New Sights in Cancer Survival Analysis: Non-clinical Determinants of Survival for Patients with Cancer
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Survivorship and Quality of Life".
Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 22797
Special Issue Editor
2. Calvados Digestive Cancer Registry, University Hospital of Caen, 14000 Caen, France
3. Epidemiology Research and Evaluation Unit, Department of Research, University Hospital of Caen, Avenue de la Côte de Nacre, CEDEX, 14033 Caen, France
Interests: survival; contextual effect; socioeconomic factors; deprivation; multilevel analysis; centre effect; population-based studies; hierarchical-structured data; aggregated data
Special Issue Information
Dear Colleagues,
Almost all research on prognostic factors for cancers focuses on intrinsic factors related to the disease or the individual. However, many extrinsic factors also have a strong influence on the chances of survival of patients: their social environment, the place where they are treated, the organization of the health system. The analysis of these factors requires unbiased quality data and adapted statistical analysis models. A good understanding of these factors in general explanatory models and their integration into well-conducted interventional research protocols would allow the implementation of an evidence-based public health policy. This Special Issue of the journal illustrates the importance of non-clinical prognostic factors through several examples from population-based studies. It also brings together the general concepts and explanatory models allowing a general understanding of the mechanisms of social determination of cancer prognosis as well as several conceptual frameworks which are particularly relevant for probing a chronic, multifactorial disease such as cancer.
Prof. Dr. Guy Launoy
Guest Editor
Manuscript Submission Information
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Keywords
- survival
- contextual effect
- socioeconomic factors
- deprivation
- multilevel analysis
- center effect
- population-based studies
- hierarchical-structured data
- aggregated data
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