Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

The prediction of long-term outcomes in surviving infants born very preterm (VPT) or with very low birth weight (VLBW) is necessary to guide clinical management, provide information to parents, and help target and evaluate interventions. There is a large body of literature describing risk factor models for neurodevelopmental outcomes in VPT/VLBW children, yet few, if any, have been developed for use in routine clinical practice or adopted for use in research studies or policy evaluation. We sought to systematically review the methods and reporting of studies that have developed a multivariable risk factor model for neurodevelopment in surviving VPT/VLBW children. We searched the MEDLINE, Embase, and PsycINFO databases from January 1, 1990, to June 1, 2014, and identified 78 studies reporting 222 risk factor models. Most studies presented risk factor analyses that were not intended to be used for prediction, confirming that there is a dearth of specifically designed prognostic modeling studies for long-term outcomes in surviving VPT/VLBW children. We highlight the strengths and weaknesses of the research methodology and reporting to date, and provide recommendations for the design and analysis of future studies seeking to analyze risk prediction or develop prognostic models for VPT/VLBW children.

Original publication

DOI

10.1093/aje/kww135

Type

Journal article

Journal

Am J Epidemiol

Publication Date

01/04/2017

Volume

185

Pages

601 - 612

Keywords

data reporting, development, preterm infants, prognosis, research methodology, risk factors, systematic reviews, very low birth weight, Child Development, Data Collection, Data Interpretation, Statistical, Humans, Infant, Extremely Premature, Infant, Newborn, Infant, Very Low Birth Weight, Models, Neurological, Risk Factors