One article on PainSci cites Colquhoun 2017: The “Impress Me” Test
PainSci commentary on Colquhoun 2017: ?This page is one of thousands in the PainScience.com bibliography. It is not a general article: it is focused on a single scientific paper, and it may provide only just enough context for the summary to make sense. Links to other papers and more general information are provided wherever possible.
Dr. David Colquhoun briefly but persuasively argues that clinical guidelines and scientific reviews routinely make recommendations based on inadequate evidence, substantially due to a common failure to appreciate the risk of false positives in positive studies of treatments with low prior plausibility: “every false positive not only harms patients (and budgets) but also provides ammunition for the antiscience brigade, who are now so evident.“
~ Paul Ingraham
original abstract †Abstracts here may not perfectly match originals, for a variety of technical and practical reasons. Some abstacts are truncated for my purposes here, if they are particularly long-winded and unhelpful. I occasionally add clarifying notes. And I make some minor corrections.
Heneghan and colleagues discuss the need for better clinical guidelines. One problem with guidelines is that in very many cases no good treatment exists, yet recommendations are still made.
A good example is non-specific low back pain—the 2009 guidelines from the National Institute for Health and Care Excellence recommended acupuncture despite little evidence that it works to any useful extent. The guidelines were revised in 2016 to say “do not offer acupuncture.” This left few other recommended treatments, but the new guidelines fail to say explicitly that it’s an unsolved problem.
Even Cochrane reviews don’t seem to appreciate the distinction between P values and the risk of false positives. If you observe a P value close to 0.05, then to achieve a false positive rate of 5% you must assume that you are 87% certain of a real effect before the trial is done. That’s clearly preposterous. Even if you observe P=0.001, you would still have a false positive rate of 8% if the hypothesis was implausible (prior probability 0.1). And these numbers apply to perfect unbiased experiments, before you add all the other problems of P hacking, multiple comparisons, and so on.
These misunderstandings must be responsible for many false positive results. And every false positive not only harms patients (and budgets) but also provides ammunition for the antiscience brigade, who are now so evident.
- “The faulty statistics of complementary alternative medicine (CAM),” Maurizio Pandolfi and Giulia Carreras, Eur J Intern Med, 2014.
- “Clinical trials of integrative medicine: testing whether magic works?,” David H. Gorski and Steven P. Novella, Trends in Molecular Medicine, 2014.
- “Recommendations are made in the absence of any good treatments,” David Colquhoun, British Medical Journal, 2017.
This page is part of the PainScience BIBLIOGRAPHY, which contains plain language summaries of thousands of scientific papers & others sources. It’s like a highly specialized blog. A few highlights:
- Association of Lumbar MRI Findings with Current and Future Back Pain in a Population-based Cohort Study. Kasch 2022 Spine (Phila Pa 1976).
- A double-blinded randomised controlled study of the value of sequential intravenous and oral magnesium therapy in patients with chronic low back pain with a neuropathic component. Yousef 2013 Anaesthesia.
- Is Neck Posture Subgroup in Late Adolescence a Risk Factor for Persistent Neck Pain in Young Adults? A Prospective Study. Richards 2021 Phys Ther.
- Sudden amnesia resulting in pain relief: the relationship between memory and pain. Choi 2007 Pain.
- Photobiomodulation therapy is not better than placebo in patients with chronic nonspecific low back pain: a randomised placebo-controlled trial. Guimarães 2021 Pain.