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…).
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.
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
Emulation of target cluster trials of complex interventions: Estimands, methods and application
2024
Effectiveness of post-COVID-19 primary care attendance in improving survival in very old patients with multimorbidity: a territory-wide target trial emulation.
2024
Family medicine and community health
Making the most of observational data to estimate causal effects using target trial emulation. Invited seminar at the SIOG – Methods Working Group.
2024
Target trial emulation with multi-state model analysis to assess treatment effectiveness using clinical COVID-19 data.
2023
BMC medical research methodology
