Clinical Research and Methodology
Co-ordination: Professor Alain Duhamel (EA2694, University of Lille 2) and Andrew Kramar (Oscar Lambret Centre – COL), who are biostatisticians
Structuring and summary of the missions:
The clinical research and methodology platform consists of four structures:
- The methodology and biostatistics unit, directed by Prof. A. Duhamel (Lille CHRU – University Regional Hospital Centre) and Dr. A. Kramar (COL),
- The clinical research unit, directed by Dr. S. Clisant (COL) and Prof. D. Deplanque, (Lille CHRU),
- The data management unit, directed by A. Duhamel, A. Kramaret, and Dr. M. Castera-Tellier (Data Processing Centre, Caen),
- The Lille and Regional Cancer Register, directed by Dr. K. Ligier.
The Clinical Research and Methodology platform provides assistance to researchers and clinicians for their research projects, from the design phase (putting together projects) through to making use of the results (scientific publications). The platform also develops its own research projects linked to the orientations of the scientific projects of the ONCOLille SIRIC’s researchers and relying on research team EA2694 (Public Health: epidemiology and healthcare quality).
The Clinical Research and Methodology platform set up within ONCOLille has clearly contributed to improving multi-disciplinary exchanges between experts from the platform and researchers and clinicians, enabling a more fluid, effective organising of clinical trials. In addition to the dynamism of clinical research already set up at the Lille site, this has contributed to obtaining the INCA-CLIP² quality label for early-stage clinical trials in the field of cancerology (including paediatric trials, which are very difficult to obtain).
The platform’s missions:
1) Ensuring development assistance for research projects sponsored by ONCOLille researchers
- Methodological and biostatistical assistance for research projects: The platform provides assistance with drawing up research protocols (in particular the choice of design, calculating the number of subjects, and the statistical analysis strategy), carrying out statistical analyses according to good practice recommendations (ICH, CONSORT), helping with interpreting results, and publication in scientific reviews.
- Clinical research studies logistics: Promotion, medical & regulatory support, assistance with investigations, access to specialised investigation platforms (biology, molecular biology, imaging, radiotherapy), assisting with management of clinical trials, and particularly screening patients who can potentially be included, and gathering data in observation logs.
- Data management using professional tools approved by the FDA: Designing observation logs, designing the eCRF, checking the consistency of data, freezing the database and data exports, and data archiving.
- Facilitating the development of clinical research studies using the Lille and regional cancer register.
2) Optimisation of clinical research and biostatistics methodology
The platform develops its own research linked to the ONCOLille SIRIC’s research orientations. The objectives of these research works are as follows:
- Improving the scope of the results of early-stage clinical trials (phases 1 and 2) through better selection of the patients included (Phase 1) with more relevant definitions of the efficacy and toxicity indicators for treatments (phase 2).
- Optimising the estimate for tumour growth/reduction depending on its response or resistance to the new treatments tested by optimising how frequently patients are monitored.
- Analysis of genome data: In the field of transcriptomics, we are working on empirical Bayesian models. We are also working on the selection of biomarkers applicable using regularisation techniques (the Lasso method for example). Lastly, we are working on improving automatic calibration techniques. We have deployed 2 full pipelines for the SNP array analysis available through R packages and in a Galaxy public instance (the bioinformatics Cloud).
- Development of statistical methods for detecting high incidence or low incidence clusters for events using scan statistics, which are very useful for epidemiological studies in the field of cancerology.
- Works concerning adjusted survival rates in relation to the quality of life using the Q-TWiST method. This method offers very high performance but is little used for assessing the quality of life of patients during tests. This method thereby enables a better therapeutic strategy and a better assessment of the benefit/risk calculation ratio.
- Putting together and validating prognostics scores in order to optimise treatment strategies and the monitoring of patients.
Examples of contributions:
– The FREGAT Project: Setting up a French national clinical and biological database concerning oesophageal gastric cancer, including clinical data, socio-economic data, and biological samples.
– Participating in the SURGIGAST national PHRC (Hospital Clinical Research Programme) entitled “Quality of life adjusted survival after palliative gastric resection plus chemotherapy versus chemotherapy alone in stage IV gastric cancer”.
– Participation in the DEREDIA (Human and Social Sciences) project: “Determinants of delay in consultation among head and neck cancer patients”.
– Participation in the KALIKOU3 (Human and Social Sciences) project: “Assessment of the impact of the emotional skills of young women (≤ 45 years of age) suffering from non-metastatic breast cancer and of their partners in relation to adjustment”.
– Participation in the REGOSARC international project: “An international double-blind, randomised, stratified phase II trial assessing the activity/toxicity of Regorafenib in sarcoma patients”.
Participation in the RECICOG project: “Geographical and socio-economic inequalities in view of the risk of recurrence of gastro-oesophageal cancer”.