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Accounting for multiple births in randomised trials: a systematic review
  1. Lisa Nicole Yelland1,2,
  2. Thomas Richard Sullivan2,
  3. Maria Makrides1,3
  1. 1Women's and Children's Health Research Institute, The University of Adelaide, North Adelaide, South Australia, Australia
  2. 2School of Population Health, The University of Adelaide, Adelaide, South Australia, Australia
  3. 3South Australian Health and Medical Research Institute, Adelaide, Australia
  1. Correspondence to Dr Lisa Nicole Yelland, School of Population Health, Mail Drop DX650 511, The University of Adelaide, SA 5005, Australia; lisa.yelland{at}


Objectives Multiple births are an important subgroup to consider in trials aimed at reducing preterm birth or its consequences. Including multiples results in a unique mixture of independent and clustered data, which has implications for the design, analysis and reporting of the trial. We aimed to determine how multiple births were taken into account in the design and analysis of recent trials involving preterm infants, and whether key information relevant to multiple births was reported.

Design We conducted a systematic review of multicentre randomised trials involving preterm infants published between 2008 and 2013. Information relevant to multiple births was extracted.

Results Of the 56 trials included in the review, 6 (11%) excluded multiples and 24 (43%) failed to indicate whether multiples were included. Among the 26 trials that reported multiples were included, only one (4%) accounted for clustering in the sample size calculations and eight (31%) took the clustering into account in the analysis of the primary outcome. Of the 20 trials that randomised infants, 12 (60%) failed to report how infants from the same birth were randomised.

Conclusions Information on multiple births is often poorly reported in trials involving preterm infants, and clustering due to multiple births is rarely taken into account. Since ignoring clustering could result in inappropriate recommendations for clinical practice, clustering should be taken into account in the design and analysis of future neonatal and perinatal trials including infants from a multiple birth.

  • Multiple Births
  • Twins
  • Evidence Based Medicine
  • Statistics

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