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Problems in Meta-Analysis of Comparative Effectiveness of Conservative Interventions for Nonspecific Chronic Spinal Pain

  • David C. Hoaglin
    Correspondence
    Address reprint requests to David C. Hoaglin, PhD, Department of Quantitative Health Sciences, University of Massachusetts Medical School, 368 Plantation Street, Albert Sherman Center, Worcester, Massachusetts 01605.
    Affiliations
    Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts
    Search for articles by this author
      As a statistician who is interested in methods of meta-analysis, the letter by Gatchel and Licciardone
      • Gatchel R.J.
      • Licciardone J.C.
      Potential problems with systematic reviews and meta-analyses.
      prompted me to examine the article by O'Keeffe et al
      • O'Keeffe M.
      • Purtill H.
      • Kennedy N.
      • Conneely M.
      • Hurley J.
      • O'Sullivan P.
      • Dankaerts W.
      • O'Sullivan K.
      Comparative effectiveness of conservative interventions for nonspecific chronic spinal pain: Physical, behavioral/psychologically informed, or combined? A systematic review and meta-analysis.
      on comparative effectiveness of conservative interventions for nonspecific chronic spinal pain. I was discouraged to find numerous shortcomings in methods, analysis, and reporting that undermine its validity.
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      Linked Article

      • Criticism for Following Recommended Practice
        The Journal of PainVol. 19Issue 2
        • Preview
          The author David C. Hoaglin criticises the methods used in our review. Specifically, he questions using a random effects model, halving of sample sizes to avoid double counting of participants, and assessing heterogeneity using the I2 statistic. However, we were in line with the recommendations of the Cochrane Back Review Group1 in using these approaches—of which the author is either unaware, or does not acknowledge. This is compounded by the fact that the author provides no evidence-based, rigorously tested alternative for these choices (eg, using the I2 statistic).
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