Biostatistics at KEP/CPE

The Clinical Epidemiology Division (KEP) and the Centre for Pharmacoepidemiology (CPE) employ around 25 statisticians who provide biostatistical expertise to clinical and epidemiological research in a range of areas including, rheumatology, diabetes and other chronic diseases, cardiovascular disease, cancer, reproductive epidemiology, drug effectiveness and safety. All research groups employ both junior and senior statisticians as well as doctoral students and postdocs.

Much of the work done by statisticians is centered around the design and analysis of epidemiological studies. Our biostatisticians have a wide range of backgrounds including mathematical statistics, statistics, engineering, data science, health economics, and epidemiology. Although all statisticians are closely integrated in the divisions’ research groups, they also share knowledge and experiences across the research groups through joint seminars series and social activities.

Statistical areas that appear frequently in the applied research include survival analysis, pharmacoepidemiology, safety and effectiveness analyses, predictive modelling, machine learning, causal inference, genetic epidemiology, heritability and familial risk studies, meta-analysis, and federated analysis. The statistical challenges that arise in the research projects can sometimes also prompt methods development in biostatistics, epidemiology and pharmacoepidemiology. 

While statisticians at KEP and CPE have many methodological interests in common, examples of research profiles and specializations at KEP and CPE are highlighted below.

Clinical Epidemiology Division

The research at KEP is centered around clinical epidemiology where national and regional register-based health care data, often supplemented with information from medical records, biological samples and surveys, are used to address questions that aim to improve patient health care and clinical practice. The work in biostatistics is primarily conducted through collaborative research in the various research groups at KEP. The projects have a strong clinical anchoring and biostatisticians and clinical researchers work with expertise in specific medical research areas work closely together. We also encounter situations in international collaborations where register data from different countries are combined which raises specific statistical challenges.

Collaboration within national clinical networks (e.g., hospitals, quality registers and disease area specialists) is common. For example, KEP hosts several large data linkages and a quality register (The pregnancy register) and we collaborate closely with external colleagues around these research resources.

KEP is also home to the Research Schools for Clinicians where biostatisticians are an important integrated part of the research school as keen lecturers of methods used in epidemiology and biostatistics.

Centre for Pharmacoepidemiology

The Centre for Pharmacoepidemiology (CPE), one of the research groups at KEP, works in a dynamic environment at the intersection of academia, healthcare, authorities and the pharmaceutical industry. CPE conducts academic research on drug safety, drug effectiveness and drug utilization and carry out projects on behalf of authorities and the business community in the area of pharmacoepidemiology. CPE has over the years developed specific pharmacoepidemiology expertise in the areas of: reproductive medicine, psychiatry, cancer, cardiovascular disease and neurological diseases

A large part of our research is based on data from the national registers held at the National Board of Health and Welfare and Statistics Sweden, quality registers or local databases (e.g., Stockholm VAL database or VEGA from the Gothenburg area) as well as corresponding registers from other countries, especially the Nordic countries.

Statisticians at CPE participate in all stages of the process from protocol to report and are involved in the study design in collaboration with the epidemiologists. CPE has also developed a data model called CDM (common data model) which can be used in the studies. Moreover, the statisticians at CPE take a special interest in the study and development of drug exposure definitions.

Degree projects (examensarbete) in biostatistics or epidemiology

We welcome applications from master level students who are interested in doing their degree projects at KEP. In the past we hosted students with both statistical and medical backgrounds from Karolinska institutet or other universities who have performed their projects with us. Before you contact us, please browse our web pages to identify researchers working in an area that interests you. It´s recommended that you include a copy of your CV and academic transcript (resultatintyg) when you contact us to facilitate finding a good match.

Example publications from our group

Sibling comparison studies. 
Sjölander A, Frisell T, Öberg A. 
Annual Review of Statistics and its Applications 9, 2022 71-94.

Generalizability and effect measure modification in sibling comparison studies
Sjölander A, Öberg S, Frisell T
Eur J Epidemiol 2022 May;37(5):461-476.

Predictive models for clinical decision making: Deep dives in practical machine learning
Eloranta S, Boman M
J Intern Med. 2022 Aug;292(2):278-295.

A multistate model incorporating estimation of excess hazards and multiple time scales.
Weibull CE, Lambert PC, Eloranta S, Andersson TML, Dickman PW, Crowther MJ
Stat Med  2021 Apr;40(9):2139-2154.

Methods for constructing treatment episodes and impact on exposure-outcome associations.
Pazzagli L, Brandt L, Linder M, Myers D, Mavros P, Andersen M, Bahmanyar S
Eur J Clin Pharmacol 2020 Feb; 76(2):267-275

 

Staff

Senior lecturer

Fredrik Granath

Associate professors and senior research specialists

Thomas Frisell

Sandra Eloranta

Helga Westerlind

Applied Statisticians and data analysts

Abid Lashari

Arda Yilal

Bénédicte Delcoigne

Caroline Weibull

Daniel Sjöholm

Daniela Di Giuseppe

David Hägg

Fanny Bergström

Frode Boman

Gustav Bruze

Hannah Bower

Henrik Svanström

Ida Hed Myrberg

Karina Patasova

Laura Pazzagli

Lena Brandt

Marie Linder

Matti Bryder

Pär Karlsson

Renata Zelic

Sara Ekberg

Stefanie Antonilli

Viktor Wintzell

Xingrong Liu

PhD students

Anton Öberg Sysojev

Joshua Entrop