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Fortunately, most treatment decisions need information only on whether a practice has a specific effect and on the magnitude of that effect in practice. This is evidence from randomized controlled trials and outcomes research, respectively. An evidence-based practice would then involve clinical expertise, informed patient communication, and quality research. This presumes that the physician has good clinical and communication skills. Medical training and experience address these, but evaluation of the CAM research evidence may not be something that physicians feel fully prepared to undertake. Obtaining research, selecting appropriate research for clinical situations, and then evaluating the quality of that research in CAM are essential for a fully evidence-based practice that addresses these topics.
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A. Finding and Selecting Good Information
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Where can the family physician obtain research on CAM? A number of groups have collated and produced CAM-specific databases (Cochrane Collaboration, Evidence Based Medicine Reviews, Samueli Institute, and Natural Standard). Table 50-2 lists some good sources of clinical information on CAM and what they provide. When searching these databases, look for the following key terms: (1) meta-analyses, (2) RCTs, and (3) observational or prospective outcomes data. Although there are many other types of studies, it is necessary to be cautious about using these for problem-oriented decision making in practice. If no research information is found from the databases listed, it is likely that there is little relevant evidence for the practice on that clinical condition. A search for this information need not take up a lot of time. A trained research assistant or librarian can often do the search, streamlining time spent on this process. Many librarians, especially those at health centers and hospitals, are now receiving training in literature searching methodology and growing awareness and expertise in CAM databases. After a literature search, the physician can be confident in knowing the quantity of evidence on the therapy (Figure 50-3). Patients are usually grateful for this effort as they will come to their physician in the hopes of obtaining science-based information they can trust.
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B. Risks and Types of Evidence for Practice
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If there are studies on a specific type of CAM practice, then the risk of toxicity and the cost of the therapy indicate which types of data are needed. Low-risk practices include OTC homeopathic medications, acupuncture and gentle massage or manipulation, meditation, relaxation and biofeedback, other mind-body methods, and vitamin and mineral supplementation below toxic doses. Low-cost therapies involving self-care are also often low-risk. High-risk practices include herbal therapies, high-dosage vitamins and minerals, colonics, and intravenous administration of substances. Some otherwise harmless therapies can produce considerable cost if they require major lifestyle changes. Herbal therapies can produce serious adverse effects secondary to their impact on cell function, including enzymatic reactions or contamination with toxic materials. Because patients frequently take herbal products along with calculated dose prescription medications, physicians should specifically inquire about their use. High-risk or high-cost practices and products require RCT data.
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Under some circumstances, observational (outcomes) data are more important, and in other circumstances RCT data are more important. Outcomes research provides the probability of an effect and the absolute magnitude of effects in the context of normal clinical care. It is more similar to clinical practice and usually involves a wide variety of patients and variations of care to fit the patient’s circumstances. It does not provide information on whether a treatment is specific or better than another treatment.
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With low-risk practices, the physician wants to know the probability of benefit from the therapy. Quality observational data from practices are preferable to RCT data if the data are collected from actual practice populations similar to those of the practitioner. This may be sufficient evidence for making clinical decisions. Often, it will be the only useful information available for chronic conditions. For example, if quality outcome studies report a 75% probability of improving allergic rhinitis using a nontoxic, low-cost, homeopathic remedy, this information can assist in deciding on its use.
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For high-risk, high-cost interventions, the physician should use randomized controlled trials (or meta-analyses of those trials). RCTs address the relative benefit of one therapy over another (or no therapy). RCTs can determine whether the treatment is the cause of improvement and how much the treatment adds to either no treatment or placebo treatment. RCTs provide relative (not absolute) information effects between a CAM and control practice. They are difficult to do properly for more than short periods and difficult if the therapy being tested is complex and individualized or if there are marked patient preferences. In addition, RCTs remove any choice about therapy and, if blinded, blunt expectations—both of which affect outcomes. Placebo-controlled RCT differences are dependent largely on the control group, which requires careful selection and management. Strong patient preferences for CAM, differing cultural groups, and informed consent may also alter RCT results. RCTs are more important if we need to know more about specific benefit-harm comparisons, such as with high-risk, high-cost interventions. Recently comparative effectiveness research (CER) has emerged as an important goal and set of methods. CER may be a valuable addition to CAM research, allowing whole systems of care to be compared to other different systems.
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The more a CAM practice addresses chronic disease and depends on self-care (eg, meditation, yoga, biofeedback), or involves a complex system (eg, classical homeopathy, traditional Chinese medicine, Unani-Tibb), the more local, observational data are important. The more a CAM practice involves high-risk or high-cost interventions, the more essential RCT data become.
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C. Evaluating Study Quality
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Once data are found and the preferred type of study is selected, the practitioner should apply some minimum quality criteria to these studies. Three items can be quickly checked: (1) blind and random allocation of subjects to comparison groups (in RCTs) or blind outcome assessments (in observational research), (2) the clinical relevance and reliability of the outcome measures, and (3) the number of subjects that could be fully analyzed at the end of the study compared to the number entered. These same minimum quality criteria apply to RCTs or observational studies, except that blinded, random allocation to treatment and comparison groups does not apply in the latter. However, evaluation of effects before/after treatment can be blinded to the treatment given in any study. Detailed descriptions of patients, interventions, and dropouts are hallmarks of a quality outcomes trial.
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Finally, one can ask if the probability of benefits reported in the outcomes study is worth the inconvenience, risk of side effects, and costs of the treatment and, in addition, whether confidence intervals were reported. Confidence intervals are the range of minimum to maximum effects expected in 95% of similar studies. If confidence intervals are narrow, the physician can be confident that similar results will occur with other patients. If confidence intervals are broad, the chance of obtaining those effects from treatment in other patients will be less predictable.
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If the quality screening questions reveal marked quality flaws in the studies retrieved, the evidence in the study is insufficient and should not be used as a basis for clinical decisions.
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D. The Population Studied
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Even if good evidence is found for a practice, physicians should determine whether the population in the studies is similar to the patient being seen. Although this matching is largely subjective, the physician can compare five areas. Specifically, determine whether the study was done (1) in a primary, secondary, or tertiary referral center; (2) in a Western, Eastern, developing, or industrialized country; and (3) with diagnostic criteria similar to the patient (eg, the same criteria were used to diagnose osteoarthritis or congestive heart failure). Also, determine whether the age (4) and gender(s) (5) of the study population were similar. If the study population is not similar to the patient being seen, then the data, even though valid, cannot be applied to the situation. The study country may be especially important for some CAM practices. For example, data on use of acupuncture to treat chronic pain may come from China. Pain perception and reporting is different in China from that in the United States. Results from a study done in one country may not be applicable in another. If the study and clinic population match, an appropriate body of evidence for moving forward with a therapeutic trial exists.
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Belief in the treatment by the physician and the patient needs to be explicitly considered in CAM. In conventional medicine, both patient and physician accept the plausibility of treatment. Belief has long been known to affect outcome. Strong belief enhances positive outcomes, and weak belief interferes with them. A physician may feel that a CAM practice has incredibly low plausibility although the patient may have a strong belief in the therapy. This “prior probability” (or belief) by the physician and patient should be considered in the decision to allow or not allow the patient to use a treatment. If physician and patient have similar beliefs, then a decision is easily made. Sometimes, however, the patient has a strong belief in the therapy, but the physician finds it unbelievable. In such situations, the physician should work with the patient to decide the best action—including referral elsewhere as an option.
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F. Alternative Diagnoses
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Some diagnoses are not very useful for management of a patient’s illness. If the family physician’s conventional diagnosis is not helping a patient, the clinician may want to consider an evaluation by an alternative system. Chinese medicine uses energy diagnosis, for example, and homeopathy has a remedy classification system. Sometimes, obtaining an assessment from a practitioner experienced in a CAM system may prove useful. For example, a 51-year-old woman with several years of idiopathic urticaria had obtained no relief from several conventional physicians. A homeopathic assessment showed that she might benefit from the remedy Mercurius 200C (mercurius virax). She was given several small doses and the urticaria cleared.
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The physician should also be alert to practitioners who pursue CAM diagnoses that are not useful. A complicated CAM evaluation and treatment with little effect might be managed simply and effectively by conventional medicine. For example, a 57-year-old man with cardiovascular disease and recurrent bouts of angina was treated by a CAM practitioner for 3 years with special diets and nutritional supplements without help. Consultation with a conventional practitioner shows that he had myxedema. A thyroid supplement cleared his angina rapidly. In cases in which the diagnostic approach of the medical system fails, a professional consultation may be needed. In situations in which the alternative system’s diagnostic and treatment approach is clear, a limited therapeutic trial with specific treatment goals and follow-up can be attempted. Of course, quality products and qualified practitioners must be located. In situations of serious disease, such as cancer, desperate patients may seek out CAM treatments. Under these circumstances, good training and clinical experience and protection of patients from harm (even from themselves) should prevail.
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Evidence-based medicine can be applied to complementary and alternative medicine. Table 50-3 summarizes questions for CAM management. Although evidence-based CAM may initially seem like a large task, appropriate data-driven clinical decisions can be made with CAM as with all medical care.
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