About

Steven’s work combines epidemiological study design, statistical modelling, and computational biology, including genetic and other multi-omic analyses, to generate evidence that can support clinical and public health decisions, with a particular interest in translation to personalised (precision) medicine. He has experience using large-scale population and healthcare datasets and translating complex analyses into interpretable, decision-relevant insights.

He is based in the ECHO (Epidemiology of Cancer Healthcare & Outcomes) research group at UCL working on projects with specific aims in earlier and more effective cancer diagnosis and care, including:

- Diagnostic intervals and pathways: investigating potentially avoidable delays in the diagnosis of symptomatic patients with underlying (as-yet-undiagnosed) cancer, and the mechanisms responsible for these delays.

- Prodromal symptoms of cancer: quantifying the predictive value of presenting symptoms and tests for cancer (and other consequential illness) among patients consulting in primary care.

- Variation in cancer health care: analysing differences in cancer diagnosis and treatment between patients and healthcare organisations, in England and other countries, to target interventions that reduce unwarranted variation.

More widely, Steven is interested in individual participant data meta-analysis (IPD-MA), the use of electronic health records (EHR) for medical research, and the application and integration of “-omic” technologies (for example metabolomics, proteomics, phenomics, and transcriptomics). His genomic work includes genome-wide association studies (GWAS), analyses of whole-genome data (germline and somatic), and risk stratification approaches such as polygenic risk scores (PRS). He also works with machine learning approaches and longitudinal modelling to understand change over time and heterogeneity in risk and outcomes.

He has published across general medicine, epidemiology, and disease-focused journals, and contributes to the research community through editorial roles, committee membership, training leadership, mentorship, and equality, diversity and inclusion (EDI) work.

Employment

Employment history is unavailable.

Education

Education history is unavailable.

Projects & Funding

  • Using Multi-Modal Data Integration Across Breast Cancer Molecular Subtypes to Develop Predictors of Treatment Response, Early Relapse, and Survival and to Explore Early Signals of Later Metastatic Recurrence Congressionally Directed Medical Research Programs
    2023 - 2027
  • Using genetics to better understand disease processes in cerebral small vessel disease and vascular cognitive impairment to improve treatment and prediction British Heart Foundation
    2022 - 2026
  • Alcohol Harms: The relationship between alcohol consumption and cardiovascular risk - A life-course perspective Medical Research Council
    2015 - 2018

Publications (107)