Identifying Predictors of Response Using an Individual Patient Data Meta-Analysis

  • Joanne Stocks, Monica Persson
  • January 2020, SAGE Publications
  • DOI: 10.4135/9781529741551

Case study on the methodology to undertake Individual Patient Data (IPD) meta-analyses.

Photo by Sarah Shaffer on Unsplash

Photo by Sarah Shaffer on Unsplash

What is it about?

To personalise osteoarthritis (OA) pain relief to an individual patient, we need to first identify predictors of their treatment response. We undertook two individual patient data (IPD) meta-analyses conducted as part of the OA Trial Bank. One aim was to identify predictors of response to two topical treatments: topical non-steroidal anti-inflammatory drugs and capsaicin. The other aim was to identify placebo responders and predictors of response in osteoarthritis.

Why is it important?

An IPD meta-analysis requires the original trial authors to share the data on all the individual patients in their trial with the advantage being an increased study sample size. However, being restricted only to variables previously measured within the trials is a limitation. In this case study, we report on some of the challenges we experienced, and lessons learnt from undertaking two different IPD meta-analyses to identify predictors of response in patients with osteoarthritis.

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The following have contributed to this page: Dr Joanne Stocks