The general objective for this study is to evaluate the survival and disease-free period of women participating in screening programs for breast cancer with a cancer diagnosed during the screening or an interval cancer, specifically true interval cancers and false negatives.
The cohort has information of women participating in breast cancer screening programs in Spain between 2000 and 2009, with a breast cancer diagnosed during the screening or between the screening interval (interval cancer), specifically true interval cancers and false negatives. The investigators obtained woman-related information (including breast density), tumor-related information (including tumor phenotype), and follow-up information (including relapses, second neoplasms and vital status at the end of follow up (June 2014)).
Expected results: Nowadays there are no results of cohort analysis of the diagnostic process of care that integrates all those different aspects. This study will complement the evaluation of population screening, specifically the interval cancer and the impact on survival and disease-free period taking into account relevant variables like breast density, tumor phenotype, clinical complications, readmissions, and the surgical approach.
This study is part of a broader project (CAMISS study) coordinated by the Evaluation of Health Services of Epidemiology and Public Health Group, which consists of two cohorts of women diagnosed with breast cancer: a prospective cohort (n=2,040 incident cases of breast cancer diagnosed in 18 hospitals of 5 Spanish regions) (Identifier in ClinicalTrials.gov: NCT02439554) and a retrospective cohort of screened women diagnosed with breast cancer between 2000 and 2009 in two Spanish regions (n=1,086).
The general objective of the CAMISS study is to evaluate different aspects of health care received by patients with breast cancer like the diagnostic process, treatment, complications, survival, costs and quality of life to provide information to improve the effectiveness and cost-effectiveness of interventions, reduce variability, have better predictive rules and increase the quality of life.
