Course Cancer Epidemiology using the Danish Clinical Cancer Databases

The course C245/12 Cancer Epidemiology using the Danish Clinical Cancer Databases is being offered by the Graduate School of Health, Aarhus University, spring 2027.

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).

Requirements 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 R.

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 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 or R
5. Evaluating study findings, interpreting, and reporting study findings

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

Dates and time: To be decided. Morning sessions 9.00 to 11.45 am. Afternoon sessions 12.30 to 3.30 pm 

Place:  To be decided

Language: English

Instructors: Deirdre Cronin Fenton, PhD, Mette Nørgaard, MD, PhD, Cathrine Hjorth, PhD, Julie Schmidt, DPhil, Therese Grønborg, PhD, Jannik Wheler, PhD, and student assistant teachers.

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. Setting up a study. 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

Dee

Monday pm

Data view and management, retrieving diagnostic codes, variables, etc.

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

Jannik
Student assistant

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

Mette

Tuesday pm

Computer lab: Continued data preparation and conducting a validation study

Therese

Jannik
Student assistant

Wednesday am

How can we address a research question?

Types of research questions; Defining the study population; Epidemiological study designs (Identify, describe, compare, contrast, and visualize study designs to address a research question); Measures of association.

Examples from several KEA research papers using DBCG data

GROUP WORK: Students work on assigned research topic

Julie
Cathrine

Wednesday pm

Computer lab: Introduction to time-to-event analyses

Therese

Student assistant

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

Dee

Thursday pm

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

Julie

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

Dee
Mette

Friday pm

GROUP WORK: Students present assigned research topic

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

Dee
Mette

Instructors: Deirdre Cronin Fenton, Mette Nørgaard & KEA faculty.

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 coursess

Course dates:

• 24 May 2027 09:00 - 15:30
• 25 May 2027 09:00 - 15:30
• 26 May 2027 09:00 - 15:30
• 27 May 2027 09:00 - 15:30
• 28 May 2027 09:00 - 15:30