After graduation at the University of Lund I started working as a medical oncologist at Department of Oncology, Karolinska Hospital, in 1984. During my sixteen years at Radiumhemmet I initiated and headed the Hereditary Breast Cancer Unit and later the Cancer Epidemiology Unit. I defended my thesis in the field of Radiation Epidemiology in 1991.
I started working as a full time epidemiologist at the Department of Medical Epidemiology and Biostatistics in 2000. Today my research focus is breast cancer. Part time I am moving back to clinical practice with a focus on clinical research as I just received a part time position at the South General Hospital (Södersjukhuset).
Since 1996 I have coordinated six European Commission and three NIH projects. Besides the ordinary national funding agencies I have received funding from private donations and the Stockholm County Council.
My strength as a researcher is that questions asked and hypothesis generated are all based in my clinical background. I want my results to have clinical implications.
However, research is not the most important part of life, that’s my three sons, two at home and one at the University of Lund.
Short presentation of current research
My overall and most important scientific goal is to lower the incidence and mortality of breast cancer, a potentially fatal disease that is increasing dramatically throughout the world. One woman a minute is diagnosed with breast cancer in Europe.
In order to do decrease incidence, a tool that identifies the individual risk of breast cancer has to be identified. Such a tool should answer the question "Who are the women that will be diagnosed with breast cancer?". The risk prediction tool has to include detailed information on lifestyle factors, genetic markers and something called mammographic density. Several of my projects aim to identify these markers. When we are able to identify women at high risk we will offer means to influence the risk as described in the Prisma study below.
The Karma project
The Karma project is conducted in close collaboration with four hospitals in Sweden, Södersjukhuset, Helsingborg, Landskrona and Lund. Women attending a mammography, screening or clinical, at any of these hospitals were invited to participate in the Karma project. Upon acceptance, participants filled out a web-based questionnaire and donate blood. We also ask for informed consent to store the processed and raw mammograms and to link the personal ID to the Swedish Inpatient, Prescription, Cancer, Emigration/Immigration and Cause of Death Registers. Participants are also linked to the nationwide Breast Cancer Registry (INCA). During 27 months, January 2011 – March 2013, 71,876 women chose to participate in Karma.
The Karma cohort is the best characterized breast cancer cohort in the world and a unique resource for future studies of risk and prognosis of breast cancer. Ourselves, we are totally focused on generating a risk prediction model allowing the identification of the individual risk of breast.
An important aspect of the Karma project is that data are shared with researchers outside the group, department and country. We have built the Karma Research Platform that enables outside researchers to browse the content of Karma and request data. Several projects have been initiated ranging from quality of life to exosomes. The only prerequisite, besides ethics, is that results should be fed back in to the database when published, enabling the next generation of researchers to benefit from the data.
The COGS project
The Collaborative Oncological Gene-environment Study, COGS, is a European Commission funded project with the overall objective to identify the genetic determinants of breast, ovarian and prostate cancer.
I coordinated this gigantic effort, including 167 research groups, in close collaboration with Professor Doug Easton in Cambridge. By 2012 more than 250,000 individuals had been genotyped using a tailor made Illumina array, the iCOGS chip, including 200,000 SNPs. The first major publications emerged in March 2013 and can be found in Nature Genetics. To quickly understand the impact of COGS, please see the list below. The number of SNPs identified before and after the initiation of the COGS project are given.
- Breast cancer: pre-COGS SNPs: 27; COGS SNPs: 92; total number of SNPs: 119
- Ovarian cancer: pre-COGS SNPs: 4; COGS SNPs: 14; total number of SNPs: 18
- Prostate cancer: pre-COGS SNPs: 42; COGS SNPs: 48; total number of SNPs: 90
Mammographic density, the radiolucent part of the mammogram, consists of glandular and connective tissue. Mammographic density is a strong risk factor for breast and is influenced by age, BMI and hormone replacement therapy. The anti-hormonal therapy administrated to breast cancer patients post surgery decreases density. We have recently shown that a density decrease while on adjuvant tamoxifen is a strong prognosticator and influences breast cancer survival beyond 15 years of diagnosis.
Measuring density for all Karma participants where we collected ≈ 500,000 mammograms, could only be done in a fully automated way. We have therefore teamed up with the Volpara company that provide one of the few FDA approved density measurement devices. In our first publication we found that Volpara mimicked the measured results of the “gold standard” Cumulus, that it predicted risk of breast cancer, was influenced by the established genetic markers related to mammographic density and that it was not machine dependent.
Mammographic density reduction is a prognostic marker of response to adjuvant tamoxifen therapy in postmenopausal patients with breast cancer.
J. Clin. Oncol. 2013 Jun;31(18):2249-56
Automated measurement of volumetric mammographic density: a tool for widespread breast cancer risk assessment.
Cancer Epidemiol. Biomarkers Prev. 2014 Sep;23(9):1764-72
The Karisma project
The possible primary preventive measures for breast cancer ranges from increased physical activity to prophylactic mastectomy. However, lifestyle changes such as increased physical activity, weight loss and reduced intake of alcohol will only have minute influence on risk. Prophylactic removal of the breasts will dramatically lower the risk of breast cancer but at a high prize. An alternative would be risk-reducing medication where a number of studies have shown dramatic effects in breast cancer incidence. As an example, tamoxifen administrated to perfectly healthy women reduces the risk of breast cancer with 40-60%.
The Karisma project will be the first project to use a comprehensive risk model for identification of women in need of risk-reducing medication. We will recruit participants directly from the Karma Cohort. Karma participants identified as having a lifetime risk >20% will be invited to Karisma. Before the main Karisma study begins we will identify the tamoxifen dose that has the highest risk reducing effect and the lowest frequency of side effects. The optimal benefit vs risk ratio will be identified using a novel approach where mammographic density is used as a proxy for therapy response.
We have recently received a grant from the Stockholm County Council and the Karisma study will start during 2015.
I am a professor of radiation epidemiology, lately with a focus on radiation associated late adverse health effects in women diagnosed with breast cancer. Recently, we managed to estimate the dose dependent risk of a myocardial infarction and identify particularly susceptible subgroups of women. This paper has had an enormous influence on how breast cancer patients are treated and has by far the highest citation rate of my papers.
Another important contribution was a paper published in 2004. We managed to show that low doses of ionizing radiation, equivalent to the dose of a CT scan of the skull, delivered in infancy influenced cognitive function in adult life. A finding that changed the way premature babies are handled.
Risk of ischemic heart disease in women after radiotherapy for breast cancer.
N. Engl. J. Med. 2013 Mar;368(11):987-98
I conduct most of my projects in close collaboration with Professor Kamila Czene. Our group at the Department of Medical Epidemiology and Biostatistics consists of post docs and students, research nurses, data base managers, project leaders and administrative personnel. Most analyses are conducted in collaboration with statisticians at the department. We both have extensive and intense international collaboration.
Current supervision of PhD students