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Semin Perinatol. 2016 Oct;40(6):374-384. doi: 10.1053/j.semperi.2016.05.005. Epub 2016 Jun 22.

Methodological issues in the design and analyses of neonatal research studies: Experience of the NICHD Neonatal Research Network.

Author information

1
Biostatistics and Epidemiology Division, RTI International, 6110 Executive Blvd, Suite 902, Rockville, MD 20852. Electronic address: adas@rti.org.
2
Center for Clinical Research and Evidence-Based Medicine, University of Texas Health Science Center at Houston, Houston, TX.
3
Department of Pediatrics, University of Pennsylvania, Philadelphia, PA.
4
Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, NC.
5
Children's Mercy Hospitals and Clinics, University of Missouri-Kansas City School of Medicine, Kansas City, MO.
6
Pregnancy and Perinatology Branch, Eunice Kennedy Shriver National Institute of Health & Human Development, National Institutes of Health, Bethesda, MD.

Abstract

Impressive advances in neonatology have occurred over the 30 years of life of The Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network (NRN). However, substantial room for improvement remains in investigating and further developing the evidence base for improving outcomes among the extremely premature. We discuss some of the specific methodological challenges in the statistical design and analysis of randomized trials and observational studies in this population. Challenges faced by the NRN include designing trials for unusual or rare outcomes, accounting for and explaining center variations, identifying other subgroup differences, and balancing safety and efficacy concerns between short-term hospital outcomes and longer-term neurodevelopmental outcomes. In conclusion, the constellation of unique patient characteristics in neonates calls for broad understanding and careful consideration of the issues identified in this article for conducting rigorous studies in this population.

KEYWORDS:

Causal inference; Competing outcomes; Randomization of multiples; Statistical methodology; Trial design

PMID:
27344192
PMCID:
PMC5065743
DOI:
10.1053/j.semperi.2016.05.005
[Indexed for MEDLINE]
Free PMC Article

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