Accounting for multiple births in randomised trials: a systematic review.
OBJECTIVE
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.


METHODS
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.
Women's and Children's Health Research Institute, The University of Adelaide, North Adelaide, South Australia, Australia School of Population Health, The University of Adelaide, Adelaide, South Australia, Australia.
Lisa Nicole
LN
Yelland
School of Population Health, The University of Adelaide, Adelaide, South Australia, Australia.
Thomas Richard
TR
Sullivan
Women's and Children's Health Research Institute, The University of Adelaide, North Adelaide, South Australia, Australia South Australian Health and Medical Research Institute, Adelaide, Australia.
Maria
M
Makrides
D016000:Cluster Analysis; D006801:Humans; D007231:Infant, Newborn; D007234:Infant, Premature; D009099:Multiple Birth Offspring; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012107:Research Design; D018401:Sample Size
Evidence Based Medicine; Multiple Births; Statistics; Twins