I am a biostatistician and epidemiologist with research interests in cancer epidemiology and reproductive epidemiology. Since coming to Karolinska Institutet in 1999, I have developed research in numerous epidemiological projects, with a strong focus on cancer and perinatal outcomes. In 2016, I defended my thesis “Pregnancy and breast cancer: Risk patterns, tumour characteristics and prognosis”. I have a methodological interest in register-based research, epidemiological designs and survival analysis. I am also involved in developing policy and guidelines concerning research data documentation and regulations at Karolinska Institutet.
Since 2017, I am affiliated (20%) with the Cancer Registry of Norway, where I lead a project on breast cancer survival by clinical subtype and stage.
I have collaborations with clinical researchers at Karolinska University Hospital.
- 2016, PhD (Medical Sciences), Karolinska Institutet.
- 1999, MSc (Mathematical statistics), Stockholm University.
Research on cancer and pregnancy
My primary research interest is cancer in relation to pregnancy and reproductive history, with a special focus on pregnancy-associated cancer, i.e. cancer diagnosed during or within one or two years after a pregnancy. The research questions I am addressing concern the increasing incidence trend, risk patterns before and after delivery, tumour characteristics and survival. I also study other reproductive factors, such as age at births, number of children, infertility and IVF treatment, in relation to cancer risk and prognosis.
Due to improvements in cancer treatments, the number of young cancer survivors is increasing. It is important to evaluate their possibilities to form families after end of treatment. One of my research aims is therefor to study reproductive potential and fertility after cancer, both by clinical factors and by previous reproductive history.
Research on breast cancer survival
My second research interest is breast cancer among women. I am specifically studying how survival has improved over time, and how survival depends on patient and tumour factors. One of my projects relates to identifying predictors for long-term survival, given that breast cancer patients have an increased relapse risk many years after diagnosis. I am also interested in clinical subtypes of breast cancer (as defined by ER, PR and HER2 status) and survival.
Since 2017, I am affiliated (20%) with the Cancer Registry in Norway on a project on breast cancer survival. I am also using Swedish Breast Cancer Quality Registry data to address these questions.
Methods for register-based epidemiology
As a statistician and epidemiologist, I am particularly interested in finding the best way to utilize register data to estimate disease risks in the population, for example by clever study designs and statistical methods for register-based research.
In my research I utilize the large Swedish population-based health registers available for research. These unique data sources can be used to answer many questions in way that is impossible in many other countries. In some of my research projects, I develop new methodology and study designs to be able to answer our questions.
Research documentation and Data management
The quality of research is highly dependent on the quality of the underlying data. I have worked effortlessly for many years to improve the procedures for research documentation and data management within research projects at KI. This includes everything from standardized variable lists and codes, commented and structure statistical programming, version control to documentation of research projects and ethical approvals.
I have been leading the development of research documentation guidelines in our department, as well as teaching hands-on techniques for research documentation to epidemiologists, clinicians and researchers at KI and elsewhere. I am regularly an invited speaker on this topic.
In my role as an applied biostatistician, I collaborate within several research projects at MEB. For example: sleeping disturbance and risk for dementia, HPV and cervical cancer, longterm effects of breast cancer treatment. In these projects I contribute statistical expertise to a multi-disciplinary team.
I have been involved in teaching and course organising of:
• Survival analysis (biostat III), within the Doctoral Programme in Epidemiology
• Epidemiology II, within the Doctoral Programme in Epidemiology
• Competing risks and multistate models
• Epidemiological designs in a statistical framework
• Workshops on epidemiological designs and cancer survival analysis
• Good Data Management Practice in Epidemiology
• Guidelines for Data Management in Clinical Research