Course Cancer Epidemiology using the Danish Clinical Cancer Databases

The course C245/09 Cancer Epidemiology using the Danish Clinical Cancer Databases is being offered by the Graduate School of Health, Aarhus University, spring 2024.

Criteria for participation:  University degree in medicine, dentistry, nursing, or Master’s degree in other fields and/or postgraduate research fellows (PhD students and research-year medical students).

Aim: To provide students with an overview on how to take a research idea through to implementing, analyzing, and interpreting an epidemiologic study using the Danish Clinical Cancer Databases, and Denmark’s network of medical and population-based registries. Each concept will be introduced in a lecture. Through a combination of exercises and computer labs, students will be provided with guidance on implementing, analyzing and interpreting studies using data from the clinical cancer databases. Students are not required to complete an exam at the end of the course. 

Learning outcomes: The course includes lectures, exercises and computer labs on the following:

1. Identify and design a clinical epidemiologic research study using the Danish Clinical Cancer Databases – comparing and contrasting study designs in order to suitably address a research question
2. Identifying and ascertaining data from the Clinical Cancer Databases
3. Assessing study validity and implementing validity checks
4. Data analysis including data cleaning and implementing survival analysis using Stata
5. Evaluating study findings, interpreting and reporting study findings

Workload: The classroom hours are expected to be 37 hours. There will be precourse reading and preparation on top of this.

Content: The course includes lectures, exercises and computer labs on the following:

Time                   Topic

Monday am      What data can we use?

Overview of the data permissions, data sources, data variables
Introduction to the Danish Clinical Cancer Databases & main Danish health and administrative registries. Some examples:
The Danish Breast Cancer Cooperative Group (several research examples)
GROUP WORK: Students are assigned to a research topic & begin to work on assigned research topic

Monday pm         Data view and visualization of study design

Computer lab: Data cleaning and preparation of data for statistical analyses

Tuesday am          Can we trust the data?

Approaches to ensure data validity? How to deal with incomplete data; how to incorporate validity checks via validation studies; how to minimize bias in the design phase; approaches to sensitivity analyses

GROUP WORK: Students work on assigned research topic

Tuesday pm        Computer lab: Conducting a validation study

Wednesday am    How can we address a research question?

Epidemiological study designs (Identify, describe, compare and contrast study designs to address a research question).
Defining the study population; measure of exposure; measures of association
KEA Research papers

GROUP WORK: Students work on assigned research topic

Wednesday pm   Introduction to survival analyses

Computer lab: Survival analysis

Thursday am    Evaluating whether an observed association suggests a causal association: Can we trust the analysis?

Dealing with confounding, effect measure modification, and bias
Restriction, stratification, standardization, multivariate modelling
(Immortal person-time bias in cancer prognosis studies)
Examples from several KEA research papers using DBCG data

Thursday pm    GROUP WORK: Students work on assigned research topic – preparation of presentation for Friday

Friday am          How can we interpret and present our findings?

STROBE and STREGA guidelines; p-values
Evaluating whether an observed association suggests a causal association
Contextualizing research findings Example of KEA reviews (Dee – CYP2D6 & statins reviews)

GROUP WORK: Students work on assigned research topic

Friday pm          GROUP WORK: Students present assigned research topic

(10 minute presentation, 5 minute Q&A) (4 groups of 3-4)

Recommended knowledge for participation: Basics of epidemiology (undergraduate level), oncology/cancer research knowledge and some knowledge of statistics. Knowledge of a statistical program – examples will be presented in STATA or R.

Language: English

Instructors: Deirdre Cronin Fenton, Ph.D., Mette Nørgaard, M.D., Ph.D., Signe Sørup, Ph.D., Katrine Bødkergaard Nielsen, M.Sc.,     Julie Schmidt, DPhil, Jannik Wheler, MD, Peter Jepsen, MD, PhD, DMSc, Cathrine Hjorth, PhD, Therese Grønborg, Ph.D.

Venue: Aarhus University, Aarhus (other)

Participation in the course is without cost for:

• PhD students, Health Research Year students from Aarhus University
• PhD students enrolled at partner universities of the Nordoc collaboration
• PhD students from other institutions in the open market agreement for PhD courses

Course dates:

• 27 May 2024 09:00 - 15:30
• 28 May 2024 09:00 - 15:30
• 29 May 2024 09:00 - 15:30
• 30 May 2024 09:00 - 15:30
• 31 May 2024 09:00 - 15:30