Clinical trials using routinely collected outcomes from registries are still relatively rare, but have potential advantages over the traditional model. Efficiency gains can be made by removing the need for individually designed clinical trial databases, and the burden on patients can be greatly reduced. Cluster randomised trials, including stepped wedge trial designs, also benefit from routinely collected outcomes, where complete enumeration of a cluster can be used, rather than consenting individual patients to a trial.
There is current national interest in the use of routine data to obtain evidence to inform healthcare policy. Health Data Research UK (HDR UK) is an investment led by the Medical Research Council, in partnership with several other organisations including NIHR, aiming to develop and apply cutting edge data science approaches to address health research challenges. The National Institute for Clinical Excellence (NICE) has introduced the Accelerated Access Collaborative, using data from routine sources to help streamline the route to market for new pharmacological products.
The supervisors are investigators on the NERVES (Nerve Rootblock Versus Surgery) trial, a national multi-centre, randomised trial funded by the NIHR and due to report in 2019. The primary outcome studied was the Oswestry disability index (ODI) but secondary outcomes including Core Outcome Measure Index (COMI) and VAS pain scores for back and leg pain. This trial was carried out in parallel with routine data collection as part of an NHS data registry, which occurs as part of routine NHS care, and contributes to the international spinal registry SPINE TANGO (ST), part of the Spine Society of Europe. ST data sets exist across the UK and Europe which hold routine registry data such as COMI and ODI for routinely treated patients with sciatica either under-going injection or surgery.
The project will focus on the potential of the spinal surgery registries to provide routinely collected outcome data for future clinical trials. The data collected in each registry will be reviewed, and the alignment with suggested core outcome sets considered. The registries will be evaluated with respect to data quality and completeness of outcome measures. Data from the NERVES trial, which was run using standard data collection methods, will be used as a comparator to the alternative methods considered in this project. The potential for use of spinal registry data in alternative clinical trial designs such as cluster randomised trials will be explored. The potential impact of these alternative designs on efficiency can be modelled using statistical simulation studies.
The student will have the opportunity to work within a large group of statisticians in the Clinical Trials Research Centre, and the wider Department of Biostatistics, with a range of practical and methodological expertise. They will also benefit from interaction with clinicians involved in clinical trials, and also work with the spinal registries.
Qualifications and Experience
You should hold a 1st or 2:1 degree in statistics or a related discipline, preferably with a Masters degree, and have experience of coding in a statistical package such as SAS, R, or Stata.
Please note the English Language Requirement for EU Students is an IELTS score of 6.5 with no band score lower than 5.5.
How to apply
To apply please send your CV, cover letter and the names and addresses of at least two references to email@example.com.
For application enquires please contact Dr Girvan Burnside, firstname.lastname@example.org
Open to EU/UK applicants
This 3-year PhD studentship covers tuition fees, research support costs and a stipend at UKRI standard rates (£14,999 p.a. for 2019/20). The studentship is open to UK and EU candidates.