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- Title
Individual growth curve models for assessing evidence-based referral criteria in growth monitoring.
- Authors
van Dommelen, P.; van Buuren, S.; Zandwijken, G. R. J.; Verkerk, P. H.
- Abstract
The goal of this study is to assess whether a growth curve model approach will lead to a more precise detection of Turner sydnrome (TS) than conventional referral criteria for growth monitoring. The Jenss-Bayley growth curve model was used to describe the process of growth over time. A new screening rule is defined on the parameters of this growth curve model, parental height and gestational age. The rule is applied to longitudinal growth data of a group of children with TS ( n=777) and a reference ( n=487) group. The outcome measures are sensitivity, specificity and median referral age. Growth curve parameters for TS children were different from reference children and can therefore be used for screening. The Jenss-Bayley growth model, which uses all longitudinal measurements from birth to a maximum age of 5 years with at least one measurement after the age of 2, together with parental height and gestational age can achieve a sensitivity of 85.2 per cent with a specificity of 99.5 per cent and a median referral age of 4.2 (the last measurement between the age of 2 and 5 of each child is considered to be the moment of referral). Sensitivity increases by 2 percentage points when decreasing the specificity to 99 per cent. The Jenss-Bayley growth model from birth to a maximum age of 8 years with at least one measurement after the age of 2, together with parental height results in a sensitivity of 89.0 per cent with a specificity of 99.5 per cent and a median referral age of 6.1. For a specificity of 98 per cent, we obtain a sensitivity of 92.3 per cent. In comparison to conventional rules applied to the same data, sensitivity is about 11-30 percentage points higher at the same level of specificity for the Jenss-Bayley growth rule. We conclude that from the age of 4, growth curve models can improve the screening on TS to conventional screening rules. Copyright © 2005 John Wiley & Sons, Ltd.
- Publication
Statistics in Medicine, 2005, Vol 24, Issue 23, p3663
- ISSN
0277-6715
- Publication type
Article
- DOI
10.1002/sim.2234