the quality and reliability of evidence. Making any recommendations based on the evidence is not easy, because such a recommendation depends on several factors, many choices, and situation-specific outcome expectations. For instance, several categories of drugs like β-blockers, calcium channel blockers, diuretics, angiotensin-converting enzyme inhibitors, and angiotensin receptor blockers are available to treat hypertension. The right choice in specific situations will depend on the nature of the supporting evidence. While systematic reviews provide essential evidence, they may not have sufficient information for well-informed decisions. Different reviewers might have different conclusions, and different experts might have different interpretations. The GRADE working group has developed a software application to assess the overall quality of evidence in the facilitation of systematic decision making.
The EBM process, supported by initiatives like GRADE, has provided systematic, critical, consolidated, authoritative, unbiased, statistically significant, and reproducible scientific evidence. This helps to get distilled knowledge that can be uniformly applied in clinical practice. However, experts have also warned that best available evidence should not be regarded as a mere collection of data, which might be suitable evidence. The authoritative aura attached to the collection of information may lead to abuses or rigidity in clinical practice [12].

EBM in Practice

The practice of medicine is more than merely following theoretical guidelines arising out of EBM. First, the physician has to keep in mind the basic principle of medicine: do no harm. Second, he has to observe the nature of the patient and keep track of the patient’s response to treatment. Based on these minute, day-to-day observations, subjectively derived from the patients’ histories, and objectively seen from clinical examination, the physician has to do midterm corrections during the course of the illness. That is why it is important to realize that while EBM provides a general framework to guide the modern physician’s clinical practice, there is more to it—the practice of medicine is an art and science. Our current approach to EBM does not sufficiently take onboard this reality. As a result, if one critically looks at actual clinical practice, it would be quite daring to say that it is evidence based. Today, clinicians follow cause and effect relationships in terms of symptoms of a disease or syndrome. However, in a mechanical process, they tend to ignore the patient who is suffering. For example, for a patient with suspected metabolic syndrome, the prescription invariably contains a combination of drugs for hypertension, hypercholesterolemia, obesity, and diabetes. Under the pretext of preventive cardiology, the patient is likely to get drugs like aspirin, β-blockers, statins, and angiotensin-converting enzyme inhibitor. Now, cocktail polypills are available. Although there is no sufficient evidence for such formulations, our current symptom-dominated clinical approaches are leading to irrational practices which are masquerading as EBM. Especially in developing countries like India, clinical practice is far away from EBM principles. It is no secret that the majority of clinicians receive continuing medical education from drug companies. Obviously, the prescriptions will be influenced by various business tactics. In a few countries, including India, a practice where a certain percentage per patient, and per diagnostic test is paid for referral (also known as kickbacks practice), has been condemned by the judicial system. Thus, while EBM is a very valuable contribution that has changed medical practice for good, in reality the picture of its actual use varies greatly across different landscapes.

T&CM and the Cochrane Approach
In the analysis of the evidence base for traditional and complementary medicine (T&CM) there are limitations as well. The Cochrane reviews are mainly based on available evidence, and data from clinical trials. The Cochrane methods might not have enough emphasis on secondary data analysis. The Cochrane methodology is based on available literature and is more relevant to clinical trials at a specific point of time. Present focus on RCTs as the main measure to provide certain kinds of evidence is myopic. Sometimes observational studies can uncover conclusive cause and effect relationships about an intervention. If there are no RCTs, a conclusive statement about evidence is not possible. This point is well discussed by Dr Gordon Smith, a researcher from Cambridge, and his colleagues in a witty “systematic review.” This article asks evidence whether parachutes are effective in preventing trauma or deaths related to gravitational challenge (Figure 4.2). As there are no “clinical trials” published on this problem, they conclude that “individuals who insist that all interventions need to be validated by a randomized controlled trial need to come down to earth with a bump” [14]. Although the example of parachutes and gravity is humorous, the message of this paper is serious. We should not restrict the search for evidence only to selected scientific methods.
The primary emphasis of Cochrane on “high internal validity” demands stringent selection criteria for systematic review; this might undermine the generalizability of the findings, since the selected studies focus on a very narrow range of patients. In this case, external validity (ability to generalize findings) goes down, especially when study protocols are different, and variations in clinical practices exist due to different schools of thoughts.
Double-blind RCTs are viewed as the gold standard in modern medicine. However, RCTs are impractical for many therapies, such as surgeries and complex lifestyle changes. They encourage a one-size-fits-all approach to medical treatment that fails to address the huge diversity among individual patients, in terms of their physical and emotional symptoms, social and cultural upbringing, and other factors. An alternate model has been proposed by Stanford-based research scholar, Dr Somik Raha. This model, Rishi principles, is based on Ayurveda, and epistemology, and includes inductive learning, whole systems thinking, and individually optimized therapy. According to this approach, individually optimized therapy can be interpreted using the lens of decision analysis [15]. Dr Raha suggests integrating the use of Ayurveda tactic known as Yukti with observational research methods and Bayesian logic for strengthening clinical practice. He proposes mathematical approach for improving clinical decisions by a process of continuous learning and updating practices. Clinicians can formulate a theory and assign expected fraction of desired benefits as prior probability, which can be assessed with the help of well-documented outcome measures. This approach is important for prospective observational studies on T&CM.
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Figure 4.2 Evidence for parachute. Reproduced with permission from Ref. [14].
Cochrane reviews appear to have limitations in the assessment of T&CM, especially when the treatments are individualized according to the Prakriti and geoclimatic seasons. For example, use of Bhallataka is indicated mainly in cold seasons, and Amalaki in hot seasons. There may be diverse practices, for example, the Kerala tradition of Ayurveda uses medicated oils and decoctions, while the North Indian practice consists of metals and minerals. The current Cochrane methodology is not able to understand these nuances, which are necessary to harmonize these variations.
There are ongoing efforts to develop protocols for T&CM therapies. Cochrane CAM Field is an activity of the Center for Integrative Medicine at the University of Maryland. The center promotes training and development of systematic reviews on T&CM therapies [16]. Protocols based on an Ayurvedic approach to treatment using Cochrane framework have been proposed. For example, Dr Narahari from the Institute of Applied Dermatology published a protocol to study evidence of Ayurvedic interventions for vitiligo. His protocol uses the Cochrane structure, and the Ayurvedic approach of personalized, whole system management [17]. However, a dearth of clinical trials which have proper study designs (to ensure quality data, and a low risk of bias) remains a hurdle. These efforts suggest that it will be beneficial to develop connections between Cochrane methodology and holistic T&CM approaches.
The EBM approach and holistic principles of T&CM practices need to be integrated so that clinical practice moves away from a straight-jacketed, mechanical process, which is aimed mainly at managing symptoms. The traditional practice may bring the patient back to the center of clinical practice. The Cochrane Collaboration is now moving in the direction of a holistic approach, and is exploring mixed method research, where learning from qualitative studies may be considered as evidence. This will change the present mind-set from a hierarchal model with RCTs at the top of the evidence pyramid to a circular model. This has provided new opportunities for development of an epistemologically relevant research methodology for T&CM.
The value of evidence for correct decision making is crucial for many academic disciplines, including scientific interpretation and law and judiciary systems. Evidence is extremely crucial to ensure safe and effective medicine. However, evidence should not be restricted to or monopolized as modern medicine. EBM is a systematic and rigorous process, which can be adopted by any system of medicine. However, the predominance of modern medicine in EBM has created an equivalency between modern medicine and EBM. There have been a few attempts by the complementary and alternative systems to enter the domain of EBM, and also possibly to ride the wave of its popularity. Osteopathy, acupuncture, traditional Chinese medicine, and homeopathy underwent huge turmoil in such attempts. While osteopathy made some headway, most of the others were not successful in justifying an EBM tag. A representative example of homeopathy provides a good case study of the T&CM sector.

The Case of Homeopathy
In 1796, a German physician, Samuel Hahnemann developed a new branch of medicine now known as homeopathy. Homeopathy is based on a principle proposed by Hahnemann that “like cures like.” According to Hahnemann, a substance that causes the symptoms of a disease in healthy people will cure similar symptoms in sick people. Part of homeopathy is the “law of minimum dose”: the lower the dose of the medication, the higher the effectiveness. Homeopathic medicines are derived from plants, minerals, or animal sources. Many potentially poisonous substances like nux vomica, arsenic, poison ivy, belladonna, and stinging nettle are used in extremely diluted forms. Homeopathic remedies are mostly prepared as lactose globules, and also as ointments, gels, drops, creams, and tablets. Homeopathic treatments are individualized to suit specific needs of a particular person. Many homeopathic remedies are so diluted that no molecule of the original substance is likely to remain in the diluted product.
The laws of chemistry state that there is a limit to dilution that can be made without losing the original substance altogether. This limit, which is related to Avogadro’s number, is roughly equal to homeopathic potencies of 12C or 24X (1 part in 1024). However, Hahnemann advocated 30C dilutions for most purposes, which goes to dilution by a factor of 1060. Chemically, this means that there remains not a single molecule of original substance. Therefore, critics of homeopathy call these medicines placebo. In their landmark study published in The Lancet which compared findings of 110 homeopathy verses 110 matched conventional medicine trials, Shang et al. supported the conclusion that the clinical effect of homeopathy are placebo effects [18].
The homeopathic community has been trying to convince the scientific community that homeopathic remedies are not the equivalent of placebos. Many studies were published in journals to defend the proposition that homeopathic dilutions might have a scientific basis. Homeopathic proponents also cite articles published by reputed scientists in mainstream journals. Most of these articles have indicated that solutions of high dilution can have statistically significant effects on organic processes including the growth of grain, histamine release by leukocytes, enzyme reactions, and degranulation of basophiles; this evidence is disputed since attempts to replicate them have failed.
A representative example of such attempts is a paper by French immunologist Jacques Benveniste, and the accompanying editorial, “When to Believe the Unbelievable,” published in Nature [19]. Benveniste suggested that water molecules might organize themselves as ghost molecules which mimic drug structures and can evoke biological responses—even in the absence of any original drug molecules. Benveniste’s paper certainly gave hope to proponents of homeopathy. However, the experiment was found to be ill designed and irreproducible when investigated by an independent investigative team [20].
In this decade, support for homeopathy was found in an interesting concept in toxicology known as hormesis. Hormesis does not follow a typical pharmacological dose–response relationship: low dose, low effect; high dose, high effect. In toxicology, hormesis is a dose–response phenomenon characterized by low-dose stimulation and high-dose inhibition. Over the past two decades, hormesis has become an important concept in biomedical disciplines. This is evident from the fact that the number of papers in the scientific database—a mere 10 to 15 per year in the past decade—rose to over 3200 in 2011 [21]. The resemblance of homeopathy to hormesis is so striking that many have been tempted to relate them to each other, while not making the claim for a toxicological relation. The prevalent thought is that Hugo Schulz, the founder of the hormesis concept, made a mistake in thinking that he had discovered the explanatory principle of homeopathy [22]. Taking a lesson from Benveniste, scientists and proponents of homeopathy are more cautious about reaching unsupported conclusions regarding the relationship between hormesis and homeopathy.
Proponents of homeopathy indicate that the epistemological relationship to the evidence is ignored when studying complex interventions. They believe that homeopathy has important lessons to teach with regard to complexity of individualized treatment, patterns of outcomes, and even the nonlinear, dynamic processes of healing in the patient as a whole system. These critics also maintain that the body of scientific evidence on homeopathy extends far beyond the limitations of the Shang et al. study. They point out that a number of curious, and sometimes clinically beneficial, phenomena can occur during homeopathic treatment. It is argued that homeopathic outcome measures are different from those in conventional medicine; homeopaths report global and hierarchically organized, multidimensional changes in the body. Therefore, it is suggested that future studies involving comparisons of homeopathy with modern medicine need to be designed on a level playing field in order to evaluate outcomes, from both a reductionist and a whole systems point of view [23].
One of the strong critics of homeopathy Dr David Shaw from the Institute of Biomedical Ethics, University of Basel, Switzerland, states “It should by now be very clear that homeopathy is a form of faith healing” [24]. In any case, the debate about the scientific rationale and evidence for homeopathy still continues.

Placebo and Nocebo Effects
Generally, a placebo is an inactive substance or preparation used as a control to determine the effectiveness of a pharmaceutical preparation. In 1955, Henry Beecher first recognized the clinical importance of the placebo effect [25]. Even though placebos do not act on the disease, they seem to affect how people feel. According to the American Cancer Society, the placebo effect can have an impact on the feelings or symptoms of almost one in three patients. Usually, the placebo effect usually lasts only a short time; sometimes the effect can also cause unpleasant symptoms including headaches, nervousness, nausea, or constipation. The untoward effects of a placebo is called the nocebo effect.
It is accepted that the mind can affect the body. In the quest to attain health or treat diseases, many ancient traditions, including Yoga and Ayurveda, are cognizant of the mind–body connection. Some people think that the placebo produces a cure, but placebos do not cure. For example, the role of placebos in tumor reduction has not been demonstrated, although placebos reduce pain. Still, in some people, placebos clearly can help reduce certain symptoms such as pain, anxiety, and insomnia. In earlier times, placebos were sometimes given by doctors if nothing else was available; they are still used today. A 2008 study found that nearly half of the doctors studied used a placebo. However, use of placebos is not considered ethical, and many governmental health agencies are on record as against using placebos. The United Kingdom Parliamentary Committee on Science and Technology stated: “prescribing placebos…usually relies on some degree of patient deception and prescribing pure placebos is bad medicine. Their effect is unreliable and unpredictable and cannot form the sole basis of any treatment on the NHS.” Patients may believe that a larger size placebo pill is more powerful than a small pill, an injection can have a stronger placebo effect than a pill, and expensive medicines are sometimes perceived as having more powerful effects.
A recent systematic review published by the Nordic Cochrane Centre in Copenhagen, Denmark, concludes that, in general, placebo interventions have important clinical effects. However, in certain settings placebo interventions can influence patient-reported outcomes, especially in those involving pain and nausea, although it is difficult to distinguish patient-reported effects of a placebo from biased reporting. The effect on pain varied, even among trials with a low risk of bias, from negligible to clinically important. Variations in the effect of placebo were partly explained by variations in how trials were conducted and how patients were informed [26]. This clearly indicates that the trial design, cultures, doctor–patient relations, and many other factors can influence the findings concerning the placebo response.
Another scientific observation that goes against homeopathy, and in favor of its placebo effect, is its ineffectiveness in animals and cell systems. In a study undertaken by scientists in Maryland, it was demonstrated that the highly diluted homeopathic remedies used by homeopathic practitioners for cancer show no measurable effects on cell growth, or gene expression, in vitro [27]. In April 2012, the Veterinary Clinical Research Database in Homeopathy containing 302 data records, including 146 RCT and 57 nonrandomized control trials, also did not show that homeopathic medical intervention was better than a placebo [28]. This strengthens the homeopathy opponent’s view that homeopathy is actually a treatment based on placebos.
The debate on the status of homeopathy as EBM, or placebo has gone through several phases—up and down, like a roller coaster ride. Sometimes homeopathy was riding high in popularity, sometimes it reached a low point. The final blow came from a systematic review based on the Cochrane database, published in 2010 by a professor from the University of Exeter, Dr Edzard Ernst. He concluded that the most reliable evidence fails to demonstrate that homeopathic medicines have effects beyond that of a placebo [29].
The skeptics of homeopathy proposed an interesting warning label that is based on what researcher Dylan Evans suggested in his book, Placebo: The Belief Effect [30]. In his book Trick or Treatment, Ernst suggested a warning label on every homeopathy product: “This product is a placebo. It will work only if you believe in homeopathy, and only for certain conditions such as pain and depression. Even then, it is not likely to be as powerful as orthodox drugs. You may get fewer side effects from this treatment than from a drug, but you will probably also get less benefits.” He also suggested extending the warning to other treatments like acupuncture, chiropractic, and herbal medicines [31].
Placebos work because of several factors related to mind and body interactions. Just the presence of a brain is not enough, as shown in animal studies. For a placebo to have an effect, a thinking mind and cognitive capabilities to create awareness of the desired effect is needed. Modern science’s understanding of the relationship between brain and mind is still evolving. Candace Pert discovered opiate receptors, where opiumlike drugs and morphine bind to nerve cells in the human brain [32]. This breakthrough led to the discovery of endorphins, which are analgesic, opiatelike chemicals naturally present in the brain, and responsible for feelings of happiness and bliss. We feel that it is possible for a conscious mind to actually order the brain to produce substances like endorphins.
It is known that even a placebo, or nocebo, effect can exert strong therapeutic responses, especially in cases of pain, inflammation, and psychosomatic disorders [33]. Therefore, while critics continue to believe that the putative effects of homeopathy primarily are a placebo response, many who benefit continue to put their trust in it. As stated by eminent cardiologist Dr B.M Hegde “the placebo doctor can provoke the human immune system much more powerfully than all medicines put together.” Many may feel that this is an exaggeration; it might indeed be so. However, we cannot ignore the fact that our present knowledge about mind–body relationships and therefore about the placebo is inadequate to reach to any definitive conclusions.

Evidence for Yoga

Research on Yoga provides an interesting slant on mind and body background. Yoga and Ayurveda propose lifestyle interventions, postural changes, meditation, and few therapeutic procedures. In recent years, Yoga therapies have been examined in rigorous research, and it is now more generally accepted that there is scientific backing to claims that Yoga can be used to achieve better health [34]. Research institutions in the United States, Europe, Canada, Australia, and China are actively involved in researching and teaching the practice of Yoga. The Cochrane Library cites 21 systematic reviews, and the PubMed cites 172 reviews on Yoga—much more than those on T&CM. While several institutes which teach Yoga have thrived, the contribution to biomedical research in Yoga from India is marginal. For instance, out of 21 Cochrane reviews, only one has come from India (from Apollo Hospitals); four each are from the United Kingdom, United States, and Canada.
Yoga has gained scientific credence, and has moved rapidly toward EBM by going through the rigors of scientific research. Yoga has the subject of experiments, and tests, and has been explored through sophisticated modern tools, including functional magnetic resonance imaging at the Universities of California, at San Diego, Los Angeles, and San Francisco; Harvard University; Stanford University; the University of Texas; Cleveland Clinic; Yale University; and the Mayo Clinic, among many others. In the process, Yoga has enhanced our current knowledge of neurophysiology and has spurred new research in areas such as meditation, cognition, and consciousness [35]. Ayurvedic medicine can take lessons from its Yoga component in evolving strategies and creating a road map to move it toward an integrative evidence base.

Evidence for Ayurveda

Every system of medicine that has endured the test of time has demonstrated evidence of efficacy and safety. Evidence of benefits can come from drug-based interventions, or because of a holistic approach involving diet and lifestyle. Ayurveda might not comport with the Cochrane EBM approach, but that does not mean that there is no evidence supporting it as a valid approach to health. Whether or not Ayurveda can be considered EBM is not the right question. The real question is whether the Ayurvedic fraternity has an open mind and the vibrancy required for the system to grow and evolve. Among other factors, this will involve the use of modern scientific methodology. There must also be a conducive environment for encouragement, nurturance, and respect for scholarship that facilitates the emergence of true scientists who can take any science to unending heights. Thousands of years of stagnancy in this sector raises several challenges to be met by this ancient science of life.
In India, Ayurveda is part of the culture. It is present in every family as home remedies. When it comes to doctors and patients, the picture is more complex. The value of Ayurveda as perceived by patients is very high, and so are the expectations. The majority of patient’s have a favorable perception of Ayurveda [36]. However, the costs of Ayurvedic treatments are increasing because of commercialization in wellness industry and medical tourism [37]. A lack of insurance coverage is adding to the costs to be paid out of pocket and the treatments are becoming unaffordable [38]. There are hardly any systematic studies in India on patients’ perceptions, behaviors, values, expectations, or acceptance, or on the economics and sociology of Ayurveda.
In the case of Ayurveda, the evidence might be drawn from two main sources. The first source of evidence is based on historical, classical, and contemporary clinical practice. The documentation of practice to support various claims is crucial; mere reference to classical texts is not sufficient evidence for practice. The second source of evidence can be based on scientific research to support various theories, medicines, and procedures used in Ayurvedic medicine. A critical situation analysis of the current status of clinical practice and scientific research on Ayurvedic medicine might be necessary at this stage.

Clinical Practice

Arguably, the clinical practice of classical Ayurveda is rare. Ayurvedic practitioners adopt allopathic practices in order to find more acceptance in urban settings [39]. Although a huge knowledge and wisdom resource is available in the form of classic Ayurvedic books, systematic data on actual use and evidence of reproducible outcomes is not available in the public domain. Standard treatment protocols for practitioners are not available. Systematic documentation and reliable data on pharmacoepidemiology and pharmacovigilance for clinical practice, safety, and adverse drug reactions is not available as open access, although a modest beginning has been made [40]. The status of professional [41] and continuing education [42], as well as attitudes of practitioners toward safety [43], are concerns.
In India’s current regulatory scheme, no scientific or clinical data is required for the manufacture and sale of classical Ayurvedic medicines. Technically sound pharmacopoeia, good manufacturing practices, quality control, and pharmaceutical technologies for Ayurvedic medicine are still evolving [44,45]. Issues related to appropriate research methodologies, or treatment protocols for Ayurveda also have not been properly addressed. Many critics are demanding better coordination between stakeholders, a continuous dialog with the scientific community [46], a total overhaul of the curriculum and pedagogy, and cross-talks between different modern medicines and Ayurveda and Yoga [41]. A recent report on the status of Indian medicine and folk healing indicates a need to strengthen research on and the use of Ayurveda, Yoga, Unani, Siddha, and homeopathy systems in the national health care [47,48]. The need for innovation is stressed by thought leaders in this sector [49]. In short, the evidence base to support good clinical practice, guidelines, and documentation in Ayurvedic medicine remain scant, and grossly inadequate.

Scientific Evidence
One of the basic principles behind RCTs is clinical equipoise, which agrees genuine uncertainty about treatment effects. This principle provides ethical basis to assign patients for comparisons in treatment arms—one with best known option as positive control and the other with a study drug with unknown effects. Obviously, in the case of T&CM drugs, where documentation and clinical experience is known in some form, the principle of clinical equipoise is not met. Therefore, critics argue that the RCT model might not be suitable to evaluate clinical benefits of T&CM drugs.
Therefore, while discussing about evidence for T&CM, the value of observational studies cannot be ignored. Certainly, there is a need to develop appropriate research methodology for complex, whole-system, whole-person-centered clinical trials as an alternative to RCTs. Already, scientists are advocating robust clinical study designs based on a personalized approach and metabolomics with only one patient [52]. Thus, the nonsuitability of RCTs to Ayurvedic research should not be used as an excuse for avoiding rigorous scientific research and clinical documentation.
Ayurvedic medicine continues to remain subcritical in scientific research publications, which is an important indicator of external evidence [53]. The current scientific evidence in support of Ayurvedic medicine remains extremely poor. The House of Lords and the European Union have put several restrictions on Ayurvedic medicines [54]. Many articles lamenting the quality of Ayurvedic medicines, particularly citing the presence of heavy metals and other safety-compromising substances, have been published [55,56].
Noteworthy attempts related to research and practice of Ayurveda include a national program on Ayurvedic biology [57,58], Ayugenomics [59], whole systems clinical research [60–62], good clinical practices guidelines, the establishment of a digital helpline [63], a clinical decision support system AyuSoft, and a systematic reporting standards on lines with Consolidated Standards of Reporting Trials (CONSORT) for Ayurveda [64,65]. Recent efforts to develop robust clinical protocols for comparing the effectiveness of complex Ayurvedic and conventional treatments are laudable [66]. Other notable efforts related to integrative therapy for leishmaniasis have been able to generate sufficient scientific evidence [67]. Admittedly, many of these efforts have not produced any remarkable products, processes, or protocols, and the desired impact on the scientific community is yet to be seen. The need to enhance the collaborative culture between the Ayurvedic and modern, scientific communities rightly has been stressed by many researchers who have experienced benefits of integrative approaches [68].

Concepts of Evidence in Ayurveda

The original knowledge base of Ayurveda is evidence based. Ayurveda is not merely a collection of traditional experiences. Ayurveda expects logic and proof of causality in every therapeutic decision. The chance effect is not accepted in Ayurveda. Ayurveda describes evidence in context of Pramana, in four main categories. The term Pramana literally means “right perception” and “means of acquiring knowledge” [69]. The first category is known as Pratyaksha, or evidence generated from actual and direct observations. This is very similar to experimental evidence. This evidence is based on measurable parameters, which could be based on direct feelings, or understanding through the five senses. Measurements using any instrument are also included in this category. Essentially, what is measured using instruments ultimately has to be read and understood by our senses. In a way, instruments are extensions of our senses. The Western philosophy of scientific positivism only considers this category as evidence.
The second category of evidence is known as Anumana. This involves analyzing the observed and measured data, with the help of logic and causality. The third category is Apta, which comes from experiential wisdom, and the unbiased opinions of experts. According to Ayurveda, Apta are the authorities who are distinguished, enlightened, and absolutely free of bias and ignorance, and who have state-of-the-art knowledge pertaining to the past, present, and future. Apta is not necessarily applicable to any one individual, rather, it is a continuum of knowledge traditions. Ayurveda gives maximum evidence weightage to Apta.
The fourth category is Yukti, which is a tactical analysis. Yukti actually considers multiple variables, confounding factors, and systematic reviews of available knowledge. The sum and substance of these categories is used as evidence for any decision making. Obviously, this process may involve subjectivity and qualitative variables. However, any outcome is expected to be judged in the context of causation and association.
Ayurveda emphasizes a critical assessment of cause and effect through reproducible and unbiased evidence. It expects a consistent, reproducible association in every causality analysis. The reliability and validity of evidence is considered as proof of its theories. Any reliable association with proof of causation assessed in multiple trials by various observers is considered as theory.
Ayurveda has evolved through documentation of observations from nature: the results of experiments designed to test assumptions and documented clinical experiences. Ayurveda, in its true spirit, is open to questions and critique. The knowledge of Ayurveda is not restricted to the particular person, or a book. Any demonstrated conclusion of an argument is termed as Siddhanta, which requires sound proof through multiple, critical scrutiny before it is widely accepted. The Siddhanta term covers the following concepts related to evidence:
• Unbiased enquiry by impartial authorities
• Testable hypothesis
• Multiple and reproducible tests
• Consistent observations established by causality
• Overcoming counterfactual evidence
• Any statement requiring proof
Ayurvedic sage Charaka discusses the definition of management in the context of logic, and proof of efficacy. He terms any management “effects following certain logic and rules,” rather than chance or haphazard phenomenon. He further condemns any practice that does not follow this approach as “quackery,” and castigates the doctor who spreads diseases rather than providing health. The expectations in EBM match the qualities of a good doctor detailed in the Samhita, and there is no conceptual divide. Sushruta states that evidence endorsed by unbiased authorities, and which is perceived in direct observation, can be practiced as a truth, and treated as a sacred mantra.
Yoga describes a new paradigm for evidence in terms of self-realization; in Sanskrit self-realization is Aatmanubhooti. In addition to any external evidence, Yoga suggests “self-experiencing” as the highest level of evidence. It suggests eight steps to gradually move toward self-realization. In simple terms, before convincing others, the concerned individual should be convinced about the value of the knowledge; this conviction can be considered as evidence. For example, any doctor should prescribe only such drugs and procedures which he or she will be willing to accept as a safe and appropriate treatment. This requires a high level of professional competency and ethics. Therefore, self-experiencing is an acid test, which should be considered as the highest level of evidence.
Ayurveda has its own EBM. The key challenge is to strengthen its evidence base further to produce Vaidya scientists in the professional community who are Ayurvedic physicians (Vaidya) as well as well-versed with modern science. This is similar to physician–scientists who simultaneously undertake scientific research and clinical practice. Admittedly, the arguments for and against EBM and Ayurveda are based on Western biomedical standards. This includes systematic drug discovery, development with the help of RCTs, and statistical analysis to show that the prescribed drug prevails over a placebo. However, it is important to recognize that Ayurveda has a holistic approach based on thousands of years of experience. It is an integrated system that considers body, mind, and spirit. Ayurvedic therapeutics is not restricted to the mere use of drugs. While herbal drugs are used, lifestyle modification remains the bedrock of Ayurvedic therapeutics. Lifestyle modification prescribed by Ayurveda is not just diet and exercise, but encompasses the entire process of personality—including mental attitude and personal philosophy. This is how Ayurveda approaches diseases, and attempts to treat the root cause—by introducing change in the environment within a milieu intérieur, as described by Claude Bernard. This approach goes beyond eliminating or decreasing symptoms with drugs. In fact, RCTs for Ayurveda could be considered an oxymoron, and experts are questioning validity of these models to holistic systems like Ayurveda [70]. This has to be kept in mind when we talk about EBM for Ayurveda. There are no existing models to follow, and this is a great challenge for holistic systems.
Therefore, the authors believe that the Cochrane concept of EBM in its present form might not be suitable for T&CM systems. We strongly feel that “E” in EBM should not be restricted to scientific Evidence but should also include “Experience” and wisdom of generations. The epidemiological and outcome-based evidence should also be given due weightage. We feel that scientific evidence, and traditional experience should not be mutually exclusive. The new EBM should also be experienced-based medicine. Appropriately, we might call it E 2 BM, wherein experience-based medicine and EBM are fully integrated (Figure 4.3).
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Figure 4.3 EBM needs to include experimental and epidemiological dimensions. Experiential wisdom is not enough unless it is backed by outcome-based evidence. Together, they can evolve a new approach known as evidence- and experience-based medicine (E2BM).

The New EBM

The concept of EBM has gone through many transitions ever since Gordon Guyatt, a Canadian professor of clinical epidemiology, and his colleagues coined the term over 20   years ago. JAMA has recently released the oral history of EBM [71]. While EBM has many advantages, it also poses some problems. Many experts feel that the evidence-based “quality mark” has been misappropriated, and distorted by vested interests—particularly by the pharmaceutical and medical devices industries [72]. We discussed this subject in Chapter 2 in sections related to medicalization. Industries seem to use financial means to not only set the research agenda but also influence definitions of disease conditions. They also often dictate normal values, and the nature of diagnostic tests. Sponsored clinical trials and using statistics to the commercial interests’ advantage is a matter of great concern. The volume of evidence is becoming unmanageable. The inflexible rules, and technology-intensive protocols create health care management which is driven by the interests of partners who have competing interests, rather than by a focus on the good of the patient—which should be the primary concern. In the process, EBM has become more mechanical, protocol driven, and pathology diagnostics oriented. Ironically, in the process, EBM has become very expensive and unaffordable to many—especially to those who are not covered by insurance.
The new EBM should make the care of individual patient’s top priority. The best course of action is likely to be different for different patients, who are in different environments, and have different disease conditions [73]. The new EBM should consciously and reflexively refrain from unethical practices and unnecessary, or avoidable, tests and medicines. It should engage with ethical and existential questions. Experts are suggesting that patients should be empowered to make correct and appropriate decisions regarding their own health care. Medical associations, guidelines, governments, and insurers should not unilaterally decide the fate of the patient. This is now possible due to the power of information science [74]. The new EBM should be individualized for the patient. It should be accepted in principle that even the “best evidence” may not apply to certain patients for a variety of reasons [75]. Every patient should be objectively evaluated by the clinician in an unbiased way, on case-by-case basis. Clinicians should use their own clinical acumen and experience and then judge their evaluation against the scientific evidence. Here also, the “first-do-no-harm” principle should be followed.
We feel that it is high time for the EBM movement to be extended to integrative health. A new idea needs to be conceptualized as evidence-based health (EBH) approach. The principles of EBH should be based on personalized and integrative approaches, bridging modern science and traditional knowledge. We must produce an integrative system of evidence-based care, which combines the strength of each system. For instance, Ayurveda possesses the proven benefits of body–mind melding Yoga and meditation, a rational diet, and nutrition and lifestyle doctrines, and it emphasizes restorative or rejuvenative medicine.
The future of medicine has in its grasp the capability to heal the increasingly sick planet. It needs both the Western biomedicine, as well as the Eastern Ayurveda and other Eastern traditional practices. A new system of integrative health is emerging where the barriers between traditions, disciplines, and systems are dissolving. It is hoped that this new integrative system will meet the daunting challenges of today and tomorrow!
Efforts to obtain scientific evidence in the T&CM sector require applying appropriate methods. Current evidence is based on our contemporary understanding and on the availability of scientific tools, both of which are continuously evolving. Therefore, just because we are not able to measure something using current scientific methods, it does not mean that it does not exist. It is generally accepted that “the absence of evidence should not be taken as evidence of absence” [76]. Current statistical practices, and double-blind approaches in clinical trials, where p values are considered symbols of scientific evidence to prove a drug’s efficacy, are under debate. We need to develop novel statistical models based on Bayesian logic and systems analytics in order to evolve innovative scientific methodologies, create a new evidence base, and facilitate sensible decision making for Ayurveda.
At this stage, it is important to recall Sir Austin Bradford Hill’s 1965 discourse where he listed experiential evidence as one among nine, key factors. We cannot make a final judgment call merely based on experimental evidence. Many decisions can be made based on epidemiologic evidence and outcome-based evidence. Sir Austin advised epidemiologists to avoid the overemphasis of statistical significance testing, because systematic error is often greater than random error. He also stressed the need to consider costs and benefits when making decisions. Sir Austin’s presidential address of 1965 is even more relevant today [77].

High Evidence Low Ethics
According to a study by the watchdog group, Public Citizen, the pharmaceutical drug industry has surpassed the defense industry to become the biggest defrauder of the federal government. The Public Citizen report states that the drug industry paid nearly $20 billion in penalties during the past two decades for violations of the False Claims Act [78]. This unhealthy behavior, and the tendency to compromise ethics for profits, appears to be a global phenomenon. The big four companies—GlaxoSmithKline, Pfizer, Eli Lilly, and Schering-Plough—account for more than half of the violations. These leading violators are among the world’s largest pharmaceutical companies.
The United States Food and Drug Administration has levied fines of $500 million for scientific fraud and dubious research outcomes on Indian companies like Ranbaxy. The whistle-blower, Dinesh Thakur, who single-handedly exposed this scam, was awarded $28 million in recognition of his role in exposing the fraud. A detailed case study of corporate crime in the pharmaceutical industry [79] by John Braithwaite of the University of California, Irvine, gives a very scary glimpse of unethical practices that seem to be deeply rooted in this industry—an industry which directly deals with the health of billions. Sadly, the role of scientists in this process is also being questioned. The analysis of the data in one recent systematic review suggests that the outcomes of industry-sponsored drug and device studies are often favorable to the sponsors’ products [80]. Another systematic review concludes that industry-sponsored studies are biased in favor of the sponsors’ products [81].
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Figure 4.4 High in evidence low in ethics.
There exist not only biases in favor of sponsors’ products but also instances where the scientific data has been fudged, twisted, and interpreted in such a way that a particular drug’s actions are highlighted as favorable, while safety issues or side effects are downplayed. Several examples of such attempts are available. For instance, blockbuster drugs like new-generation antipsychotics have seen a fall in favor, because their predicted benefits were found literally to wear off [82].
In this context, a recent report titled Late Lessons from Early Warnings, released by the European Environmental Agency is very relevant [83]. Citing examples, the crux of this report is that, by and large, scientists have worked more for businesses and economics, and less for people and humanity. The best, or rather worst, example of such industry–scientist nexus is from the tobacco industry, which deliberately created confusion, and delayed public awareness of the dangers of tobacco use, and legislation regarding the advertising of tobacco products for decades. Many journals like British Medical Journal (BMJ), Thorax, and Heart have stopped publishing research funded by the tobacco industry, because the research is corrupted, and the companies back the research to advance their commercial aims.
The situation in which bottom-line, financial considerations outweigh public health and safety is also feared to be insinuating itself into the pharmaceutical industry. Now critics are extending the reasons and arguments against the way in which the tobacco industry comported itself in obfuscating the dangers of tobacco use, to research funded by the drug industry. The way in which pharmaceutical companies get the results they want has been extensively debated. Critics are deeply concerned about the use and misuse of statistical methodologies in pharmacology research [84]. It is of great concern that statistics is being misused to interpret results to support a desired outcome, rather than to show the true outcome. There seems to be strong evidence that companies obtain desired outcomes through backing research that will only support their interests, or skewing the interpretation of the data to suit their interests; a substantial number of the clinical trials published in major journals like Annals of Internal Medicine, JAMA, The Lancet, and The New England Journal of Medicine are funded by the pharmaceutical industry [85]. Critics ask the tough question: Are medical journals a marketing arm of pharmaceutical companies? [86]. It is suggested that journals should critique trials, and not just publish them. Experts are suggesting that, in the interest of patient safety, more transparent, and better ways to release results of trials must be implemented.
Today, prescription drugs are the third leading cause of death worldwide. It is a matter of great concern; investigation and introspection are required to understand why we have reached such a scenario. The present models of drug research and regulatory provisions, especially to evaluate safety and toxicity, are in need of serious overhaul. Vested interests which push unsafe drugs are certainly not in the interest of anyone. Earlier incidences from trials of cyclooxygenase-2 inhibitors for arthritis and selective serotonin reuptake inhibitors for depression are good examples. Critics are asking the question: Should journals stop publishing research funded by the drug industry [87]. In short, scientific evidence is important, but it should not compromise medical ethics at the cost of business.
We need a balance of scientific medicine, EBM, and traditional experience-based medicine. Against this background, we hope that the traditional knowledge and ethos can help to resolve the current impasse. This new balance will offer rich experience, knowledge and resources, new ideas, and leads and strategies. Drug discovery should be curiosity- and research-based approach where passionate individuals are committed to serve the humanity by developing affordable effective treatments. Present drug discovery is viewed as a pipeline process, which has been outsourced to mechanical productions where evidence is seen as a commodity, which can be manufactured.