Deviations from protocol-defined dosing regimens, in the form of variable adherence to trial medication, are prevalent and problematic. An analysis of 95 clinical studies, reported that the number of patients taking prescribed oral medication(s) decreased progressively over time, with less than 70% of patients being fully adherent to the protocol-specified dosing regimen after 100 days [https://doi.org/10.1146/annurev-pharmtox-011711-113247]. This can lead to incorrect interpretation of a medicine’s efficacy, confound the selection of an appropriate dosing regimen and may mislead the attribution of safety concerns to trial medication. This is especially problematic given that the measurement of medication adherence in registration trials varies widely and is reported poorly [https://doi.org/10.1002/cpt.2709]. Under the auspices of the International Society for Medication Adherence (ESPACOMP), we have developed a consensus taxonomy for medication adherence (ABC), medication adherence reporting guidelines (EMERGE) and methods for analysing adherence data (TEOS). This PhD project will aim to further advance the methodology of medication adherence measurement and reporting in clinical trials.
As an explanatory variable, adherence to trial medication is conventionally measured as the proportion of doses taken (or some variation on this); and, as an outcome variable, as the proportion of patients achieving some arbitrary threshold (usually 80%) of doses taken over a defined period of observation. Both measures conceal important differences in the nature of patients’ adherence. Specifically, non-adherence includes non-initiation (which is a dichotomous outcome); poor implementation of the dosing regimen (patients who take the drug, but not according to the prescribed dosing regimen); and premature discontinuation (when they are fail to persist with treatment). The student will: (i) review the literature for measures and models of medication adherence; (ii) develop appropriate statistical models that more effectively represents the three phases of adherence, utilising data from several thousand trial participants in whom adherence was measured electronically using the Medication Event Monitoring System (Aardex Group’s Adherence Knowledge Centre database); (iii) define a parsimonious model that characterises patients’ adherence behaviour; and (iv) develop a core outcome set of adherence measures for use in drug trials.
The student will be part of a vibrant postgraduate research community within Bangor University’s Institute of Health and Medical Research. The lead supervisor will provide overall direction to the student, and mentorship with respect to the concepts and clinical / pharmacological context. Professor Bernard Vrijens will contribute statistical and modelling expertise.
The student will engage with the ESPACOMP network for wider buy-in and will have an opportunity to spend periods of time at Aardex to gain first-hand experience of adherence measurement. PPI involvement will be via recruitment of patient(s) who have participated in clinical trials and with experience of medicines for chronic disease.
HOW TO APPLY
You are applying for a PhD studentship from the MRC TMRP DTP. A list of potential projects and the application form is available online at:
http://www.methodologyhubs.mrc.ac.uk/about/tmrp-doctoral-training-partnership/
Please complete the form fully. Incomplete forms will not be considered. CVs will not be accepted for this scheme.
Please apply giving details for your first choice project. You can provide details of up to two other TMRP DTP projects you may be interested in at section B of the application form.
Before making an application, applicants should contact the project supervisor to find out more about the project and to discuss their interests in the research before 09 January 2023.
The deadline for applications is 4pm (GMT) 16 January 2023. Late applications will not be considered.
Completed application forms must be returned to: [Email Address Removed]
Informal enquiries may be made to Professor Dyfrig Hughes [Email Address Removed]
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