Research Topic: Predicting cancer outcomes from patient reported data and routine healthcare data
Supervisors: Prof Tony Cohn, Prof Vania Dimitrova, Prof Adam Glaser, Dr Amy Downing
About Shazeea: I have an integrated masters in Biochemistry and since graduating, have been working for a Pharmaceutical company called Novartis in Medical Affairs/ project management.
Project description: Cancer survival in the UK has doubled in the last 40 years; 50% survive cancer for 10 or more years (2010-11 data). However, UK survival rates are still below the rates in similar countries. Predicting long term outcomes following cancer treatment is crucial. A Patient Reported Outcome Measure (PROM) is a report coming directly from patients about how they feel or function in relation to a health condition and its therapy. Cancer patients’ PROMs represent an important part of assessing patient quality of life, indicating whether treatment has improved a patient’s symptoms, the type of experience of care patients have received at the practice, whether the patient’s health and well-being is improving. The aim of the project is to determine whether AI techniques can enable accurate prediction of cancer outcomes using PROMs routinely collected health data to inform the production of robust personalised outcome prediction models addressing quality of survival as well as absolute duration of survival.