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Developing meta-analytic methods for analysing survival data in children with specific birth defects


Project Description

This PhD project will aim to develop statistical methods for describing the survival of children with specific congenital anomalies (birth defects) while allowing for country of origin. It will be based on EUROlinkCAT, a five year EU funded project involving congenital anomaly registries in 14 European countries, each linked to data on mortality, hospital discharge, prescription and educational attainment. The project will be based on aggregate data and will consider both non-parametric and Bayesian approaches to allow for variations in data quality between registries and will explore the use of hierarchical models to allow for similarities between different congenital anomalies. Factors influencing survival (e.g. prenatal diagnosis, gestational age and birthweight) will be investigated. This project will require collaboration with both clinical geneticists and statisticians.

This PhD project will be based within EUROlinkCAT,an EU-funded five year HORIZON 2020 Project led by St George’s University of London involving 22 congenital anomaly registries in 14 European countries linking their data to information on mortality, hospital discharge, prescription and educational databases. The aim of this PhD will be to develop statistical methods to combine information on the survival of children with specific anomalies (birth defects) to adjust for European country. Due to information governance issues, individual case data will may not be transferred between countries, and hence only aggregate data (ie the number of deaths per year) or analytic results (ie the hazard ratios) can be sent to the Central Results Repository. Multilevel models exist for parametric survival analysis, but it is hoped that this PhD will consider non-parametric approaches and also explore the potential of Bayesian methods in allowing for the quality of the data received from the different registries and possibly hierarchical models to allow for the similarities between different congenital anomalies. Some congenital anomalies investigated are extremely rare and issues of analysing survival of such rare anomalies may arise. Factors influencing survival, including such as prenatal diagnosis, gestational age at birth and birthweight, will be investigated. This project will require collaboration with clinical geneticists as well as statisticians. This studentship will be based in the Population Health Research Institute at St George’s, University of London. The Institute is actively involved in research on a range of issues relevant to the improvement of human health both nationally and internationally. PHRI staff are also involved in teaching epidemiology and medical statistics to undergraduate MBBS students; the student would have opportunities for involvement in teaching and tutoring.

Please note that the Lead Supervisor will now be Professor Joan Morris

Funding Notes

Stipend and fees will be paid for a maximum of three years.

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