Estimation of gestational age in early pregnancy from crown-rump length when gestational age range is truncated: the case study of the INTERGROWTH-21st Project
1 Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute (OMPHI), Green Templeton College, University of Oxford, Level 3 Women's Centre, John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
2 Centre for Statistics in Medicine, University of Oxford, Botnar Research Centre, Windmill Road, Oxford OX3 7LD, UK
BMC Medical Research Methodology 2013, 13:151 doi:10.1186/1471-2288-13-151Published: 7 December 2013
Fetal ultrasound scanning is considered vital for routine antenatal care with first trimester scans recommended for accurate estimation of gestational age (GA). A reliable estimate of gestational age is key information underpinning clinical care and allows estimation of expected date of delivery. Fetal crown-rump length (CRL) is recommended over last menstrual period for estimating GA when measured in early pregnancy i.e. 9+0-13+6 weeks.
The INTERGROWTH-21st Project is the largest prospective study to collect data on CRL in geographically diverse populations and with a high level of quality control measures in place. We aim to develop a new gestational age estimation equation based on the crown-rump length (CRL) from women recruited between 9+0-13+6 weeks. The main statistical challenge is modelling data when the outcome variable (GA) is truncated at both ends, i.e. at 9 and 14 weeks.
We explored three alternative statistical approaches to overcome the truncation of GA. To evaluate these strategies we generated a data set with no truncation of GA that was similar to the INTERGROWTH-21st Project CRL data, which we used to explore the performance of different methods of analysis of these data when we imposed truncation at 9 and 14 weeks of gestation. These 3 methods were first tested in a simulation based study using a previously published dating equation by Verburg et al. and evaluated how well each of them performed in relation to the model from which the data were generated. After evaluating the 3 approaches using simulated data based on the Verburg equations, the best approach will be applied to the INTERGROWTH-21st Project data to estimate GA from CRL.
Results of these rather “ad hoc” statistical methods correspond very closely to the “real data” for Verburg, a data set that is similar to the INTERGROWTH-21st project CRL data set.
We are confident that we can use these approaches to get reliable estimates based on INTERGROWTH-21st Project CRL data. These approaches may be a solution to other truncation problems involving similar data though their application to other settings would need to be evaluated.