Clinical Review State of the Art Review

Management of chronic pain using complementary and integrative medicine

BMJ 2017; 357 doi: (Published 24 April 2017) Cite this as: BMJ 2017;357:j1284

Complementary and integrative medicine for chronic pain

We read with great interest the review by Chen and Michalsen [1] on the use of complementary and integrative medicine (CIM) in back pain, neck pain, and rheumatoid arthritis with a high incidence of chronic pain. The authors conclude that CIM has an increasing role in the management of chronic pain, but high quality research is warranted.

We would like to respond to their conclusions about acupuncture. Probably due to the timing of the authors, they have missed three highly important articles on assessing acupuncture. The clinical practice guideline from the National Institute for Health and Care Excellence (NICE), in the United Kingdom recommended against the use of acupuncture on osteoarthritis and this decision triggered three papers with remarks on this decision, but also on acupuncture research in general [2-4] and on the bias that may occur if the guidelines for recommendation are not broad enough or not stated well. When the authors remark, that it is too premature to conclude anything on rheumatoid arthritis, they base this conclusion on meta-analyses that do not include all the points mentioned in these articles, especially in the article by Birch et al. [3], for instance, the authors do not describe what would be necessary to make the statement that acupuncture would be an effective treatment? Since they do not seem to work according to a SMART (Specific, Measurable, Achievable, Responsible, Time-related) system [5], their conclusion seems subjective. If they would describe a hypothesis and would tell the readers when it would or would not be confirmed, it would be more scientific and it would be understandable why they draw a conclusion. It is unclear whether the low adverse effects that are generally found and known for acupuncture counted at all in their evaluation, neither was this the fact for cost-effectiveness data. Moreover, there was a lack of comparison between the interventions that they describe. Besides, the effect size, which is important in deciding whether a treatment should be used or not, is highly dependable on the methods of the study. If someone uses enough patients and a low intensity control group, the effect size is likely to be higher than in the case of a high intensity control, like the sham conditions that have been used for a long time [6]. The authors report the article that describes this, but do not seem to implement its consequences in their review. In their abstract, the authors claim to summarize research on CIM in the treatment of chronic pain. In light of our remarks, the authors not only summarize, but draw conclusions without describing the necessary scientific hypotheses and basis to do so; their conclusions are therefore likely to be the subject of bias.

1 Chen L, Michalsen A. Management of chronic pain using complementary and integrative medicine. BMJ 2017;357:j1284. doi:10.1136/bmj.j1284 pmid:28438745.
2 Macpherson H. NICE for some interventions, but not so NICE for others: questionable guidance on acupuncture for osteoarthritis and low-back pain. J Altern Complement Med 2017;23:247-8. doi:10.1089/acm.2017.0029 pmid:28304178.
3 Birch S, Lee MS, Robinson N, Alraek T. The U.K. NICE 2014 guidelines for osteoarthritis of the knee: lessons learned in a narrative review addressing inadvertent limitations and bias. J Altern Complement Med 2017;23:242-6. doi:10.1089/acm.2016.0385 pmid:28394671.
4 Woods B, Manca A, Weatherly H, et al. Cost-effectiveness of adjunct non-pharmacological interventions for osteoarthritis of the knee. PLoS One 2017;12:e0172749. doi:10.1371/journal.pone.0172749 pmid:28267751.
5 Doran GT. There’s a S.M.A.R.T. way to write management’s goals and objectives. Manage Rev 1981;70:35-6.
6 MacPherson H, Vertosick E, Lewith G, et al. Influence of control group on effect size in trials of acupuncture for chronic pain: a secondary analysis of an individual patient data meta-analysis. PLoS One 2014;9:e93739. doi:10.1371/journal.pone.0093739 pmid:24705624.

Competing interests: No competing interests

03 May 2017
Dr. Peggy Bosch
postdoc/clinical psychologist
Prof. Dr. Maurits van den Noort, Prof. Dr. Sabina Lim, Prof. Dr. Gerhard Litscher
Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
Montessorilaan 3, 6525 HR Nijmegen, The Netherlands