Facilitating shared decision making in advanced cancers: Development of predictive analytics tools from clinical trial and electronic health record data.
It is hypothesised that effective communication of personalised predictions of expected benefits and harms from medicines used in advanced cancer treatment will improve shared decision making, lead to more informed and empowered patients, and enable better decisions regarding whether to commence and continue medicines.
Our group presently has access to individual-patient data (demographic, laboratory and tumour data) from over 60,000 advanced cancer patients. Such data allows the development of prognostic tools that can present personalised likelihoods of therapeutic and adverse effects to medicines.
Historically high-quality prediction models have rarely been available for more than a single outcome for a single medicine. However improved data collection and data sharing initiatives are allowing validated prognostic models to be developed for multiple outcomes for multiple medicines. Therefore, a research focus of the group involves the development of prognostic tools via the analysis of “big data” sourced from clinical trials and data registries through standard and advanced statistical techniques.
However, there is very little evidence on the optimal design of prognostic tools or apps for the presentation of both benefit and harms to medicines used in advanced cancers. Therefore, another focus of the group involves investigating optimal decision aid designs that facilitate effective communication of personalised predictions of expected benefits and harms from medicines used in advanced cancer treatment, with a patient centred focus.
Prospective students qualities
Prospective students require a background in any of pharmacology / biostatistics / pharmacy / laboratory medicine / medical sciences / nursing or psychology, with good verbal and written communication skills. Prospective students require interest in pharmacology, clinical epidemiology, biostatics, pharmacometrics, R programming and improving cancer care.
The projects will be conducted at Flinders University as part of Flinders Cancer Research, which is a multi-disciplinary collaboration between oncologists from the Flinders Medical Centre and researchers from Flinders University.
Professor Michael Sorich
Dr Ashley Hopkins
Associate Professor Andrew Rowland
Professor Ross McKinnon
The group declares funding from the National Breast Cancer Foundation, NHMRC, Tour De Cure, Cancer Council SA, and Pfizer.
We are currently accepting expressions of interest from individuals looking to do a PhD within the group; the two best candidates will be provided a living allowance top-up valued at $10,000 per annum, for three years, pendant commitment and dedication to the project.
Projects will begin within the 2020 year.
To be eligible to receive the PhD top-up applicants must successfully acquire a standard PhD scholarship allowing the commencement of a PhD at Flinders University. The research group will help candidates apply for PhD scholarships and if successful the top-up will be added to the awarded stipend (i.e. Total PhD living allowance = standard scholarship + top-up). Note: Standard scholarship application rounds for the 2020 year are open or are soon to open.
The following eligibility criteria apply to the PhD top-up:
- Must be an Australian citizen or hold permanent residency.
- The PhD must be undertaken on a full-time basis.
- Applicants must have good verbal and written communication skills.
- Applicants must have received or demonstrate significant potential to receive (if still in progress), a first-class honours or equivalent qualifications.
- Grade point average (GPA) must be well above a credit average, and evidence needs to be provided.
- Meet the PhD entry requirements of Flinders University (HDR Eligibility).
Please contact Dr Ashley Hopkins for more information: email@example.com
To apply you must provide:
- A brief curriculum vitae/cover letter (no more than 3 pages, size 12 times new roman, with 1.5-line spacing) which includes the project title, your qualifications, GPA, honours class, research interests, suitability for the project, academic achievements, publications, work history, and referee details. Application must outline your grade point average (GPA) and honours class (or predicted class).
- A PDF copy of your academic transcript.
- Documents should be named as:
Please submit all required documents by email to: firstname.lastname@example.org