In a recent review of systematic reviews and controlled studies, researchers were unable to find sufficient evidence to support the clinical use of medical cannabis or the pharmaceutical formulations for gastrointestinal, cancer, or rheumatic pain, or weight loss in cancer of AIDS. Many data from previous studies were either statistically insignificant or were of low quality. However, the authors did find that existing literature sufficiently supported the treatment of neuropathic pain with cannabis. Additional controlled studies may shed more light on the use of cannabis for general pain management. Interestingly, while the authors do raise two important limitations of the studies that they highlight in the article (inadequate size of some studies and generally limited supply of traditional scientific studies from which to draw conclusions) they do not address some of the more fundamental concerns with the reporting.
Dr. Caplan and the #MDTake:
The limitations of studies in cannabis are numerous and an important consideration for researchers as they study cannabis, and equally essentially to consider for those of us reading the study product. To my personal count, there are at least 40 different types of biases that can skew data in a way that delivers information other than a precise description of actual events. This study, as many like it, presumptuously assumes that, if data doesn’t show a trend that so-mocked “anecdotal” data shows, then surely the anecdote must be incorrect. What if the reviews are simply not yet accurately recording what human iteration has discovered repeatedly for millennia?
The conclusion the review draws follows:
“Conclusion: The public perception of the efficacy, tolerability, and safety of cannabis-based medicines in pain management and palliative medicine con- flicts with the findings of systematic reviews and prospective observational studies conducted according to the standards of evidence-based medicine.“
Is the right question for science to question the validity of the stories that individuals are telling, against an imperfect science of information collection, as well as the limited scope of statistical validity for understanding data? Or is the right task for science to question its own methods of assumptions in discovery and understanding?
On the one hand, we have millions of people calling the color of the ocean “blue.” On the other hand, we have data that tells us that water, in fact, has no color. Similarly, the anecdotes from cannabis consumers are telling a story that is starkly different from the currently available data.
For those interested in combing through a close inspection of the many ways that data can be misrepresented and misunderstood, check out https://first10em.com/bias/
and/or watch the video below:
View this review (yellow link) or download:
This paper is also stored here: http://bit.ly/34NXhQV inside the CED Foundation Archive
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