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Dr Matthew Smith

PhD MSc BSc GradStat AMIMA

Research Fellow
in Biostatistics

Room
G81

LSHTM
Keppel Street
London
WC1E 7HT
United Kingdom

Tel.
020 7636 8636 ext.2495
Jump to: Affiliations Teaching Research Publications

Matthew has experience in applying advanced statistical methods to answer epidemiological research questions regarding cancer patient health outcomes. His research involves investigating the patient and healthcare system interactions, evaluating interventions to reduce inequalities, and recommending key policy decisions.

In 2015, Matthew graduated in Mathematics and Statistics from Nottingham, and, in 2017, he completed a Masters in Medical Statistics at the London School of Hygiene and Tropical Medicine (LSHTM). Following this, in 2017, he was awarded the Cancer Research UK Studentship in Cancer Survival, thereby funding his doctoral research on the socioeconomic inequalities in survival of patients with non-Hodgkin lymphoma; he completed his PhD in 2021.

Currently, he is a Postdoctoral Research Fellow of Biostatistics within the Inequalities in Cancer Outcomes Network at the LSHTM.

For further information, see his personal website.

Affiliations
Department of Non-communicable Disease Epidemiology
Faculty of Epidemiology and Population Health

Centres

Centre for Global Chronic Conditions
Centre for Statistical Methodology

Teaching

Matthew is currently a seminar leader for the following MSc modules:

- Advanced Statistical Modelling;

- Robust Statistical Methods; and

- Statistical Methods in Epidemiology.

He is a seminar assistant for the short course "Cancer Survival: Principles, Methods and Applications".

Matthew sat on the Student Representive Council for the position of Vice President Doctoral Students.

Research

Matthew's main interests are in developing methodologies to investigate the inequalities in cancer survival, with a focus surrounding the effects of comorbidities on the survival of patients with non-Hodgkin lymphoma.

Research Area
Ageing
Health inequalities
Health outcomes
Health services research
Statistical methods
Health services
Discipline
Epidemiology
Mathematics
Statistics
Bioinformatics
Disease and Health Conditions
Cancer
Non-communicable diseases
Country
United Kingdom
Region
Euro area
European Union

Selected Publications
Investigating the inequalities in route to diagnosis amongst patients with diffuse large B-cell or follicular lymphoma in England.
Smith MJ; Fernandez MAL; Belot A; Quartagno M; Bonaventure A; Majano SB; Rachet B; Njagi EN
2021
British journal of cancer
A tutorial on trial emulation in the presence of immortal-time bias. Assessing the benefit of major surgery for elderly lung cancer patients using observational data
Des Vallieres C; Benitez Majano S; Exarchakou A; Smith M; Rachet B; Belot A; Leyrat C
2020
International Journal of Epidemiology
Reflection on modern methods: trial emulation in the presence of immortal-time bias. Assessing the benefit of major surgery for elderly lung cancer patients using observational data.
Maringe C; Benitez Majano S; Exarchakou A; Smith M; Rachet B; Belot A; Leyrat C
2020
Int J Epidemiol
Reply to: Versatility of the clone-censor-weight approach: response to ''trial emulation in the presence of immortal-time bias''.
Maringe C; Benitez Majano S; Exarchakou A; Smith M; Rachet B; Belot A; Leyrat C
2020
International Journal of Epidemiology
Tutorial: Introduction to computational causal inference for applied
researchers and epidemiologists using reproducible Stata code with
translations to R and Python
Smith MJ; Maringe C; Rachet B; Mansournia MA; Zivich PN; Cole SR; Luque-Fernandez MA
2020
Should major surgery be offered to elderly patients with early-stage lung cancer? An emulated trial using observational data in England
Maringe C; Leyrat C; Majano SB; Exarchakou A; Smith M; Rachet B; Belot A
2019
BRITISH JOURNAL OF CANCER
See more Publications
Matthew Smith

Contact

Room
G81

LSHTM
Keppel Street
London
WC1E 7HT
United Kingdom

Tel.
020 7636 8636 ext.2495