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| Hpathy Ezine - January, 2006 | ||||
Is
the Randomized Double Blind Placebo Controlled Trial
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| The RCT and Homeopathy: Randomization Randomization is a simple procedure that distributes trial participants between control and experimental groups, as suggested by the name, on a random basis. In this way, any factors that tend toward a particular response to treatment are excluded from influencing the frequency of that response in either of the groups. In the event there is still concern that one group or the other is, on the whole, more responsive or more resistant to the treatment under investigation, the trial may be split in two, so that the sides are switched, and in the second half of the trial the experimental group becomes the control group, and vice versa. This ‘crossover’ technique effectively controls for vulnerability of the RCT to inequalities between the groups, at least in a trial of conventional treatments. But in the homeopathic trial, in the circumstances discussed above,
the crossover simply won’t work. This is clearly the case,
since, as we discussed, some effects in enhancing placebo response
effect only the placebo group. Thus, in a crossover, although
the populations of the control and experimental groups are exchanged,
the effects of the trial situation on outcomes remains
the same – the effects are specific to the nature
of the “control” itself, not to the characteristics
of the participants who populate it. A Second Layer of Observation – Selecting and Interpreting Outcomes Simply, numbers do not speak for themselves. Two examples will provide a sample of problems that may be encountered designing a trial, and interpreting its outcomes, in the absence of reasonable clinical (i.e., not statistical) guidelines. In a recent article,2 Brien et. al. use a list of symptoms as the basis for evaluating response to the homeopathic remedy. On this list, 5 symptoms were real symptoms found in the proving record for the test remedy; the other 5 symptoms were not proving symptoms of that remedy: thus, if a participant reported he had experienced one of the latter 5 symptoms, it was clear his response was a placebo response, rather than a response to the remedy. In measuring outcomes, however, the authors established a procedure in which verum symptoms were not counted if that same participant produced two symptoms from the second group. Though they did not clarify the point, it is clear they assumed that since that participant showed a fairly marked suggestibility, in producing two placebo responses, it was safe to assume that the supposed verum response was itself merely a result of suggestibility. The problems with such an approach seem fairly obvious: without any knowledge whatsoever of how symptoms form in response to homeopathic remedies, nor even any “objective” proof that the remedies do or do not provoke such symptomatic responses, these authors introduced a completely arbitrary definition that resulted in a reduction in the “efficacy” of the homeopathic remedy, as reflected statistically through the blinded trial. This frankly incredible presumption reflects, furthermore, the inability of the randomized, blinded trial to understand trial outcomes, in short, to do anything more than count them. In the present case, the RCT reduced verum response – equally, to be sure (statistically) – in both the experimental and the control group, but obviously could not determine whether the verum symptom was a response to the real medicine, or to the sugar pill, in the case of the verum prover. In other words, reduction of count for a participant in the control group is unobjectionable: there is no way that the apparent verum symptom could have been a response to the real medicine, because the participant did not receive the real medicine. But, reduction of count for a participant in the experimental group does nothing less than strike evidence of efficacy from the record! All of us – patients, trial participants, authors, and statisticians – will respond to some medications, and not respond as much or as well to others, and will also respond to placebo. The presence of a placebo response in a participant in the verum group, in short, has no bearing on whether an accompanying verum response is truly a response to verum, as opposed to a placebo response that coincidentally mimics a verum response. Brien et. al. also note that “…consumption [by trial participants] of alcohol and possible undisclosed recreational drug intake may minimize any homeopathic response. Lifestyle factors may colour the outcome, e.g., Belladonna-related symptoms of ‘headache’ and ‘sinking and rising sensation in his head’ were reported following high alcohol intake for the previous evening.” Yet, in their conclusions, the authors ignore their own caveats, citing the statistically negative outcome of the trial, for homeopathy, and recommending “…future research should focus on … those factors such as the therapeutic relationship and the process of the homeopathic consultation that may mediate the apparent success of the homeopathic process.” Clearly, these authors demonstrate the point, that conclusions drawn from the statistical outcomes of the trial need not accurately reflect the significance of those numbers. Discussion: Implications for Research In the present paper, four situations have been discussed, that impact our ability to review results of objective research, with confidence that findings accurately reflect events in the real world. Normally, such research is, of course, subject to review for determining whether findings are statistically reliable. As a simple example, one might consider whether the sample size was sufficient to permit a confident statistical outcome, since too small a sample will be vulnerable to wild fluctuations in trial results: in the event a medical trial had, for example, five participants, 3 of whom showed ‘positive’ for a medicinal effect, that would reflect a 60% success rate for the medication. Yet a swing of one case, from positive to negative response, would alter the outcome to reflect a 60% failure rate for the medicine in question. The present review of randomized trials, however, suggests that observational assessment of the trial design and outcomes – a kind of “clinical” evaluation of the experiment – is needed to ensure the logical, or “experiential” aspect of the trial does not introduce confounders of its own. We have, as stated, already identified four such potential confounders:
In summary, these examples illustrate a variety of ways in which the objectivity of the randomized, blinded trial may be compromised. The first three situations are peculiar to the situation of the homeopathic proving trial, or treatment trial. These paradoxical results are made possible by the fact that homeopathic remedies produce symptoms rather than just eliminate them, as with conventional medications. These results are also encouraged because, in context of the large numbers of symptomatic responses associated with homeopathic remedies, it becomes cumbersome and perhaps altogether impractical (financially or logistically) to implement a thoroughgoing symptom harvest. In an efficacy trial of conventional medications, on the other hand, the focus of the action of medicine is narrowly circumscribed, therefore easier and more practical to observe. The decisions of the research team, to discount verum symptoms in case 3, above, and to disregard acknowledged confounders in case 4, represent, on the other hand, a type of bias introduced into research proceedings through the medium of human error – poor definition of terms, failure to address all aspects of the research situation in their summary. In short, these interpretative errors can have an effect on trials in homeopathic research as well as in trials of conventional medication. What seems perfectly clear, is that future research efforts should be directed to evaluating the efficacy of randomized and blinded research trial itself, and should seek to identify as many situations as possible in order to measure the impact of therapeutic dynamics (e.g., the homeopathic mechanisms of action) and logical errors of the research team, on the accuracy – the credibility – of statistical and analytical results of published trials. It is not accidental, nor unimportant, that our intuitive grasp of the situation agrees with the outcome of the conventional trial: we see that aspirin works, and the trial demonstrates that this is true – perception is vindicated. It is frankly beyond dispute, that we should be able to expect the same agreement as between perception and experimental outcomes, in the case of the homeopathic trial, or, failing this, we have a right to expect a responsible examination of the sources of disparity. I believe the present paper represents an important step in that direction. Conclusion The RCT has been involved as a major player in scientific research in recent decades. There certainly can be no justification in questioning the profound power of this research technology for controlling bias, in the effort to produce objective, and, more important, reliable, or credible, observational data. But, in case the skeptics in our midst haven’t noticed, the concept of the RCT, as an idealized instrument capable of easily measuring clinical process in homeopathy, has just been falsified. This does not mean that the RCT can not be used to measure homeopathic action; indeed, at present, it is simply too early to tell, how significant the errors will be, that are introduced into the blinded statistical study by the transactions between blinding, placebo control, and those characteristics of homeopathic practice that distinguish it from conventional medicine. This is the first time, after all, that such paradoxical results have been shown in the workings of the double blinded trial. There is more to be done, to satisfy ourselves that the now dented instrument of the RCT can be relied on in all of the applications to which its faithful wish to put it, but we are not yet at the point, either, of concluding that more careful and more skillful design of trial protocols can’t overcome the obstacles in the path of reliable – credible – research. In short, to value something highly, even to hold it very dear, is not to cherish it as an icon. It does not do to wave your magic wand, and chant three times, slowly, “Randomized! Double Blind! Placebo Controlled! Trial!! Randomized! Double Blind…!!” It does not generate confidence that the outcome of a trial can be trusted, just because its numbers add up; one can give a calculator to a child, but all one accomplishes by that, is to limit what one can expect from the calculator. One quality the child lacks is perspective. Another is experience. These are keystones of knowledge and understanding. To the child, however, they don’t matter, as all he is concerned about are his numbers. But in science, we need to know if the numbers apply to real objects, and real processes, in the real world. As I believe I have clearly demonstrated – far beyond, frankly, what I expected to be able to do when I began – current practice in statistical research is as self-absorbed as a child, preoccupied with discovery of its own unfolding powers, but not yet at a stage of maturity as to grasp its relations to external reality. I have to frankly laugh, though it be rude, at the thought that adherents of this methodology, in applying it to research into homeopathy, have managed to find not one, but at least four mechanisms (that I have identified) by which production of placebo response is enhanced in the Randomized Trial! Truly, it is a wonder that homeopathy does even as well as placebo in these trials, let alone outperform it! Perhaps it all has something to do with the fact that so many researchers, as it appears, prefer to think of themselves as skeptics, rather than scientists, and to busy themselves more with doubt than with curiosity. And certainly, it has to do with the fact, that these self-same skeptics eschew the specialized knowledge of professionals in the fields they pretend to investigate. “Nonsense!” one can almost hear them saying. “If there were radio sources in deep space, surely even a poorly designed optical telescope would have found some piece of evidence for it by now!” But perhaps one day, when someone combines understanding with calculation, and reason with randomization, the truth will finally be revealed. To be fair, it should be commented that statistical research, after all, is still a very young branch of science, and that there are, for good reason, no names amongst its practitioners that have been elevated to the pantheon, as Hahnemann to homeopathy, Freud, Jung, Adler, or Pavlov to psychology, Darwin or Mendel to biology, Einstein or Bohr to physics. This reflects, frankly, that there has as yet been no one to grasp the broader sweep and implications of statistical methodology in its various applications. It is after all the merest blink of an eye since it was realized, in the wake of the thalidomide scandal, that second generation testing should be a standard practice in such trials. Further, the ‘profession’ of statistical research hasn’t even been successful in helping its audience understand that ‘efficacy’ is unrelated to ‘safety,’ and that the RCT has nothing to say about the latter. Simply put, this is still a youthful science, a useful and promising one, to be sure, but immature, and even naive, zealous, and self-satisfied, in the way of the young. One only hopes that, as they continue to stump for repression of medical practices they don’t like, for whatever personal motives they may have, these supposed skeptics will at least report honestly to the public and to government leaders, that their claim to perfect objectivity has been slain. References 1 Shere, Neil D. 2005. Proving Homeopathy:, hpathy ezine (April), 2 Brien, et. al. 2003. Ultramolecular homeopathy has no observable clinical effects. A randomized, double-blind, placebo-controlled proving trial of Belladonna 30C.” British Journal of Clinical Pharmacology, 56:562-568. |
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