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Use of re-randomized data in meta-analysis.

Publication ,  Journal Article
Hozo, I; Djulbegovic, B; Clark, O; Lyman, GH
Published in: BMC Med Res Methodol
May 10, 2005

BACKGROUND: Outcomes collected in randomized clinical trials are observations of random variables that should be independent and identically distributed. However, in some trials, the patients are randomized more than once thus violating both of these assumptions. The probability of an event is not always the same when a patient is re-randomized; there is probably a non-zero covariance coming from observations on the same patient. This is of particular importance to the meta-analysts. METHODS: We developed a method to estimate the relative error in the risk differences with and without re-randomization of the patients. The relative error can be estimated by an expression depending on the percentage of the patients who were re-randomized, multipliers (how many times more likely it is to repeat an event) for the probability of reoccurrences, and the ratio of the total events reported and the initial number of patients entering the trial. RESULTS: We illustrate our methods using two randomized trials testing growth factors in febrile neutropenia. We showed that under some circumstances the relative error of taking into account re-randomized patients was sufficiently small to allow using the results in the meta-analysis. Our findings indicate that if the study in question is of similar size to other studies included in the meta-analysis, the error introduced by re-randomization will only minimally affect meta-analytic summary point estimate. We also show that in our model the risk ratio remains constant during the re-randomization, and therefore, if a meta-analyst is concerned about the effect of re-randomization on the meta-analysis, one way to sidestep the issue and still obtain reliable results is to use risk ratio as the measure of interest. CONCLUSION: Our method should be helpful in the understanding of the results of clinical trials and particularly helpful to the meta-analysts to assess if re-randomized patient data can be used in their analyses.

Duke Scholars

Published In

BMC Med Res Methodol

DOI

EISSN

1471-2288

Publication Date

May 10, 2005

Volume

5

Start / End Page

17

Location

England

Related Subject Headings

  • Selection Bias
  • Seizures, Febrile
  • Recurrence
  • Randomized Controlled Trials as Topic
  • Patient Selection
  • Outcome Assessment, Health Care
  • Odds Ratio
  • Neutropenia
  • Models, Statistical
  • Meta-Analysis as Topic
 

Citation

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Hozo, I., Djulbegovic, B., Clark, O., & Lyman, G. H. (2005). Use of re-randomized data in meta-analysis. BMC Med Res Methodol, 5, 17. https://doi.org/10.1186/1471-2288-5-17
Hozo, Iztok, Benjamin Djulbegovic, Otavio Clark, and Gary H. Lyman. “Use of re-randomized data in meta-analysis.BMC Med Res Methodol 5 (May 10, 2005): 17. https://doi.org/10.1186/1471-2288-5-17.
Hozo I, Djulbegovic B, Clark O, Lyman GH. Use of re-randomized data in meta-analysis. BMC Med Res Methodol. 2005 May 10;5:17.
Hozo, Iztok, et al. “Use of re-randomized data in meta-analysis.BMC Med Res Methodol, vol. 5, May 2005, p. 17. Pubmed, doi:10.1186/1471-2288-5-17.
Hozo I, Djulbegovic B, Clark O, Lyman GH. Use of re-randomized data in meta-analysis. BMC Med Res Methodol. 2005 May 10;5:17.
Journal cover image

Published In

BMC Med Res Methodol

DOI

EISSN

1471-2288

Publication Date

May 10, 2005

Volume

5

Start / End Page

17

Location

England

Related Subject Headings

  • Selection Bias
  • Seizures, Febrile
  • Recurrence
  • Randomized Controlled Trials as Topic
  • Patient Selection
  • Outcome Assessment, Health Care
  • Odds Ratio
  • Neutropenia
  • Models, Statistical
  • Meta-Analysis as Topic