Authors:
Thomas Ostermann
1
;
Sebastian Unger
1
;
Michaela Warzecha
2
;
Sebastian Appelbaum
1
;
Daniela Recchia
1
;
Holger Cramer
3
and
Heidemarie Haller
4
Affiliations:
1
Department for Psychology and Psychotherapy, Witten/Herdecke University, Alfred Herrhausen-Straße 50, 58448 Witten, Germany
;
2
Medical Informatics, University of Applied Sciences Dortmund, Emil-Figge-Str. 42 44227 Dortmund, Germany
;
3
Institute for General Practice and Interprofessional Care, University Hospital Tuebingen and Bosch Health Campus, Stuttgart, Auerbachstraße 110, 70376 Stuttgart, Germany
;
4
Department of Internal and Integrative Medicine, Evang. Kliniken Essen-Mitte, Faculty of Medicine, University of Duisburg-Essen, Am Deimelsberg 34a,45276 Essen, Germany
Keyword(s):
Clinical Registry, Breast Cancer, Database, Baseline Characteristics.
Abstract:
Cancer is one of leading causes of mortality worldwide. According to GLOBOCAN database, 19.3 million new cancer cases and 10 million cancer deaths worldwide were counted in 2020. Thus, there is an absolute necessity for statistical data on cancer incidence and treatments. This is mainly done by cancer registries, which aim at collecting, managing, and analyzing health and demographic data on individuals diagnosed with cancer. As more and more patients make use of integrative oncology to optimize their health and quality of life during and after cancer treatment, it is important to gather clinical registry data of complementary as well as conventional cancer care. The INTREST registry is the first approach that aims to identify predictors of treatment-response in women undergoing individualized, integrative breast cancer treatment. This article reports on the technical realization and representativity of the registry based on 3,341 eligible women and 885 cases included in interim stat
istical analysis. The analyses show that the INTREST sample of women suffering from breast cancer does not significantly differ from population-based registries and pragmatic trial data of breast cancer patients in Germany with respect to main sociodemographic and clinical cancer data. However, completeness, particularly in tumor classification, currently is a major limitation.
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