Tom Menzies

Medical Statistician

UAMS

Also affiliated: University of Leeds (2020–2023); University Hospitals Birmingham NHS Foundation Trust (2023); Institute of Cancer Research (2023); Leeds Teaching Hospitals NHS Trust (2023); Cancer Research UK (2021–2022); Institute of Cancer Research (2023); Cancer Research UK Clinical Trials Unit (2022–2023); Lancaster University (2021–2022); University of Birmingham (2021–2023)

8 h-index 19 pubs 285 cited

Research Areas

Biomedical Subjects

Links

ORCID Research Group

OverviewAI-generated summary

Tom Menzies' research focuses on the statistical analysis of multiple myeloma patient data, particularly concerning treatment outcomes and prognostic factors. His work has investigated the significance of minimal residual disease after autologous stem-cell transplant and the impact of lenalidomide maintenance therapy. Menzies has also explored sex differences in multiple myeloma biology and clinical outcomes, analyzing data from large patient cohorts such as the Myeloma XI Trial.

His publications address optimal durations for lenalidomide maintenance and the incidence of second primary malignancies in patients receiving this treatment. Menzies' research also includes evaluating the addition of other agents, like vorinostat, to treatment regimens and examining clinical characteristics of specific myeloma subtypes, such as IgD myeloma. He has also contributed to methodological research, including comparisons of aggregation functions in multi-criteria decision analysis for drug benefit-risk assessment.

Metrics

h-index: 8
Publications: 19
Citations: 285

Positions

Medical Statistician 2019–present

University of Leeds Clinical Trials Research Unit ORCID
Medical Statistician publications 2023

University of Arkansas for Medical Sciences ORCID

Selected Publications

Progression free survival of myeloma patients who become IFE-negative correlates with the detection of residual monoclonal free light chain (FLC) by mass spectrometry (2023)

Research Square 1 citation DOI OpenAlex

View all publications on OpenAlex →