SFOK18007U Systematic Reviews and Meta-analysis – a practical course

Volume 2022/2023
Education

MSc in Public Health Science - elective course

MSc in Health Informatics - elective course

MSc in Global Health - elective course

MSc in Human Biology - elective course

MSc in Health Science- elective course

The course will also be open to PhD students. PhD student should apply as external students in order to obtain a slot in the course:

https://healthsciences.ku.dk/education/student-mobility/guest-students/

Content

This elective course has a practical approach to the systematic review method and the meta-analysis tools. The systematic review method will include building a relevant search model, choosing the right databases for the topic, choosing in- and exclusion criteria, inclusion of studies, data extraction, and risk of bias assessment. The course will also have an analytical part where the students will learn to perform meta-analysis using R, including sensitivity analysis, subgroup analysis, and meta-regression. The goal for this course is to provide the students with enough experience to conduct a basic systematic review and meta-analysis, possibly as their master thesis.

Learning Outcome

After completed course, students are expected to be able to:

Knowledge

  • Explain how a literature search search can be made wider and how to make it more specific, by using search terms and Boolean operators.

  • Explain the differences between the biggest electronic databases and their content (Medline, Embase, Web of Science, SCOPUS, Google Scholar, and Clinicaltrials.gov).

  • Describe main characteristics for the most common quantitative study designs: case studies, case-control studies, cross sectional studies, cohort studies, randomized controlled trials, systematic reviews and meta-analyzes.

  • Discuss the methodological quality of included studies, including risk of different types of bias.

  • Describe central epidemiological elements; odds ratios, relative risks, risk differences, means, medians, standard deviations, quantiles, and confidence intervals.

  • Describe the grounds for conducting different types of meta-analyses.

  • Describe relevant terms including heterogeneity, regression types and different types of meta-analyses.

Skills

  • Conduct a protocol for a systematic review and a meta-analysis that meets the requirements of PROSPERO.

  • Build a PICO model with relevant search terms.

  • Be familiar with the PRISMA guidelines.

  • Identify relevant studies in title / abstract and full text.

  • Use relevant methodological checklists on the included studies.

  • Identify and extract relevant information and results.

  • Choose a relevant statistical approach and the right types of analysis.

  • Illustrate results from risk of bias assessment.

  • Discuss and use information on risk of bias, heterogeneity and precision.

  • Present the results and conclusion in a Summary of Findings (SoF) table by using the GRADE Approach.

Competences

  • Plan and perform a systematic literature search to identify the most relevant literature according to the search question.

  • Evaluate methodological quality of the included studies, using relevant checklists.

  • Extract relevant results and information and use these in a meta-analysis.

  • Use stratified analyzes and meta-regressions to explain heterogeneity in the results.

  • Make a statement on the estimate and the underlying evidence using a SoF table.

Literature and other teaching matrials will be uploaded to Absalon, along with relevant reading guides. Short videos and web-based tutorials will be prioritized over hard literature (e.g. book chapters and articles), whenever possible.

Software:

The R programming language will be used. You will be able to download R and RStudio here:

https:/​/​www.r-project.org/​

https://www.rstudio.com/

In case you are not familar with R, please watch some of the following introductory videos:

https:/​/​www.youtube.com/​watch?v=_V8eKsto3Ug&t=2487s

https:/​/​www.youtube.com/​watch?v=fDRa82lxzaU&t=1405s

https:/​/​www.youtube.com/​watch?v=BvKETZ6kr9Q&t=1361s

Epidemiology on a level that equals the course ’introduktion til epidemiologi’ and statistic knowledge on a level that equals the course ”introduktion til statistik”.

Some familiarity with R. Please do some tutorials before the beginning of this course.

https:/​/​www.youtube.com/​watch?v=_V8eKsto3Ug&t=2487s
https:/​/​www.youtube.com/​watch?v=fDRa82lxzaU&t=1405s
https:/​/​www.youtube.com/​watch?v=BvKETZ6kr9Q&t=1361s
Lectures and group work including student presentation and plenum discussion of the assignments.
  • Category
  • Hours
  • Lectures
  • 40
  • Preparation
  • 180
  • Project work
  • 32
  • Exam
  • 10
  • Total
  • 262
Continuous feedback during the course of the semester

Discussion and class activities will provide ongoing feedback about students understanding of the methods.

Credit
10 ECTS
Type of assessment
Oral examination
Type of assessment details
Oral presentation on the last day of the course. Papers for presentation should be uploaded in Absalon after the presentation.
Aid
All aids allowed
Marking scale
passed/not passed
Censorship form
No external censorship
One internal examiner
Exam period

Please see the exam schedule at KUnet 

Re-exam

Please see the exam schedule at KUnet 

 

Criteria for exam assesment

To achieve the grade Passed, the student must adequately be able to:

Knowledge

  • The student should be able to explain how a literature search can be made wider and how to make it more specific.

  • The student should be able to explain the differences between the biggest electronic databases and their content (Medline, Embase, Web of Science, SCOPUS, Google Scholar, and Clinicaltrials.gov).

  • The student should be able to describe main characteristics for the most common quantitative study designs: case studies, case-control studies, cross sectional studies, cohort studies, randomized controlled trials, systematic reviews and meta-analyses.

  • The student should be able to discuss the methodological quality of included studies, including risk of different types of bias.

  • The student should be able to describe central epidemiological elements; odds ratios, relative risks, risk differences, means, medians, standard deviations, quantiles, and confidence intervals.

  • The student should be able to describe the grounds for conducting different types of meta-analyses.

  • The student should be able to describe relevant terms including heterogeneity, regression types and different types of meta-analyses.

 

Skills

  • The student should be able to conduct a protocol for a systematic review and a meta-analysis that meets the requirements of PROSPERO.

  • The student should be able to build a PICO model with relevant search terms.

  • The students should be able to navigate the PRISMA checklist and flowchart.

  • The student should be able to identify relevant studies in title / abstract and full text.

  • The student should be able to use relevant methodological checklists on the included studies.

  • The student should be able to identify and extract relevant information and results.

  • The student should be able to choose a relevant statistical approach and the right types of analysis.

  • The student should be able to illustrate results from risk of bias assessment.

  • The student should be able to discuss and use information on risk of bias, heterogeneity and precision.

  • The student should be able to present the results and conclusion in a Summary of Findings (SoF) table by using the GRADE Approach.

 

Competences

  • The student should be able to plan and perform a systematic literature search to identify most relevant literature according to the search question.

  • The student should be able to evaluate methodological quality of the included studies, using relevant checklists.

  • The student should be able to extract relevant results and information and use these in a meta-analysis.

  • The student should be able to use stratified analyzes and meta-regressions to explain heterogeneity in the results.

  • The student should be able to make a statement on the estimate and the underlying evidence using a SoF table.