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Middlekoop et al chapter three – what do the numbers mean?



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Here is a final installment in our coverage of the Middlekoop paper.  First up, we had Neil O’Connell talking about elephants and then we had Peter O’Sullivan raising some provocative thoughts on the value of our current direction in trying to evaluate exercise as a treatment for back pain. Now, from that odd group of people called Bio-statisticians, comes an important consideration that may leave us all scratching our heads…

From Dr Anne Smith

The validity of any meta-analysis is questionable here even under a random effects model such as the one used in the Middlekoop paper[1], as heterogeneity between studies is likely to be very high, many of the studies were at high risk of bias (60%), and in all analyses the number of trials included was only 6 or less, and in most cases only 2 or 3. Continuing on with these kind of meta-analyses is futile at the present time. However, it is unlikely that we will ever reach the situation in which we are able to pool results from large, homogenous trials with minimal bias in the area of CLBP. Indeed it is impossible to eliminate some aspects of bias from these sorts of trials. Here are some questions I think are important:

(1) How do we effectively blind patients from their intervention and thus minimise effects of what are often very powerful belief systems about what particular form of exercises will help them?

(2) How do we blind care providers so they do not bring their belief systems into the mix?

(3) How do we absolutely ensure patients are only exclusively receiving a particular exercise intervention and not other co-interventions?

It is only human for care providers to want to assist their patients as much as possible, and so subtle co-intervention bias is likely to always be present. Surely it would be better at this stage to put our time and resources into expanding our understanding of the many pathways to chronic and persisting pain and disability, and then on this basis design targeted interventions.

From Lorimer:

Nice work Anne – don’t hold back will you.  I would like to float a couple of answers to those excellent questions. We have tried to address the first one by telling patients in both groups that they are in the active treatment group that is being compared to a control treatment. We have tried to address the second one by telling them the same thing.  We also measure as much of these things as we can and control for them in statistics – VAS on expectations of patient and practitioner, beliefs and attitudes of both, enthusiasm and perceived knowledge level of practitioner.  Intriguingly, reviewers of these papers often suggest they are meaningless data and should not be included.  I agree with Anne that they are not meaningless – quite the contrary – I wonder if they are very VERY meangful.

About Anne

Anne Smith is a really nice, totally understated and very clever person who has advanced training in bio-statistics (a language that few of us understand). She originally trained as a physiotherapist, but because of her frustration with current clinical practice, she embarked on a research career.  She is currently a post doctoral fellow at Curtin University, Perth, Australia (in spite of the fact that she could be working in the private sector earning squillions with her advanced stats skills). She has a big knowledge and interest in the complexities of chronic spinal pain disorders, and the pathways that lead to their development. She has published lots of great papers and does really clever things with complex data sets, to answer clinical questions in order to tell a clear story. She actually reads stats modelling books on holiday because they interest her (that is, if she is not surfing, running with her black labrador or hanging out with her family). Clearly this bio was not written by her.

[1] van Middelkoop M, Rubinstein SM, Verhagen AP, Ostelo RW, Koes BW, & van Tulder MW (2010). Exercise therapy for chronic nonspecific low-back pain. Best practice & research. Clinical rheumatology, 24 (2), 193-204 PMID: 20227641

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