Acupuncture Doesn't Work « Science-Based Medicine - 0 views
-
Clinical research can never prove that an intervention has an effect size of zero. Rather, clinical research assumes the null hypothesis, that the treatment does not work, and the burden of proof lies with demonstrating adequate evidence to reject the null hypothesis. So, when being technical, researchers will conclude that a negative study “fails to reject the null hypothesis.” Further, negative studies do not demonstrate an effect size of zero, but rather that any possible effect is likely to be smaller than the power of existing research to detect. The greater the number and power of such studies, however, the closer this remaining possible effect size gets to zero. At some point the remaining possible effect becomes clinically insignificant. In other words, clinical research may not be able to detect the difference between zero effect and a tiny effect, but at some point it becomes irrelevant. What David and I have convincingly argued, in my opinion, is that after decades of research and more than 3000 trials, acupuncture researchers have failed to reject the null hypothesis, and any remaining possible specific effect from acupuncture is so tiny as to be clinically insignificant.
-
It is clear from meta-analyses that results of acupuncture trials are variable and inconsistent, even for single conditions. After thousands of trials of acupuncture and hundreds of systematic reviews,18 arguments continue unabated. In 2011,Pain published an editorial31 that summed up the present situation well. “Is there really any need for more studies? Ernst et al.18 point out that the positive studies conclude that acupuncture relieves pain in some conditions but not in other very similar conditions. What would you think if a new pain pill was shown to relieve musculoskeletal pain in the arms but not in the legs? The most parsimonious explanation is that the positive studies are false positives. In his seminal article on why most published research findings are false, Ioannidis32 points out that when a popular but ineffective treatment is studied, false positive results are common for multiple reasons, including bias and low prior probability.” Since it has proved impossible to find consistent evidence after more than 3000 trials, it is time to give up. It seems very unlikely that the money that it would cost to do another 3000 trials would be well-spent.