REALYSA cohort is a population-based epidemiological platform in real-life for lymphomas designed to enrich prognostic data, by integrating together epidemiological, clinical and biological data.
REALYSA is a platform perfectly set up to
* Study prognostic factors using integrated epidemiological and biological data (genetics), to better characterize the determinants of refractoriness and relapse in patients with lymphoma, to follow the growing number of survivors and describe median to long-term sequela, second cancer, quality of life (QoL)… * Document treatment effectiveness in real life and observance * Address socio-economical questions
Signature of the consent form for participation in the REALYSA cohort
Aged over 18 at the time of inclusion
Diagnosed with lymphoma in the last 6 months (180 days)
Lymphoma subtype belonging to at least one of the 7 histological subtypes: diffuse large B-cell lymphoma, follicular lymphoma, mantle cell lymphoma, marginal zone lymphoma, T-cell lymphoma, Hodgkin's lymphoma, Burkitt lymphoma
Anti-lymphoma treatment already received (except pre-phase: typically corticosteroids, vincristine, cyclophosphamide, etoposide, alone or in combination)
Documented HIV infection
Chronic lymphocytic leukemia/small lymphocytic lymphoma
Hairy cell leukemia and variant
Patients diagnosed with lymphoma in the last 6 months.
Cohort
Prospective
Real-life epidemiological platform of lymphoma in France
Other interventionThe REALYSA database will be described with the following characteristics: * Number of patients included per month in total and according to subtype of lymphoma * Number of patients in each region in total and according to subtype of lymphoma
Progression-Free Survival (PFS)
Number of patients included per month in total and according to subtype of lymphoma
Number of patients in each region in total and according to subtype of lymphoma
Progression-Free Survival (PFS)
Event-Free Survival (EFS)
Representativeness of the included population
Study population must show a good representativeness of the source population regarding demographic or diseases characteristics, to be able to generalize our results. Indeed, the representativeness of the study population can only be evaluated in areas covered by population-based cancer registries (PBCR) by comparing cases included in the REALYSA project to incident lymphoma cases registered in the general population (PBCR of the FRANCIM network).
Representativeness of the included population
Study population must show a good representativeness of the source population regarding demographic or diseases characteristics, to be able to generalize our results. Indeed, the representativeness of the study population can only be evaluated in areas covered by population-based cancer registries (PBCR) by comparing cases included in the REALYSA project to incident lymphoma cases registered in the general population (PBCR of the FRANCIM network).
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Hospices Civils de Lyon
Lead sponsor
The Lymphoma Academic Research Organisation
Collaborator
