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Alternative medicine does not exist, biomedicine does not exist, there is only evidence-based medicine

Authors:
  • Quality of Life Research Center
Alternative medicine does not exist, biomedicine does not exist. There is only evidence-based medicine:
Medicine scientifically documented to be of therapeutic value, with a high ratio of benefit to harm.
Søren Ventegodt and Joav Merrick
There is only medicine. Not good and bad medicine. Not alternative medicine. Not biomedicine. NN was
right (1). All drugs are to some extends poisonous, and have adverse effects, so their value as medicine
depends on the ratio benefit to harm. In the Danish law regulating the pharmaceutical drugs used in
Denmark, the focus is thus on the therapeutic value expressed as the ratio of benefit to harm (2).
The benefit must be larger than the harm or at least the benefits must be more preferable than the harm, if a
drug is to be used as medicine. This is logical. If a drug only causes harm and have no positive qualities, or if
the negative qualities dominate the positive, the drug is a poison, not a medicine.
The principle that the therapeutic value can be expressed as the ratio benefit/harm is valid for all kinds of
medicine. In intervention is medicine if and only if the benefit for the patient is significantly larger than the
harm. Just to move a health problem from one organ to another is not a solution or a cure, although the
patient might feel that for a moment, because every change if felt as progress.
The simplest scientific expression of the ratio benefit to harm is called “Therapeutic Value” (3) and can be
calculated as TV=NNHtotal/NNT, where NNHtotal is the total likelihood to get a harmful adverse effect, and
NNT is the likelihood to get the benefit (3,4). The condition for this formula to be meaningful is that the
benefits and harms are effects of similar clinical significance, which luckily often is the case in clinical trials,
as positive effects and negative effects are registered as soon as they are clinically significant (to minimize
NNT and maximize NNH in the measurement, which favors sales of the new drug tested ) (5).
The nature of the fraction TV=NNHtotal/NNT make it a rather rough estimate, and only if there is difference
in magnitude of numbers can we be sure of a clinically significant difference in a comparison of two cures.
This means that one cure needs a TV that is 10 times larger than another or so, before we can be sure that
one is better than another. Of course one would always choose the cure with the highest TV, if nothing
pointed to one treatment more than another (prize, specific unwanted adverse effects etc.)
As BMJ deputy-editor Trish Groves recently has concluded, evidence-based drug medicine has recently
looked more like evidence-debased medicine, as many types of drugs come out with very large or even
insignificant NNTs (very small TVs) in the independent metaanalyses (often Cochrane reviews) (6).
In the industrial trials NNTs are usually low and HHNs are usually high. But when all data is collected and
bias like publication bias from publication only selective, positive findings are eliminated in large
metaanalyses, NNTs are almost always getting much higher and NNHs much lower than in the original
industrial RCTs.
As studies are collected the number of adverse effects is also rising, because different studies include
different adverse effects. A typical antipsychotic, antidepressant or anticancer drug can have 20 severe
adverse effects or more each with NNHs from 2-30, making NNHtotal coming close to one (7,8,9).
At the same time, NNTs, which are normally around 20 (5-50) in the industrial RCT-studies (10) are often
going up to 50, 100 or even all the way to insignificant benefits (7,8,9).
If you in the high-level meta-analyses of whole groups of drugs look for the specific outcomes which are
really important to the patients, you will see that these outcomes are often not significantly improved at all,
revealing that the drugs we believed were medicines are actually poisons. This is highly problematic as this
means that we as physicians often give patients drugs we believe to be beneficial, but which in the end are
found to be only harmful. In reality we have been poisoning our patients, in good faith of course.
Let look at some examples. We all know of extremely useful drugs, like penicillin for syphilis and
gonorrhea, compensatory treatments with hormones like insulin, T3 and T4 etc. So please understand that we
are not criticizing the use of drugs per se. We just want drugs to be evidence-based – like any other
intervention we call medicine.
In a Cochrane review the patients were not less depressed with any antidepressant drugs when active placebo
was used to control for toxicity – no antidepressant passed the test of being better than placebo (7). All
known antidepressant drugs are poisons according to this study. The whole group of antidepressant drugs
failed the test.
In a vast Cochrane metaanalysis of all anti-psychotic drugs no drug came our better than chlorpromazine,
and “Mental state” – the only outcome directly related to the patients mental health - was not improved by
any antipsychotic drug (8). Antipsychotic did improve patient’s behaviour (outcome: less “hallucinatory
behaviour”) so that the patients acted out less, which can be very practical with violent psychotic patients.
This effect tells us that the antipsychotic drugs are sedatives; but they are still poisons: According to the
Cochrane review they harm significantly more than they help.
A famous example is the Abel study of anticancer chemotherapy (9). Abel collected all data on the treatment
of epitheloid cancers (all major cancers) from all researchers and found to his own surprise that quality of
life and survival was not improved; actually quite the opposite was the case. The drugs were according to
Abel poisons, not medicines.
Often antibiotics still works in metaanalysis, but not always: penicillin for acute otitis given to 98% of all
children failed to speed healing significantly in a Cochrane metaanalysis, but the harm was still done (11).
Many more examples could be given but we are sure you got the picture. It is difficult times indeed for
evidence-based drug medicine. The drugs almost always have a TV=NNHtotal/NNT of about 1 in industrial
studies; in Cochrane reviews and independent meta-analyses of single drugs TV falls down to 0.1-0.01,, and
often the positive effect is completely lost in metaanalyses of whole groups of drugs (TV=0).
As the last type of studies are the most reliable and valid, we are forced to conclude, that many drugs used
today are really not medicine, even if we believe them to be so.
Some physicians know this and argue that it still is rational to use them as the placebo-effect will benefit the
patient after all. But a recent Cochrane metaanalyses has even taken this excuse from us (12): there is no
placebo effect in a pill. Only a close relationship between physician and patient will give a clinically
significant placebo-effect (13).
Another important problem with the inefficient drugs is that they might prevent the patient from having the
cure that really could help and cure them(4). CAM been found safe and efficient in a large number of
Cochrane reviews (14) and other independent research reports like the many Backgrounder papers from
NCCAM.
The safest kind of CAM seems to be massage therapy, with 20.000.000 adults and 700.000 children having
massage therapy every year in USA alone; while “very few” patients have been harmed by massage (15),
indicating a NNHtotal≈1,000,000. Unfortunately massage therapy is not very effective for most clinical
conditions; the studies listed in (15) indicates NNTs around 3-30 for most physical and mental illnesses.
But when you compare benefits to harm you get an impressive TV=NNHtotal/NNT=1,000,000/30= 33.000!
Similar numbers are found for talk therapy, so you understand why talk and touch therapy were the two types
of therapy used by the Hippocratic doctors who had the absolutistic, medical ethic: “First do no harm”. The
reason for combining the therapeutic talk and touch to the classic, holistic, mind-body medicine (which we
now call clinical holistic medicine, CHM) seems to be a strong synergic effect allowing for even severe
illnesses to be cured, like coronary heart disorder (16,17) with remarkable NNTs of about 2! In recent
reviews we found holistic medicine of mind-body type to be effective in most clinical conditions (18,19,20)
Comparing the TVs of drugs (1-0.01) with the TVs of CAM (100-33.000) gives us a strong indication that if
a clinical condition can be treated with a drug and a non-drug treatment, the non-drug CAM treatment will
normally be the cure of choice. We should never forget that drugs always are poisonous to some extent, and
that it is estimated that there are now 100,000 deaths a year in US hospitals directly caused by
pharmaceutical drugs (21). That does not mean that we should try to cure syphilis gonorrhoea with non-drug
CAM, of course. But for the many chronic conditions like the many chronic pain syndromes, depressions,
psychotic mental illnesses etc. where drugs has little to offer patients, and put patients in significant danger,
non-drug CAM should always be the first choice.
ACKNOWLEDGMENTS
The Danish Quality of Life Survey, Quality of Life Research Center and the Research
Clinic for Holistic Medicine, Copenhagen, was from 1987 till today supported by grants
from the 1991 Pharmacy Foundation, the Goodwill-fonden, the JL-Foundation, E
Danielsen and Wife's Foundation, Emmerick Meyer's Trust, the Frimodt-Heineken
Foundation, the Hede Nielsen Family Foundation, Petrus Andersens Fond, Wholesaler CP
Frederiksens Study Trust, Else and Mogens Wedell-Wedellsborg's Foundation and IMK
Almene Fond. The research in quality of life and scientific complementary and holistic
medicine was approved by the Copenhagen Scientific Ethical Committee under the
numbers (KF)V. 100.1762-90, (KF)V. 100.2123/91, (KF)V. 01-502/93, (KF)V. 01-026/97,
(KF)V. 01-162/97, (KF)V. 01-198/97, and further correspondence. We declare no conflicts
of interest.
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... The Qualitative Methods Working Group of NIH developed a methodological manifesto in 1997 to identify study designs and analyses applicable to CAMs, pursuing standardization or suggesting new approaches, such as the "Whole System Approach", aimed at respecting the personalization of therapies, which is often basic to the practice of CAMs [24][25][26][27][28][29][30][31][32][33]. Within these limits, the application of evidencebased medicine (EBM) to the analysis of CAMs confirms the versatility of EBM as a problem-solving approach, disentangling the complex relationship between "Medicine and Medicines" [34][35][36][37]. ...
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Search strategy: We searched the Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library Issue 4, 2007), MEDLINE (1966 to March 2008), EMBASE (1980 to March 2008), PsycINFO (1887 to March 2008) and Biological Abstracts (1986 to March 2008). We contacted experts on placebo research, and read references in the included trials. Selection criteria: We included randomised placebo trials with a no-treatment control group investigating any health problem. Data collection and analysis: Two authors independently assessed trial quality and extracted data. We contacted study authors for additional information. Trials with binary data were summarised using relative risk (a value of less than 1 indicates a beneficial effect of placebo), and trials with continuous outcomes were summarised using standardised mean difference (a negative value indicates a beneficial effect of placebo). 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The effect on pain varied considerably, even among trials with low risk of bias.In 158 trials with continuous outcomes (10,525 patients), there was moderate heterogeneity (P < 0.001; I(2) 42%), and considerable variation in effects between small and large trials (asymmetrical funnel plot). It is therefore a questionable procedure to pool all the trials, and we did so mainly as a basis for exploring causes for heterogeneity. We found an overall effect of placebo treatments, standardised mean difference (SMD) -0.23 (95% CI -0.28 to -0.17). The SMD for patient-reported outcomes was -0.26 (95% CI -0.32 to -0.19), and for observer-reported outcomes, SMD -0.13 (95% CI -0.24 to -0.02). We found an effect on pain, SMD -0.28 (95% CI -0.36 to -0.19)); nausea, SMD -0.25 (-0.46 to -0.04)), asthma (-0.35 (-0.70 to -0.01)), and phobia (SMD -0.63 (95% CI -1.17 to -0.08)). The effect on pain was very variable, also among trials with low risk of bias. Four similarly-designed acupuncture trials conducted by an overlapping group of authors reported large effects (SMD -0.68 (-0.85 to -0.50)) whereas three other pain trials reported low or no effect (SMD -0.13 (-0.28 to 0.03)). The pooled effect on nausea was small, but consistent. The effects on phobia and asthma were very uncertain due to high risk of bias. There was no statistically significant effect of placebo interventions in the seven other clinical conditions investigated in three trials or more: smoking, dementia, depression, obesity, hypertension, insomnia and anxiety, but confidence intervals were wide.Meta-regression analyses showed that larger effects of placebo interventions were associated with physical placebo interventions (e.g. sham acupuncture), patient-involved outcomes (patient-reported outcomes and observer-reported outcomes involving patient cooperation), small trials, and trials with the explicit purpose of studying placebo. Larger effects of placebo were also found in trials that did not inform patients about the possible placebo intervention. Authors' conclusions: We did not find that placebo interventions have important clinical effects in general. However, in certain settings placebo interventions can influence patient-reported outcomes, especially pain and nausea, though it is difficult to distinguish patient-reported effects of placebo from biased reporting. The effect on pain varied, even among trials with 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.