Sarah’s research interests are in diagnostic and prognostic modelling for clinical prediction, and systematic reviews of diagnostic test accuracy.
Her experience in predictive modelling mainly stems from her work in the field of diagnosis and prognostication of hepatocellular carcinoma (HCC). She contributed to the development of models predicting various clinical outcomes in HCC and chronic liver disease patients. This led to publications in high impact journals. Highlights being the development of a measure for liver function (ALBI grade) in HCC patients, which has been independently validated, with the potential to replace the current Child-Pugh grade. Another is the GALAD score for predicting the probability of HCC in patients with chronic liver disease. In 2020, the GALAD score (as part of Roche Diagnostics Liver Indication Program) was granted the Breakthrough Device Designation by the U.S. Food and Drug Administration (FDA).
Sarah is involved in various systematic reviews for evaluating the diagnostic accuracies of tests for colorectal cancer, melanoma, rheumatoid arthritis, ovarian cancer and COVID-19 (antigen and PCR).
- mTBI-predict Study: a prospective cohort biomarker study for identifying novel biomarkers for prognosis of the most disabling sequelae in patients with mild traumatic injury (mTBI).
- COPE-West Midlands (COPE-WM): a study examining the relative contribution of occupational, sociodemographic, home environment, lifestyle and clinical characteristics in the risk of SARS-CoV-2 infection among healthcare workers in several NHS Trusts within the West Midlands.