Combining follow-up and change data is valid in meta-analyses of continuous outcomes: a meta-epidemiological study

J Clin Epidemiol. 2013 Aug;66(8):847-55. doi: 10.1016/j.jclinepi.2013.03.009. Epub 2013 Jun 6.


Objective: To investigate whether it is valid to combine follow-up and change data when conducting meta-analyses of continuous outcomes.

Study design and setting: Meta-epidemiological study of randomized controlled trials in patients with osteoarthritis of the knee/hip, which assessed patient-reported pain. We calculated standardized mean differences (SMDs) based on follow-up and change data, and pooled within-trial differences in SMDs. We also derived pooled SMDs indicating the largest treatment effect within a trial (optimistic selection of SMDs) and derived pooled SMDs from the estimate indicating the smallest treatment effect within a trial (pessimistic selection of SMDs).

Results: A total of 21 meta-analyses with 189 trials with 292 randomized comparisons in 41,256 patients were included. On average, SMDs were 0.04 standard deviation units more beneficial when follow-up values were used (difference in SMDs: -0.04; 95% confidence interval: -0.13, 0.06; P=0.44). In 13 meta-analyses (62%), there was a relevant difference in clinical and/or significance level between optimistic and pessimistic pooled SMDs.

Conclusion: On average, there is no relevant difference between follow-up and change data SMDs, and combining these estimates in meta-analysis is generally valid. Decision on which type of data to use when both follow-up and change data are available should be prespecified in the meta-analysis protocol.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Epidemiologic Studies
  • Humans
  • Meta-Analysis as Topic*
  • Osteoarthritis
  • Outcome Assessment, Health Care / statistics & numerical data*
  • Pain Measurement / statistics & numerical data
  • Randomized Controlled Trials as Topic*
  • Statistics as Topic / methods*