Spinal Manipulation for Low Back Pain : An Updated Systematic Review of Randomized Clinical Trials

Because there is increasing concern about low-back disability and its current medical management, this analysis attempts to construct a new theoretic framework for treatment. Observations of natural history and epidemiology suggest that low-back pain should be a benign, self-limiting condition, that low back-disability as opposed to pain is a relatively recent Western epidemic, and that the role of medicine in that epidemic must be critically examined. The traditional medical model of disease is contrasted with a biopsychosocial model of illness to analyze success and failure in low-back disorders. Studies of the mathematical relationship between the elements of illness in chronic low-back pain suggest that the biopsychosocial concept can be used as an operational model that explains many clinical observations. This model is used to compare rest and active rehabilitation for low-back pain. Rest is the commonest treatment prescribed after analgesics but is based on a doubtful rationale, and there is little evidence of any lasting benefit. There is, however, little doubt about the harmful effects--especially of prolonged bed rest. Conversely, there is no evidence that activity is harmful and, contrary to common belief, it does not necessarily make the pain worse. Experimental studies clearly show that controlled exercises not only restore function, reduce distress and illness behavior, and promote return to work, but actually reduce pain. Clinical studies confirm the value of active rehabilitation in practice. To achieve the goal of treating patients rather than spines, we must approach low-back disability as an illness rather than low-back pain as a purely physical disease. We must distinguish pain as a purely the symptoms and signs of distress and illness behavior from those of physical disease, and nominal from substantive diagnoses. Management must change from a negative philosophy of rest for pain to more active restoration of function. Only a new model and understanding of illness by physicians and patients alike makes real change possible.

Reports of clinical trials often contain a wealth of data comparing treatments. This can lead to problems in interpretation, particularly when significance testing is used extensively. We examined 45 reports of comparative trials published in the British Medical Journal, the Lancet, or the New England Journal of Medicine to illustrate these statistical problems. The issues we considered included the analysis of multiple end points, the analysis of repeated measurements over time, subgroup analyses, trials of multiple treatments, and the overall number of significance tests in a trial report. Interpretation of large amounts of data is complicated by the common failure to specify in advance the intended size of a trial or statistical stopping rules for interim analyses. In addition, summaries or abstracts of trials tend to emphasize the more statistically significant end points. Overall, the reporting of clinical trials appears to be biased toward an exaggeration of treatment differences. Trials should have a clearer predefined policy for data analysis and reporting. In particular, a limited number of primary treatment comparisons should be specified in advance. The overuse of arbitrary significance levels (for example, P less than 0.05) is detrimental to good scientific reporting, and more emphasis should be given to the magnitude of treatment differences and to estimation methods such as confidence intervals.