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Of course, while there are similarities between the positions adopted in the "positivism/scientism versus non-positivism/scientism" and "Western medicine versus alternative medicine" debates, I suppose that one main difference is however that the latter is not just a theoretical debate but involves people's health and lives.

As was mentioned earlier, the general impression is perhaps that while Western medicine, which generally has its roots in Western societies, is scientifically proven, TCM, or alternative medicine, is however not as scientifically proven. The former is thus regarded as the dominant mainstream model of medical treatment while non-Western medical knowledge or treatment is regarded as "alternative medicine".

The process by which the above impression was created was, according to the postcolonial theorists, a highly political one. Essentially, it may be argued that along with their political colonisation of non-European territories in the past, the European/Western colonialists also colonised the minds of those living in those territories. This means that along with colonisation, traditional forms of knowledge, including medical knowledge, and cultures in the colonised terrorities were relegated to a non-dominant, if not inferior, position vis-a-vis Western knowledge and culture. And as postcolonial theorists may argue, the legacy and aftermath of this process is still felt today and efforts should be made to reverse it.

In light of the above, the increased push to have non-Western forms of medical treatment be recognised as an equally valid model of medical treatment besides that of Western medicine may be seen as part of the effort to reverse the dominance of Western knowledge and culture set in place during the colonial period. Of course, this push to reverse Western dominance is especially relevant in recent times, in light of the economic and political rise of non-Western powers such as China and India (interestingly enough, to the best of my knowledge, when talking about "alternative medicine", people are usually referring to traditional Indian or Chinese medical treatments and not really traditional African medical treatment).

Here, it is worthwhile to pause and think for a while: if it is recognised that Western and non-Western medicine are different but equally valid models of medical treatment, would they be complimentary or competing models? Or would they be just different models?

Moving on, so far it would seem that , for at least the foreseeable future, Western medicine will retain its dominant "mainstream" position but who knows what the future may hold?

This is also the fallacy of the perfect solution – since science-based medicine is not perfect, there is no legitimate basis for criticism of any modality.

The SMA does not encourage its members to refer to alternative medicine practitioners. But we have to be realistic. They exist and are here to stay. Most public hospitals already offer acupuncture services. Several have TCM clinics on their premises. Continuing this "iron curtain" of no formal communication between doctors and alternative medicine practitioners is impractical and anachronistic.

Finally, many alternative medicine forms are steeped in cultural and religious beliefs, such as TCM and ayurvedic medicine. From the perspective of safeguarding social cohesion in Singapore, getting the local medical profession to collectively criticise various alternative medicine modalities is unwise.

In Singapore's social context, journalists should not try to pit one group of caregivers against another. It is best for an impartial and respected body such as the Government to step forward to decide what is safe and unsafe for patients. Dr Abdul Razakjr Omar Honorary Secretary Singapore Medical Association (SMA)

The discomfort of many clinicians comes from the fact that the data are derived mainly from clinical trials, which exclude the elderly and people with multiple problems. Yet in the “real world” of medicine, particularly general practice, most patients are elderly and most have multiple problems. So can the “evidence” be applied to these patients? Unthinking application of multiple evidence-based guidelines may cause serious problems, says Mike Rawlins, chairman of NICE.

There has always been anxiety that the zealots would insist evidence was all that was needed to make a decision, and in its early days NICE seemed to take this line. Critics quickly pointed out, however, that patients had things called values, as did clinicians, and that clinicians and patients needed to blend their values with the evidence in a way that was often a compromise.

Social scientists have tended to be wary of the reductionist approach of evidence-based medicine and have wanted a much broader range of information to be admissible.

Evidence-based medicine has been at its most confident when evaluating drug treatments, but many interventions in health care are far more complex than simply prescribing a drug. Insisting on randomized trials to evaluate these interventions may not only be inappropriate, but also misleading. Interventions may be stamped “ineffective” by the hardliners when they actually might offer substantial benefits. Then there is the constant confusion between “evidence of absence of effectiveness” with “absence of evidence of effectiveness”—two very different things.

even some of the strongest proponents of evidence-based medicine have become uneasy, as we have increasing evidence that drug companies have managed to manipulate data. In the heartland of evidence-based medicine—drug trials—the “evidence” may be unreliable and misleading.

All this doesn’t mean that evidence-based medicine should be abandoned. It means, rather, that we must never forget the complex relationship between evidence and truth.

There are many forms of alternative medicine out there which are being sold to unsuspecting patients. Just because they are a part of our "cultural beliefs" or that they are renting shop spaces in our hospitals does not mean that doctors as a profession must accept them or not speak up against them. If you know that certain forms of alternative medicine are ineffective or indeed potentially harmful, but choose not to advocate against it because you do not want to be seen as "self-serving", what does that say about your strength of character? Will we rather our patients be harmed by such therapy than we be falsely accused of being self-serving?

If we claim to be a profession that is built upon science, if we claim to be advocates for our patients, then we must speak up even when we know it will not be well-received, even when we know it will offend.

SMA needs to ask itself whether it will choose what is expedient over what is right, and whether it is more important to be popular or to be intellectually honest.

Mike’s thesis is essentially: Silly skeptics, it’s impossible to OD on homeopathy!

1. “Notice that they never consume their own medicines in large doses? Chemotherapy? Statin drugs? Blood thinners? They wouldn’t dare drink those.

Of course we wouldn’t. Steven Novella rightly points out that, though Mike thinks he’s being clever here, he’s actually demonstrating a lack of understanding for what the 10:23 campaign is about by using a straw man. Mike later issues a challenge for skeptics to drink their favourite medicines while he drinks homeopathy. Since no one will agree to that for the reasons explained above, he can claim some sort of victory — hence his smugness. But no one is saying that drugs aren’t harmful.

The difference between medicine and poison is in the dose. The vitamins and herbs promoted by the CAM industry are just as potentially harmful as any pharmaceutical drug, given enough of it. Would Adams be willing to OD on the vitamins or herbal remedies that he sells?

Even Adams’ favorite panacea, vitamin D, is toxic if you take enough of it (just ask Gary Null). Notice how skeptics don’t consume those either, because that is not the point they’re making.

The point of these demonstrations is that homeopathy has nothing in it, has no measurable physiological effects, and does not do what is advertised on the package.

2. “Homeopathy, you see, isn’t a drug. It’s not a chemical.” Well, he’s got that right. “You know the drugs are kicking in when you start getting worse. Toxicity and conventional medicine go hand in hand.” [emphasis his]

Here I have to wonder if Adams knows any people with diabetes, AIDS, or any other illness that used to mean a death sentence before the significant medical advances of the 20th century that we now take for granted. So far he seems to be a firm believer in the false dichotomy that drugs are bad and natural products are good, regardless of what’s in them or how they’re used (as we know, natural products can have biologically active substances and effectively act as impure drugs – but leave it to Adams not to get bogged down with details). There is nothing to support the assertion that conventional medicine is nothing but toxic symptom-inducers.

3-11. “But homeopathy isn’t a chemical. It’s a resonance. A vibration, or a harmony. It’s the restructuring of water to resonate with the particular energy of a plant or substance. We can get into the physics of it in a subsequent article, but for now it’s easy to recognize that even from a conventional physics point of view, liquid water has tremendous energy, and it’s constantly in motion, not just at the molecular level but also at the level of its subatomic particles and so-called “orbiting electrons” which aren’t even orbiting in the first place. Electrons are vibrations and not physical objects.” [emphasis his]

This is Star Trek-like technobabble – lots of sciency words

if something — anything — has an effect, then that effect is measurable by definition. Either something works or it doesn’t, regardless of mechanism. In any case, I’d like to see the well-documented series of research that conclusively proves this supposed mechanism. Actually, I’d like to see any credible research at all. I know what the answer will be to that: science can’t detect this yet. Well if you agree with that statement, reader, ask yourself this: then how does Adams know? Where did he get this information? Without evidence, he is guessing, and what is that really worth?

13. “But getting back to water and vibrations, which isn’t magic but rather vibrational physics, you can’t overdose on a harmony. If you have one violin playing a note in your room, and you add ten more violins — or a hundred more — it’s all still the same harmony (with all its complex higher frequencies, too). There’s no toxicity to it.” [emphasis his]

Homeopathy has standard dosing regimes (they’re all the same), but there is no “dose” to speak of: the ingredients have usually been diluted out to nothing. But Adams is also saying that homeopathy doesn’t work by dose at all, it works by the properties of “resonance” and “vibration”. Then why any dosing regimen? To maintain the resonance? How is this resonance measured? How long does the “resonance” last? Why does it wear off? Why does he think televisions can inactivate homeopathy? (I think I might know the answer to that last one, as electronic interference is a handy excuse for inefficacy.)

“These skeptics just want to kill themselves… and they wouldn’t mind taking a few of you along with them, too. Hence their promotion of vaccines, pharmaceuticals, chemotherapy and water fluoridation. We’ll title the video, “SKEPTICS COMMIT MASS SUICIDE BY DRINKING PHARMACEUTICALS AS IF THEY WERE KOOL-AID.” Jonestown, anyone?”

“Do you notice the irony here? The only medicines they’re willing to consume in large doses in public are homeopathic remedies! They won’t dare consume large quantities of the medicines they all say YOU should be taking! (The pharma drugs.)” [emphasis his]

what Adams seems to have missed is that the skeptics have no intention of killing themselves, so his bizarre claims that the 10:23 participants are psychopathic, self-loathing, and suicidal makes not even a little bit of sense. Skeptics know they aren’t going to die with these demonstrations, because homeopathy has no active ingredients and no evidence of efficacy.

The inventor of homeopathy himself, Samuel Hahnemann believed that excessive doses of homeopathy could be harmful (see sections 275 and 276 of his Organon). Homeopaths are pros at retconning their own field to fit in with Hahnemann’s original ideas (inventing new mechanisms, such as water memory and resonance, in the face of germ theory). So how does Adams reconcile this claim?

The biggest effect was with those people who scored high on the "God as locus of health control" measure - that means people who agreed with statements like "Whether or not my HIV disease improves is up to God." Although this had no effect on medication taking at 3 months, the halfway point of the study, by the end of the study (at 6 months) people who scored high on this measure were 42% less likely to be taking their medication regularly.

This study is interesting because these aren't folks who have any crazy ideas that medicine is useless. Remember, they signed up to take part in a drug study, presumably because they thought they might benefit. What's more, they stayed in the study right to the end, and did take their medicine most of the time. It's just that they were more likely than others to 'forget' it.

Now, this is a complicated picture in other ways. People who are at death's door (unlike the mostly healthy people in this study) seem to be more likely to ask for 'heroic' interventions to try to keep them alive if they have strong beliefs in God's will.

Maybe confronting your own imminent death triggers some reconsiderations about the mysterious workings of the almighty!

Medical science, when it works well, tends to progress from basic science, to small pilot studies, to larger randomized studies, and then–only then–to those big, rigorous, insanely expensive randomized, double-blind, placebo-controlled trials. Dr. Spector mentions hierarchies of evidence, but he seems to fall into a false dichotomy, namely that if it’s not Level I evidence, it’s crap. The problem is, as Mark pointed out, in medicine we often don’t have Level I evidence for many questions. Indeed, for some questions, we will never have Level I evidence. Clinical medicine involves making decisions in the midst of uncertainty, sometimes extreme uncertainty.

Dr. Spector then proceeds to paint a picture of reckless physicians proceeding on crappy studies to pump women full of hormones. Actually, it was more than a bit more complicated on than that. That was the time when I was in my medical training, and I remember the discussions we had regarding the strength (or lack thereof) of the epidemiological data and the lack of good RCTs looking at HRT. I also remember that nothing works as well to relieve menopausal symptoms as HRT, an observation we have been reminded of again since 2003, which is the year when the first big study came out implicating HRT in increasing the risk of breast cancer (more later).

I found a rather fascinating editorial in the New England Journal of Medicine from more than 20 years ago that discussed the state of the evidence back then with regard to estrogen and breast cancer: Evidence that estrogen increases the risk of breast cancer has been surprisingly difficult to obtain. Clinical and epidemiologic studies and studies in animals strongly suggest that endogenous estrogen plays a part in causing breast cancer. If so, exogenous estrogen should be a potent promoter of breast cancer. Although more than 20 case–control and prospective studies of the relation of breast cancer and noncontraceptive estrogen use have failed to demonstrate the expected association, relatively few women in these studies used estrogen for extended periods. Studies of the use of diethylstilbestrol and oral contraceptives suggest that a long exposure or latency may be necessary to show any association between hormone use and breast cancer. In the Swedish study, only six years of follow-up was needed to demonstrate an increased risk of breast cancer with the postmenopausal use of estradiol. It should be noted, however, that half the women in the subgroup that provided detailed data on the duration of hormone use had taken estrogen for many years before their base-line prescription status was defined. The duration of estrogen exposure in these women before the diagnosis of breast cancer was probably seriously underestimated; a short latency cannot be attributed to estradiol on the basis of these data. Other recent studies of the use of noncontraceptive estrogen suggest a slightly increased risk of breast cancer after 15 to 20 years’ use.

even now, the evidence is conflicting regarding HRT and breast cancer, with the preponderance of evidence suggesting that mixed HRT (estrogen and progestin) significantly increases the risk of breast cancer, while estrogen-alone HRT very well might not increase the risk of breast cancer at all or (more likely) only very little. Indeed, I was just at a conference all day Saturday where data demonstrating this very point were discussed by one of the speakers. None of this stops Dr. Spector from categorically labeling estrogen as a “carcinogen that causes breast cancers that kill women.” Maybe. Maybe not. It’s actually not that clear. The problem, of course, is that, consistent with the first primary reports of WHI results, the preponderance of evidence finding health risks due to HRT have indicted the combined progestin/estrogen combinations as unsafe.

Given the growing evidence that ghostwriting has been used to promote HT and other highly promoted drugs, the medical profession must take steps to ensure that prescribers renounce participation in ghostwriting, and to ensure that unscrupulous relationships between industry and academia are avoided rather than courted.

Twenty-five out of 32 highly paid consultants to medical device companies in 2007, or their publishers, failed to reveal the financial connections in journal articles the following year, according to a [recent] study.

The study compared major payments to consultants by orthopedic device companies with financial disclosures the consultants later made in medical journal articles, and found them lacking in public transparency. “We found a massive, dramatic system failure,” said David J. Rothman, a professor and president of the Institute on Medicine as a Profession at Columbia University, who wrote the study with two other Columbia researchers, Susan Chimonas and Zachary Frosch.

Carl Elliot in The Chronicle of Higher Educations: The Secret Lives of Big Pharma's 'Thought Leaders':

See also a related NYTimes report -- Menopause, as Brought to You by Big Pharma by Natasha Singer and Duff Wilson -- from December 2009. Duff Wilson reports in the NYTimes: Medical Industry Ties Often Undisclosed in Journals:

Pharmaceutical companies hire KOL's [Key Opinion Leaders] to consult for them, to give lectures, to conduct clinical trials, and occasionally to make presentations on their behalf at regulatory meetings or hearings.

KOL's do not exactly endorse drugs, at least not in ways that are too obvious, but their opinions can be used to market them—sometimes by word of mouth, but more often by quasi-academic activities, such as grand-rounds lectures, sponsored symposia, or articles in medical journals (which may be ghostwritten by hired medical writers). While pharmaceutical companies seek out high-status KOL's with impressive academic appointments, status is only one determinant of a KOL's influence. Just as important is the fact that a KOL is, at least in theory, independent. [...]

Mr [Andrew] Baum [of Morgan Stanley] argues that the solution for drug companies is to share the risks of research with others. That means reducing in-house investment in research, and instead partnering and licensing experimental medicines from smaller companies after some of the early failures have been eliminated.

Chas Bountra of Oxford university calls for a more radical partnership combining industry and academic research. “What we are trying to do is just too difficult,” he says. “No one organisation can do it, so we have to pool resources and expertise.” He suggests removing intellectual property rights until a drug is in mid-stage testing in humans, which would make academics more willing to co-operate because they could publish their results freely. The sharing of data would enable companies to avoid duplicating work.

The challenge is for academia and biotech companies to fill the research gap. Mr Ratcliffe argues that after a lull in 2009 and 2010, private capital is returning to the sector – as demonstrated by a particular buzz at JPMorgan’s new year biotech conference in California.

Patrick Vallance, senior vice-president for discovery at GSK, is cautious about deferring patents until so late, arguing that drug companies need to be able to protect their intellectual property in order to fund expensive late-stage development. But he too is experimenting with ways to co-operate more closely with academics over longer periods. He is also championing the “externalisation” of the company’s pipeline, with biotech and university partners accounting for half the total. GSK has earmarked £50m to support fledgling British companies, many “wrapped around” the group’s sites. One such example is Convergence, a spin-out from a GSK lab researching pain relief.

Big pharmaceutical companies are scrambling to find ways to overcome the loss of tens of billions of dollars in revenue as patents on top-selling drugs run out. Many sound similar notes about encouraging entrepreneurialism in their ranks, making smart deals and capitalizing on emerging-market growth, But their actual plans are often quite different—and each carries significant risks. Novartis AG, for instance, is so convinced that diversification is the best course that the company has a considerable business selling low-priced generics. Meantime, Bristol-Myers Squibb Co. has decided to concentrate on innovative medicines, shedding so many nonpharmaceutical units that it' has become midsize. GlaxoSmithKline PLC is still investing in research, but like Pfizer it has narrowed the range of disease areas in which it's seeking new treatments. Underlying the divergence is a deep-seated philosophical dispute over the merits of the heavy investment that companies must make to discover new drugs. By most estimates, bringing a new molecule to market costs drug makers more than $1 billion. Industry officials have been engaged in a vigorous debate over whether the investment is worth it, or whether they should leave it to others whose work they can acquire or license after a demonstration of strong potential.

To what extent can approached to innovation influence the trend line in the graph above?  I don't think that anyone really knows the answer.  The different approaches being taken by Merck and Pfizer, for instance, represent a real world policy experiment: The contrast between Merck and Pfizer reflects the very different personal approaches of their CEOs. An accountant by training, Mr. Read has held various business positions during a three-decade career at Pfizer. The 57-year-old cited torcetrapib, a cholesterol medicine that the company spent more than $800 million developing but then pulled due to safety concerns, as an example of the kind of wasteful spending Pfizer would avoid. "We're going to have metrics," Mr. Read said. He wants Pfizer to stop "always investing on hope rather than strong signals and the quality of the science, the quality of the medicine." Mr. Frazier, 56, a Harvard-educated lawyer who joined Merck in 1994 from private practice, said the company was sticking by its own troubled heart drug, vorapaxar. Mr. Frazier said he wanted to see all of the data from the trials before rushing to judgment. "We believe in the innovation approach," he said.

Of the 49 articles, 45 claimed to have uncovered effective interventions. Thirty-four of these claims had been retested, and 14 of these, or 41 percent, had been convincingly shown to be wrong or significantly exaggerated. If between a third and a half of the most acclaimed research in medicine was proving untrustworthy, the scope and impact of the problem were undeniable. That article was published in the Journal of the American Medical Association. [here's the link.]

David Freedman -- has quite a bit on the sociology of research in medical science. Here are a few quotes:

Even when the evidence shows that a particular research idea is wrong, if you have thousands of scientists who have invested their careers in it, they’ll continue to publish papers on it,” he says. “It’s like an epidemic, in the sense that they’re infected with these wrong ideas, and they’re spreading it to other researchers through journals.”

the peer-review process often pressures researchers to shy away from striking out in genuinely new directions, and instead to build on the findings of their colleagues (that is, their potential reviewers) in ways that only seem like breakthroughs—as with the exciting-sounding gene linkages (autism genes identified!) and nutritional findings (olive oil lowers blood pressure!) that are really just dubious and conflicting variations on a theme.

The ultimate protection against research error and bias is supposed to come from the way scientists constantly retest each other’s results—except they don’t. Only the most prominent findings are likely to be put to the test, because there’s likely to be publication payoff in firming up the proof, or contradicting it.

Doctors may notice that their patients don’t seem to fare as well with certain treatments as the literature would lead them to expect, but the field is appropriately conditioned to subjugate such anecdotal evidence to study findings.

[B]eing wrong in science is fine, and even necessary—as long as scientists recognize that they blew it, report their mistake openly instead of disguising it as a success, and then move on to the next thing, until they come up with the very occasional genuine breakthrough. But as long as careers remain contingent on producing a stream of research that’s dressed up to seem more right than it is, scientists will keep delivering exactly that.

Experts in the math of probability and statistics are well aware of these problems and have for decades expressed concern about them in major journals. Over the years, hundreds of published papers have warned that science’s love affair with statistics has spawned countless illegitimate findings. In fact, if you believe what you read in the scientific literature, you shouldn’t believe what you read in the scientific literature.

“There are more false claims made in the medical literature than anybody appreciates,” he says. “There’s no question about that.”Nobody contends that all of science is wrong, or that it hasn’t compiled an impressive array of truths about the natural world. Still, any single scientific study alone is quite likely to be incorrect, thanks largely to the fact that the standard statistical system for drawing conclusions is, in essence, illogical. “A lot of scientists don’t understand statistics,” says Goodman. “And they don’t understand statistics because the statistics don’t make sense.”

In 2007, for instance, researchers combing the medical literature found numerous studies linking a total of 85 genetic variants in 70 different genes to acute coronary syndrome, a cluster of heart problems. When the researchers compared genetic tests of 811 patients that had the syndrome with a group of 650 (matched for sex and age) that didn’t, only one of the suspect gene variants turned up substantially more often in those with the syndrome — a number to be expected by chance.“Our null results provide no support for the hypothesis that any of the 85 genetic variants tested is a susceptibility factor” for the syndrome, the researchers reported in the Journal of the American Medical Association.How could so many studies be wrong? Because their conclusions relied on “statistical significance,” a concept at the heart of the mathematical analysis of modern scientific experiments.

Statistical significance is a phrase that every science graduate student learns, but few comprehend. While its origins stretch back at least to the 19th century, the modern notion was pioneered by the mathematician Ronald A. Fisher in the 1920s. His original interest was agriculture. He sought a test of whether variation in crop yields was due to some specific intervention (say, fertilizer) or merely reflected random factors beyond experimental control.Fisher first assumed that fertilizer caused no difference — the “no effect” or “null” hypothesis. He then calculated a number called the P value, the probability that an observed yield in a fertilized field would occur if fertilizer had no real effect. If P is less than .05 — meaning the chance of a fluke is less than 5 percent — the result should be declared “statistically significant,” Fisher arbitrarily declared, and the no effect hypothesis should be rejected, supposedly confirming that fertilizer works.Fisher’s P value eventually became the ultimate arbiter of credibility for science results of all sorts

But in fact, there’s no logical basis for using a P value from a single study to draw any conclusion. If the chance of a fluke is less than 5 percent, two possible conclusions remain: There is a real effect, or the result is an improbable fluke. Fisher’s method offers no way to know which is which. On the other hand, if a study finds no statistically significant effect, that doesn’t prove anything, either. Perhaps the effect doesn’t exist, or maybe the statistical test wasn’t powerful enough to detect a small but real effect.

Soon after Fisher established his system of statistical significance, it was attacked by other mathematicians, notably Egon Pearson and Jerzy Neyman. Rather than testing a null hypothesis, they argued, it made more sense to test competing hypotheses against one another. That approach also produces a P value, which is used to gauge the likelihood of a “false positive” — concluding an effect is real when it actually isn’t. What  eventually emerged was a hybrid mix of the mutually inconsistent Fisher and Neyman-Pearson approaches, which has rendered interpretations of standard statistics muddled at best and simply erroneous at worst. As a result, most scientists are confused about the meaning of a P value or how to interpret it. “It’s almost never, ever, ever stated correctly, what it means,” says Goodman.

experimental data yielding a P value of .05 means that there is only a 5 percent chance of obtaining the observed (or more extreme) result if no real effect exists (that is, if the no-difference hypothesis is correct). But many explanations mangle the subtleties in that definition. A recent popular book on issues involving science, for example, states a commonly held misperception about the meaning of statistical significance at the .05 level: “This means that it is 95 percent certain that the observed difference between groups, or sets of samples, is real and could not have arisen by chance.”

That interpretation commits an egregious logical error (technical term: “transposed conditional”): confusing the odds of getting a result (if a hypothesis is true) with the odds favoring the hypothesis if you observe that result. A well-fed dog may seldom bark, but observing the rare bark does not imply that the dog is hungry. A dog may bark 5 percent of the time even if it is well-fed all of the time. (See Box 2)

Another common error equates statistical significance to “significance” in the ordinary use of the word. Because of the way statistical formulas work, a study with a very large sample can detect “statistical significance” for a small effect that is meaningless in practical terms. A new drug may be statistically better than an old drug, but for every thousand people you treat you might get just one or two additional cures — not clinically significant. Similarly, when studies claim that a chemical causes a “significantly increased risk of cancer,” they often mean that it is just statistically significant, possibly posing only a tiny absolute increase in risk.

Statisticians perpetually caution against mistaking statistical significance for practical importance, but scientific papers commit that error often. Ziliak studied journals from various fields — psychology, medicine and economics among others — and reported frequent disregard for the distinction.

“I found that eight or nine of every 10 articles published in the leading journals make the fatal substitution” of equating statistical significance to importance, he said in an interview. Ziliak’s data are documented in the 2008 book The Cult of Statistical Significance, coauthored with Deirdre McCloskey of the University of Illinois at Chicago.

Multiplicity of mistakesEven when “significance” is properly defined and P values are carefully calculated, statistical inference is plagued by many other problems. Chief among them is the “multiplicity” issue — the testing of many hypotheses simultaneously. When several drugs are tested at once, or a single drug is tested on several groups, chances of getting a statistically significant but false result rise rapidly.

Recognizing these problems, some researchers now calculate a “false discovery rate” to warn of flukes disguised as real effects. And genetics researchers have begun using “genome-wide association studies” that attempt to ameliorate the multiplicity issue (SN: 6/21/08, p. 20).

Many researchers now also commonly report results with confidence intervals, similar to the margins of error reported in opinion polls. Such intervals, usually given as a range that should include the actual value with 95 percent confidence, do convey a better sense of how precise a finding is. But the 95 percent confidence calculation is based on the same math as the .05 P value and so still shares some of its problems.

Statistical problems also afflict the “gold standard” for medical research, the randomized, controlled clinical trials that test drugs for their ability to cure or their power to harm. Such trials assign patients at random to receive either the substance being tested or a placebo, typically a sugar pill; random selection supposedly guarantees that patients’ personal characteristics won’t bias the choice of who gets the actual treatment. But in practice, selection biases may still occur, Vance Berger and Sherri Weinstein noted in 2004 in ControlledClinical Trials. “Some of the benefits ascribed to randomization, for example that it eliminates all selection bias, can better be described as fantasy than reality,” they wrote.

Randomization also should ensure that unknown differences among individuals are mixed in roughly the same proportions in the groups being tested. But statistics do not guarantee an equal distribution any more than they prohibit 10 heads in a row when flipping a penny. With thousands of clinical trials in progress, some will not be well randomized. And DNA differs at more than a million spots in the human genetic catalog, so even in a single trial differences may not be evenly mixed. In a sufficiently large trial, unrandomized factors may balance out, if some have positive effects and some are negative. (See Box 3) Still, trial results are reported as averages that may obscure individual differences, masking beneficial or harm­ful effects and possibly leading to approval of drugs that are deadly for some and denial of effective treatment to others.

nother concern is the common strategy of combining results from many trials into a single “meta-analysis,” a study of studies. In a single trial with relatively few participants, statistical tests may not detect small but real and possibly important effects. In principle, combining smaller studies to create a larger sample would allow the tests to detect such small effects. But statistical techniques for doing so are valid only if certain criteria are met. For one thing, all the studies conducted on the drug must be included — published and unpublished. And all the studies should have been performed in a similar way, using the same protocols, definitions, types of patients and doses. When combining studies with differences, it is necessary first to show that those differences would not affect the analysis, Goodman notes, but that seldom happens. “That’s not a formal part of most meta-analyses,” he says.

Meta-analyses have produced many controversial conclusions. Common claims that antidepressants work no better than placebos, for example, are based on meta-analyses that do not conform to the criteria that would confer validity. Similar problems afflicted a 2007 meta-analysis, published in the New England Journal of Medicine, that attributed increased heart attack risk to the diabetes drug Avandia. Raw data from the combined trials showed that only 55 people in 10,000 had heart attacks when using Avandia, compared with 59 people per 10,000 in comparison groups. But after a series of statistical manipulations, Avandia appeared to confer an increased risk.

combining small studies in a meta-analysis is not a good substitute for a single trial sufficiently large to test a given question. “Meta-analyses can reduce the role of chance in the interpretation but may introduce bias and confounding,” Hennekens and DeMets write in the Dec. 2 Journal of the American Medical Association. “Such results should be considered more as hypothesis formulating than as hypothesis testing.”

Some studies show dramatic effects that don’t require sophisticated statistics to interpret. If the P value is 0.0001 — a hundredth of a percent chance of a fluke — that is strong evidence, Goodman points out. Besides, most well-accepted science is based not on any single study, but on studies that have been confirmed by repetition. Any one result may be likely to be wrong, but confidence rises quickly if that result is independently replicated.“Replication is vital,” says statistician Juliet Shaffer, a lecturer emeritus at the University of California, Berkeley. And in medicine, she says, the need for replication is widely recognized. “But in the social sciences and behavioral sciences, replication is not common,” she noted in San Diego in February at the annual meeting of the American Association for the Advancement of Science. “This is a sad situation.”

Most critics of standard statistics advocate the Bayesian approach to statistical reasoning, a methodology that derives from a theorem credited to Bayes, an 18th century English clergyman. His approach uses similar math, but requires the added twist of a “prior probability” — in essence, an informed guess about the expected probability of something in advance of the study. Often this prior probability is more than a mere guess — it could be based, for instance, on previous studies.

it basically just reflects the need to include previous knowledge when drawing conclusions from new observations. To infer the odds that a barking dog is hungry, for instance, it is not enough to know how often the dog barks when well-fed. You also need to know how often it eats — in order to calculate the prior probability of being hungry. Bayesian math combines a prior probability with observed data to produce an estimate of the likelihood of the hunger hypothesis. “A scientific hypothesis cannot be properly assessed solely by reference to the observational data,” but only by viewing the data in light of prior belief in the hypothesis, wrote George Diamond and Sanjay Kaul of UCLA’s School of Medicine in 2004 in the Journal of the American College of Cardiology. “Bayes’ theorem is ... a logically consistent, mathematically valid, and intuitive way to draw inferences about the hypothesis.” (See Box 4)

In many real-life contexts, Bayesian methods do produce the best answers to important questions. In medical diagnoses, for instance, the likelihood that a test for a disease is correct depends on the prevalence of the disease in the population, a factor that Bayesian math would take into account.

But Bayesian methods introduce a confusion into the actual meaning of the mathematical concept of “probability” in the real world. Standard or “frequentist” statistics treat probabilities as objective realities; Bayesians treat probabilities as “degrees of belief” based in part on a personal assessment or subjective decision about what to include in the calculation. That’s a tough placebo to swallow for scientists wedded to the “objective” ideal of standard statistics. “Subjective prior beliefs are anathema to the frequentist, who relies instead on a series of ad hoc algorithms that maintain the facade of scientific objectivity,” Diamond and Kaul wrote.Conflict between frequentists and Bayesians has been ongoing for two centuries. So science’s marriage to mathematics seems to entail some irreconcilable differences. Whether the future holds a fruitful reconciliation or an ugly separation may depend on forging a shared understanding of probability.“What does probability mean in real life?” the statistician David Salsburg asked in his 2001 book The Lady Tasting Tea. “This problem is still unsolved, and ... if it remains un­solved, the whole of the statistical approach to science may come crashing down from the weight of its own inconsistencies.”

For a complex and somewhat mysterious set of reasons, it is becoming increasingly difficult for experimental drugs to prove their superiority to sugar pills in RCTs

in recent years, however, has it become obvious that the abatement of symptoms in control-group volunteers — the so-called placebo effect — is worthy of study outside the context of drug trials, and is in fact profoundly good news to anyone but investors in Pfizer, Roche, and GlaxoSmithKline.

The emerging field of placebo research has revealed that the body’s repertoire of resilience contains a powerful self-healing network that can help reduce pain and inflammation, lower the production of stress chemicals like cortisol, and even tame high blood pressure and the tremors of Parkinson’s disease.

more and more studies each year — by researchers like Fabrizio Benedetti at the University of Turin, author of a superb new book called The Patient’s Brain, and neuroscientist Tor Wager at the University of Colorado — demonstrate that the placebo effect might be potentially useful in treating a wide range of ills. Then why aren’t doctors supposed to use it?

The medical establishment’s ethical problem with placebo treatment boils down to the notion that for fake drugs to be effective, doctors must lie to their patients. It has been widely assumed that if a patient discovers that he or she is taking a placebo, the mind/body password will no longer unlock the network, and the magic pills will cease to do their job.

For “Placebos Without Deception,” the researchers tracked the health of 80 volunteers with irritable bowel syndrome for three weeks as half of them took placebos and the other half didn’t.

In a previous study published in the British Medical Journal in 2008, Kaptchuk and Kirsch demonstrated that placebo treatment can be highly effective for alleviating the symptoms of IBS. This time, however, instead of the trial being “blinded,” it was “open.” That is, the volunteers in the placebo group knew that they were getting only inert pills — which they were instructed to take religiously, twice a day. They were also informed that, just as Ivan Pavlov trained his dogs to drool at the sound of a bell, the body could be trained to activate its own built-in healing network by the act of swallowing a pill.

In other words, in addition to the bogus medication, the volunteers were given a true story — the story of the placebo effect. They also received the care and attention of clinicians, which have been found in many other studies to be crucial for eliciting placebo effects. The combination of the story and a supportive clinical environment were enough to prevail over the knowledge that there was really nothing in the pills. People in the placebo arm of the trial got better — clinically, measurably, significantly better — on standard scales of symptom severity and overall quality of life. In fact, the volunteers in the placebo group experienced improvement comparable to patients taking a drug called alosetron, the standard of care for IBS. Meet the ethical placebo: a powerfully effective faux medication that meets all the standards of informed consent.

The study is hardly the last word on the subject, but more like one of the first. Its modest sample size and brief duration leave plenty of room for followup research. (What if “ethical” placebos wear off more quickly than deceptive ones? Does the fact that most of the volunteers in this study were women have any bearing on the outcome? Were any of the volunteers skeptical that the placebo effect is real, and did that affect their response to treatment?) Before some eager editor out there composes a tweet-baiting headline suggesting that placebos are about to drive Big Pharma out of business, he or she should appreciate the fact that the advent of AMA-approved placebo treatments would open numerous cans of fascinatingly tangled worms. For example, since the precise nature of placebo effects is shaped largely by patients’ expectations, would the advertised potency and side effects of theoretical products like Placebex and Therastim be subject to change by Internet rumors, requiring perpetual updating?

It’s common to use the word “placebo” as a synonym for “scam.” Economists talk about placebo solutions to our economic catastrophe (tax cuts for the rich, anyone?). Online skeptics mock the billion-dollar herbal-medicine industry by calling it Big Placebo. The fact that our brains and bodies respond vigorously to placebos given in warm and supportive clinical environments, however, turns out to be very real.

We’re also discovering that the power of narrative is embedded deeply in our physiology.

in the real world of doctoring, many physicians prescribe medications at dosages too low to have an effect on their own, hoping to tap into the body’s own healing resources — though this is mostly acknowledged only in whispers, as a kind of trade secret.

I should add that I am not criticising TCM per se. Only acupuncture, a facet of TCM, albeit its most dramatic, is being scrutinised here. Chinese herbology must be analysed on its own merits.Interestingly, although acupuncture may be TCM's poster boy today, the Chinese physician in days of yore would have looked askance at it. Instead, his practice and prestige were based upon his grasp of the Chinese pharmacopoeia.

Acupuncture was left to the shamans and blood letters. After all, it was grounded, not in the knowledge of which herbs were best for what conditions, but astrology.

In Giovanni Maciocia's 2005 book, The Foundations Of Chinese Medicine: A Comprehensive Text For Acupuncturists And Herbalists, there is a chart showing the astrological provenance of acupuncture. The chart shows how the 12 main acupuncture meridians and the 12 main body segments correspond to the 12 Houses of the Chinese zodiac.

In Chinese cosmology, all life is animated by a numinous force called qi, the flow of which mirrors the sun's apparent 'movement' during the year through the ecliptic. (The ecliptic is the imaginary plane of the earth's orbit around the sun).Moreover, everything in the Chinese zodiac is mirrored on Earth and in Man. This was taught even in the earliest systematised TCM text, the Yellow Emperor's Canon Of Medicine, thus: 'Heaven is covered with constellations, Earth with waterways, and man with channels.'This 'as above, so below' doctrine means that if there is qi flowing around in the imaginary closed loop of the zodiac, there is qi flowing correspondingly in the body's closed loop of imaginary meridians as well.

Note that not only is acupuncture astrological in origin but also the astrology is based on a model of the universe which has the earth at its centre. This geocentric model was an erroneous idea widely accepted before the Copernican revolution.

So should doctors check the daily horoscopes of their patients?

"The brain imaging is telling us that patients really are switching on and off parts of their brains through the mechanisms of expectation -- positive and negative," said Irene Tracy of Britain's Oxford University, who led the research. "(The effect of expectations) is powerful enough to give real added benefits of the drug, and unfortunately it is also very capable of overriding the true analgesic effect." The placebo effect is the real benefit seen when patients are given dummy treatments but believe they will do them good. The nocebo effect is the opposite, when patients get real negative effects when they have doubts about a treatment.

For their study, the scientists used the drug remifentanil, a potent ultra short-acting synthetic opioid painkiller which is marketed by drugmakers GlaxoSmithKline and Abbott as Ultiva. The study was published in the Science Translational Medicine journal on Wednesday. Volunteers were put in an MRI scanner and had heat applied to one leg. They were asked to rate pain on a 1 to 100 scale. Unknown to the volunteers, the researchers started giving the drug via infusion to see what effects there would be when the volunteers had no knowledge or expectation of treatment. The average initial pain rating of 66 went down to 55. The volunteers were then told they would now start to get the drug, although no change was actually made and they just continued receiving the opioid at the same dose. The average pain ratings dropped further to 39. The volunteers were then told the drug had been stopped and warned that there may be an increase in pain. In reality, the drug was still being given at the same dose, but their pain intensity increased to 64 -- meaning the pain was almost as bad as it had been at the beginning, before they had had any drug.

Tracey said there may be lessons for the design of clinical trials, which often compare an experimental drug against a dummy pill to see if there is any effect beyond the placebo effect. "We should control for the effect of people's expectations on the results of any clinical trial," she said. "At the very least we should make sure we minimize any negative expectations to make sure we're not masking true efficacy in a trial drug."

The people with this attitude aren't just fringe fundamentalists who are fearful of messing with God's Plan. Many of them are prestigious professors and authors whose arguments make no mention of religion. One of the most prominent examples is political theorist Francis Fukuyama, author of End of History, who published a book in 2003 called “Our Posthuman Future: Consequences of the Biotechnology Revolution.” In it he argues that we will lose our “essential” humanity by enhancing ourselves, and that the result will be a loss of respect for “human dignity” and a collapse of morality.

Fukuyama's reasoning represents a prominent strain of thought about human enhancement, and one that I find doubly fallacious. (Fukuyama is aware of the following criticisms, but neither I nor other reviewers were impressed by his attempt to defend himself against them.) The idea that the status quo represents some “essential” quality of humanity collapses when you zoom out and look at the steady change in the human condition over previous millennia. Our ancestors were less knowledgable, more tribalistic, less healthy, shorter-lived; would Fukuyama have argued for the preservation of all those qualities on the grounds that, in their respective time, they constituted an “essential human nature”? And even if there were such a thing as a persistent “human nature,” why is it necessarily worth preserving? In other words, I would argue that Fukuyama is committing both the fallacy of essentialism (there exists a distinct thing that is “human nature”) and the appeal to nature (the way things naturally are is how they ought to be).

Writer Bill McKibben, who was called “probably the nation's leading environmentalist” by the Boston Globe this year, and “the world's best green journalist” by Time magazine, published a book in 2003 called “Enough: Staying Human in an Engineered Age.” In it he writes, “That is the choice... one that no human should have to make... To be launched into a future without bounds, where meaning may evaporate.” McKibben concludes that it is likely that “meaning and pain, meaning and transience are inextricably intertwined.” Or as one blogger tartly paraphrased: “If we all live long healthy happy lives, Bill’s favorite poetry will become obsolete.”

President George W. Bush's Council on Bioethics, which advised him from 2001-2009, was steeped in it. Harvard professor of political philosophy Michael J. Sandel served on the Council from 2002-2005 and penned an article in the Atlantic Monthly called “The Case Against Perfection,” in which he objected to genetic engineering on the grounds that, basically, it’s uppity. He argues that genetic engineering is “the ultimate expression of our resolve to see ourselves astride the world, the masters of our nature.” Better we should be bowing in submission than standing in mastery, Sandel feels. Mastery “threatens to banish our appreciation of life as a gift,” he warns, and submitting to forces outside our control “restrains our tendency toward hubris.”

If you like Sandel's “It's uppity” argument against human enhancement, you'll love his fellow Councilmember Dr. William Hurlbut's argument against life extension: “It's unmanly.” Hurlbut's exact words, delivered in a 2007 debate with Aubrey de Grey: “I actually find a preoccupation with anti-aging technologies to be, I think, somewhat spiritually immature and unmanly... I’m inclined to think that there’s something profound about aging and death.”

And Council chairman Dr. Leon Kass, a professor of bioethics from the University of Chicago who served from 2001-2005, was arguably the worst of all. Like McKibben, Kass has frequently argued against radical life extension on the grounds that life's transience is central to its meaningfulness. “Could the beauty of flowers depend on the fact that they will soon wither?” he once asked. “How deeply could one deathless ‘human’ being love another?”

Kass has also argued against human enhancements on the same grounds as Fukuyama, that we shouldn't deviate from our proper nature as human beings. “To turn a man into a cockroach— as we don’t need Kafka to show us —would be dehumanizing. To try to turn a man into more than a man might be so as well,” he said. And Kass completes the anti-transhumanist triad (it robs life of meaning; it's dehumanizing; it's hubris) by echoing Sandel's call for humility and gratitude, urging, “We need a particular regard and respect for the special gift that is our own given nature.”

By now you may have noticed a familiar ring to a lot of this language. The idea that it's virtuous to suffer, and to humbly surrender control of your own fate, is a cornerstone of Christian morality.

it's fairly representative of standard Christian tropes: surrendering to God, submitting to God, trusting that God has good reasons for your suffering.

I suppose I can understand that if you believe in an all-powerful entity who will become irate if he thinks you are ungrateful for anything, then this kind of groveling might seem like a smart strategic move. But what I can't understand is adopting these same attitudes in the absence of any religious context. When secular people chastise each other for the “hubris” of trying to improve the “gift” of life they've received, I want to ask them: just who, exactly, are you groveling to? Who, exactly, are you afraid of affronting if you dare to reach for better things?

This is why transhumanism is most needed, from my perspective – to counter the astoundingly widespread attitude that suffering and 80-year-lifespans are good things that are worth preserving. That attitude may make sense conditional on certain peculiarly masochistic theologies, but the rest of us have no need to defer to it. It also may have been a comforting thing to tell ourselves back when we had no hope of remedying our situation, but that's not necessarily the case anymore.

I think there is a seperation of Transhumanism and what Massimo is referring to. Things like robotic arms and the like come from trying to deal with a specific defect and thus seperate it from Transhumanism. I would define transhumanism the same way you would (the achievement of a better human), but I would exclude the inventions of many life altering devices as transhumanism. If we could invent a device that just made you smarter, then ideed that would be transhumanism, but if we invented a device that could make someone that was metally challenged to be able to be normal, I would define this as modern medicine. I just want to make sure we seperate advances in modern medicine from transhumanism. Modern medicine being the one that advances to deal with specific medical issues to improve quality of life (usually to restore it to normal conditions) and transhumanism being the one that can advance every single human (perhaps equally?).

I agree with all your points about why the arguments against transhumanism and for suffering are ridiculous. That being said, when I first heard about the ideas of Transhumanism, after the initial excitement wore off (since I'm a big tech nerd), my reaction was more of less the same as Massimo's. I don't particularly see the need for a philosophical movement for this.

if people believe that suffering is something God ordained for us, you're not going to convince them otherwise with philosophical arguments any more than you'll convince them there's no God at all. If the technologies do develop, acceptance of them will come as their use becomes more prevalent, not with arguments.

the standard approach to article preparation is for planners to work hand-in-glove with drug companies to create a first draft. "Key messages" laid out by the drug companies are accommodated to the extent that they can be supported by available data.Planners combine scientific information about a drug with two kinds of message that help create a "drug narrative". "Environmental" messages are intended to forge the sense of a gap in available medicine within a specific clinical field, while "product" messages show how the new drug meets this need.

In a flow-chart drawn up by Eric Crown, publications manager at Merck (the company that sold the controversial painkiller Vioxx), the determination of authorship appears as the fourth stage of the article preparation procedure. That is, only after company employees have presented clinical study data, discussed the findings, finalised "tactical plans" and identified where the article should be published.Perhaps surprisingly to the casual observer, under guidelines tightened up in recent years by the International Committee of Journal Editors (ICMJE), Crown's approach, typical among pharmaceutical companies, does not constitute ghostwriting.

What publication planners understand by the term is precise but it is also quite distinct from the popular interpretation.

"We may have written a paper, but the people we work with have to have some input and approve it."

"I feel that we're doing something good for mankind in the long-run," said Kimberly Goldin, head of the International Society for Medical Publication Professionals (ISMPP). "We want to influence healthcare in a very positive, scientifically sound way.""The profession grew out of a marketing umbrella, but has moved under the science umbrella," she said.But without the window of court documents to show how publication planning is being carried out today, the public simply cannot know if reforms the industry says it has made are genuine.

Dr Leemon McHenry, a medical ethicist at California State University, says nothing has changed. "They've just found more clever ways of concealing their activities. There's a whole army of hidden scribes. It's an epistemological morass where you can't trust anything."Alastair Matheson is a British medical writer who has worked extensively for medical communication agencies. He dismisses the planners' claims to having reformed as "bullshit"."The new guidelines work very nicely to permit the current system to continue as it has been", he said. "The whole thing is a big lie. They are promoting a product."