DPhil, Primary Care Health Sciences
Presentation, Diagnosis and Outcomes of Lymphoma: the role of Primary Care
The research aim is to improve clinical outcomes for patients with lymphoma. There will be a focus on diagnostic issues, linked to the non-specificity of lymphoma symptoms, and the uncommon nature of lymphoma in primary care. The goal is to shorten the time between a patient first attending their GP with symptoms of lymphoma and their diagnosis, and to improve patient experience by exploring the patient’s pathway to diagnosis through from primary to secondary care to identify opportunities for improvement. I will explore combinations of symptom profiles and, as lymphoma lacks a specific blood test or other diagnostic test in general practice, I will examine how to improve the pre-test probability of a biopsy using existing diagnostic tests such as ultrasound, CT scans and blood tests. I will be utilising routinely collected healthcare/registry data (both primary and secondary care), as well as reading existing research literature and analysing clinical records to address specific research questions. The data sources include Clinical Practice Research Datalink (CPRD) and National Cancer Registrations Analysis Service (NCRAS) data for all lymphoma patients diagnosed nationally from 1997-2017 including hospital episode statistics, cancer waiting times and diagnostic imaging data.
How could this research ultimately benefit patients?
Identifying signatures of lymphoma prior to diagnosis in large routine and research datasets may be translated to tangible use in clinical care, in a relatively short time period. The importance of early diagnosis to patients has been identified, and may be associated with less intensive chemotherapy and radiotherapy with fewer short and life-long detrimental consequences such as psychological consequences, reduced fertility, increased risk of second malignancies and chemotherapy induced cardiomyopathy. By identifying the strain placed on primary care services from lymphoma patients, suitable planning and resourcing of care can be achieved.
I am a Statistician, who completed their undergraduate degree at Queen Mary’s University London (QMUL) in Mathematics and Statistics in 2020. I worked as a statistician intern at The Wolfson Institute of Preventive medicine with Dr Stephen Duffy in the Summer 2020. I worked on improving early diagnosis of Colorectal Cancer (CRC) by optimising the criteria for secondary care referral using the non-invasive diagnostic blood test FIT (Faecal Immunochemical Blood Test). The internship sparked an interest in medical research as I enjoyed being able to apply my statistical skills to positively influence the delivery of healthcare for cancer patients – for example, managing the frequency of false positive and negative FIT test results by balancing sensitivity and specificity rates. I analysed the 2014 CRC FIT pilot dataset, estimating mean sojourn time, interval cancers and over diagnosis across various FIT thresholds. The paper which I co-authored involved making recommendations in response to the colonoscopy capacity crisis following COVID-19.
From 2021-2022, I studied a MSc in Statistical Sciences at Oxford University, from which I gained extensive experience in data analysis and model fitting. As I have an interest in exploring the causation of heterogeneous responses to diseases, I decided to carry out my dissertation to examine the statistical association between mutation signatures and severity of COVID-19. I analysed SARS-CoV-2 sequences of varying severity using methods such as regression, ANOVA and non-parametric tests. I explored the occurrence of mutations in Ribonucleic acid (RNA) acid viruses and the importance of monitoring these due to the potential creation of newly created variants, which can impact on disease severity and transmissibility.
I was prompted to apply for the Cancer Science DPhil programme to specialise in academic medical data research. I am currently working with the Nuffield Department of Primary Care Health Sciences on my DPhil, amongst primary healthcare researchers, as well as receiving seminars and training from the Oxford Cancer Science centre.
Alongside research, teaching statistics is one of my long-term visions. I have a strong desire to make statistical concepts understandable and enjoyable, by contextualising its value to motivate study, such as in healthcare, where disease mortality can be reduced.