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Dr Camille Maringe

Assistant Professor

United Kingdom

Camille graduated from Paris IX Dauphine in Economy and Statistics and completed her graduation in biostatistics at ENSAI in France (Ecole Nationale de la Statistique et de l'Analyse de l'Information). She worked as a statistical fellow for the GSK epidemiology department before joining the School in November 2007. She is currently a assistant professor in the Inequalities in Cancer Outcomes Network (ICON) in the Department of Non-Communicable Disease Epidemiology.

Affiliations

Department of Health Services Research and Policy
Faculty of Public Health and Policy

Centres

Centre for Global Chronic Conditions

Teaching

I am a tutor for the MSc Epidemiology at LSHTM, and facilitates a number of practical sessions for the Statistics in Epidemiology and Public Health module.

I co-organise the Introductory Course in Epidemiology & Medical Statistics, held at LSHTM over three weeks in June and July (https://www.lshtm.ac.uk/study/courses/short-courses/epidemiology-statis…).

Research

As a member of the Inequalities in Cancer Outcomes Network, I study inequalities in cancer outcomes, mostly in England. With observational data, I am using causal inference methodology and emulated clinical trials to study the effect of receiving surgical treatment on 1-year survival in elderly lung cancer patients. I was granted an MRC Better Methods Better Research to develop and disseminate the eltmle STATA package that allows STATA users to study the causal effect of a treatment on a binary outcome using TMLE.

I have special interest in understanding the structure and elements of Electronic Health Records, in order to make best use of them in extracting valuable information for describing, modelling and explaining cancer patient outcomes. A such, I have studied the derivation of stage at diagnosis from linked electronic records, comorbidities, and emergency hospital admissions around the cancer diagnosis.

My PhD research was methodological, specifically exploring the modelling of net survival for the prediction and projection of cancer survival.

Research Area
Applied statistics (medical)
Statistical methods
Public health measure evaluation (statistical methods)
Health inequalities
Population health
Electronic health records
Disease and Health Conditions
Cancer
Country
United Kingdom

Selected Publications

The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study.
MARINGE, C; Spicer, J; MORRIS, M; Purushotham, A; NOLTE, E; Sullivan, R; RACHET, B; AGGARWAL, A;
2020
The Lancet Oncology
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
Summarizing and communicating on survival data according to the audience: a tutorial on different measures illustrated with population-based cancer registry data.
BELOT, A; Ndiaye, A; LUQUE-FERNANDEZ, M-A; KIPOUROU, D-K; MARINGE, C; Rubio, FJ; RACHET, B;
2019
CLINICAL EPIDEMIOLOGY
Explained variation of excess hazard models.
MARINGE, C; Pohar Perme, M; Stare, J; RACHET, B;
2018
Statistics in medicine
Target trial emulation with multi-state model analysis to assess treatment effectiveness using clinical COVID-19 data.
Martinuka, O; Hazard, D; Marateb, HR; MARINGE, C; Mansourian, M; Rubio-Rivas, M; Wolkewitz, M;
2023
BMC medical research methodology
Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review.
SMITH, MJ; Phillips, RV; Luque-Fernandez, MA; MARINGE, C;
2023
Annals of epidemiology
Effectiveness of Sotrovimab and Molnupiravir in community settings in England across the Omicron BA.1 and BA.2 sublineages: emulated target trials using the OpenSAFELY platform
The OpenSAFELY collaborative,; TAZARE, J; Nab, L; ZHENG, B; Hulme, W; Green, A; Curtis, H; MAHALINGASIVAM, V; Higgins, R; SCHULTZE, A; BHASKARAN, K; Mehrkar, A; Schaffer, A; Smith, R; Bates, C; Cockburn, J; Parry, J; Hester, F; Harper, S; EGGO, R; Walker, A; MARKS, M; Brown, M; MARINGE, C; LEYRAT, C; ... DOUGLAS, I.
2023
medRxiv
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