Cookie Settings

We use cookies to optimize our website. These include cookies that are necessary for the operation of the site, as well as those that are only used for anonymous statistic. You can decide for yourself which categories you want to allow. Further information can be found in our data privacy protection .

Essential

These cookies are necessary to run the core functionalities of this website and cannot be disabled.

Name Webedition CMS
Purpose This cookie is required by the CMS (Content Management System) Webedition for the system to function correctly. Typically, this cookie is deleted when the browser is closed.
Name econda
Purpose Session cookie emos_jcsid for the web analysis software econda. This runs in the “anonymized measurement” mode. There is no personal reference. As soon as the user leaves the site, tracking is ended and all data in the browser are automatically deleted.
Statistics

These cookies help us understand how visitors interact with our website by collecting and analyzing information anonymously. Depending on the tool, one or more cookies are set by the provider.

Name econda
Purpose Statistics
External media

Content from external video platforms is blocked by default. If cookies from external media are accepted, access to this content no longer requires manual consent.

Name Youtube
Purpose External media

Division of Cancer Epidemiology

Prof. Dr. Rudolf Kaaks

© dkfz.de

Our division studies the causes of cancer in population groups with the aim of identifying and, if possible, avoiding risk factors so as to prevent cancer. Our key focus is on the quantification of risks associated with lifestyle, nutrition and metabolism, and immune factors. In addition, we address the question of how lifestyle may interact with genetic susceptibility factors in cancer development, as well as in cancer survival.

On the basis of established, genetic and non-genetic risk factors, we build quantitative risk models for the identification of individuals who have an increased risk of developing cancer compared to others, and who may gain increased benefit from targeted prevention measures such as regular cancer screening.

A further focus is exploring new routes for prevention and early diagnosis of cancer, as well as quality control of introduced measures. Due to their population-related approach, statistical methods and their further development are of particularly high relevance in epidemiology.

A major part of our research takes place within the setting of large-scale prospective cohort studies, such as the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Scandinavian Consortium of Maternity Cohorts. Besides these prospective studies in the general population, our division conducts studies within large cohorts of cancer patients.

FUTURE OUTLOOK
Studies within our various prospective cohorts are increasingly making use of modern, high-throughput “omics” technologies (metabolomics, genomics, epigenomics, next-generation sequencing) for the identification of risk factors and predictors for cancer and markers for early detection.
For future studies, our division has a central role in the development and set-up of the “NAKO” – a new, large-scale prospective cohort study in Germany.

Contact

Prof. Dr. Rudolf Kaaks
Cancer Epidemiology (C020)
Deutsches Krebsforschungszentrum
Im Neuenheimer Feld 280
69120 Heidelberg
Tel: +49 6221 42 2200
Fax: +49 6221 42 2203

Selected Publications

  • Serum markers of biological ageing provide long-term prediction of life expectancy-a longitudinal analysis in middle-aged and older German adults. Srour B, Hynes LC, Johnson T, Kühn T, Katzke VA, Kaaks R. Age Ageing. 2022 Feb 2;51(2):afab271. doi: 10.1093/ageing/afab271. PMID: 35150586
  • Lung cancer mortality reduction by LDCT screening-Results from the randomized German LUSI trial. Becker N, Motsch E, Trotter A, Heussel CP, Dienemann H, Schnabel PA, Kauczor HU, Maldonado SG, Miller AB, Kaaks R, Delorme S. Int J Cancer. 2020 Mar 15;146(6):1503-1513. doi: 10.1002/ijc.32486. Epub 2019 Jun 20. PMID: 31162856 Clinical Trial.
  • Evaluation of Prediction Models for Identifying Malignancy in Pulmonary Nodules Detected via Low-Dose Computed Tomography. González Maldonado S, Delorme S, Hüsing A, Motsch E, Kauczor HU, Heussel CP, Kaaks R. JAMA Netw Open. 2020 Feb 5;3(2):e1921221. doi: 10.1001/jamanetworkopen.2019.21221. PMID: 32058555
  • Circulating Immune Cell Composition and Cancer Risk: A Prospective Study Using Epigenetic Cell Count Measures. Le Cornet C, Schildknecht K, Rossello Chornet A, Fortner RT, González Maldonado S, Katzke VA, Kühn T, Johnson T, Olek S, Kaaks R. Cancer Res. 2020 May 1;80(9):1885-1892. doi: 10.1158/0008-5472.CAN-19-3178. Epub 2020 Feb 19. PMID: 32075798
to top
powered by webEdition CMS