Systematic Reviews and Meta-Analysis

Course dates

Due to demand this 4 day course will run twice:

11 - 14 December 2018
7 - 10 May 2019

Course duration

4 days (approximately 24 hours teaching, including 14 hours of lectures and 10 hours of practical sessions).
Registration will start at 8.50am on the first day, the course will finish by 4pm on the final day. There will be an optional computer practical 'Introduction to Stata' at the end of day 1 (4-5.30pm).

Course tutors

Dr Jelena SavovićDr Hayley JonesProfessor Julian Higgins(course organisers), Professor Jonathan Sterne, Sarah Dawson, Dr Philippa Davies, Dr Deborah Caldwell, Dr Alexandra McAleenan, Dr Jack Bowden, Dr Howard Thom, Dr Penny Whiting and others.

Course aims 

The course aims to introduce participants to the methodology of systematic reviews and meta-analysis.

Course objectives

By the end of the course participants should be able to:

  1. explain the need for systematic reviews and meta-analyses;
  2. list the important aspects of a systematic review;
  3. perform a comprehensive search for relevant literature;
  4. appreciate the role of tools to assess risk of bias, including their application to randomised controlled trials;
  5. explain the basic methods of meta-analysis;
  6. use Stata software to perform meta-analysis;
  7. describe issues in conducting systematic reviews of observational studies;
  8. summarise the findings of a systematic review or meta-analysis;
  9. evaluate the quality of a systematic review.

Who the course is intended for

This course is designed for clinicians, researchers, public health specialists and other health care professionals who want to perform and/or evaluate systematic reviews and meta-analyses. The course predominantly focuses on systematic reviews of healthcare interventions, although much of the material translates to systematic reviews in other areas. Sessions examine issues in systematic reviews and meta-analyses of observational studies, network meta-analysis and diagnostic test accuracy.

Participants should have knowledge of statistical methods to the level of our 'Introduction to Statistics' course. A basic appreciation of research designs (to the level of our 'Introduction to Epidemiology' course) would be helpful, as would basic knowledge of Stata.

Note for internal PhD students:

This course covers the whole systematic review process in depth. We recommend that internal PhD students seeking skills for background literature reviews consider attending ‘Literature Searching’ instead (see BMS Graduate Studies Programme). This training session will generally be sufficient unless the thesis includes a full systematic review. 

Course outline

  1. Why we need systematic reviews and meta-analyses.
  2. The systematic review process.
  3. Identifying relevant studies.
  4. Screening and data extraction.
  5. Types of data and effect sizes.
  6. Assessing risk of bias in primary studies.
  7. Statistical methods for meta-analysis.
  8. Meta-analysis of trials with numerical (continuous) outcomes.
  9. Explaining heterogeneity: subgroup analysis and meta-regression.
  10. Meta-analysis and meta-regression in Stata.
  11. Understanding, investigating and dealing with bias in systematic reviews.
  12. Systematic reviews and meta-analysis of observational studies.
  13. Introduction to reviews of diagnostic test accuracy.
  14. Introduction to network meta-analysis.
  15. Concluding and reporting a systematic review.
  16. Certainty in the evidence in a systematic review.
  17. Critical appraisal of a systematic review. 

Computer practicals on meta-analysis will be undertaken using Stata. An optional Introduction to Stata session is provided, for course participants with no previous experience of Stata or those wanting a refresher.

Please note: Computer practical sessions will be held in a computer lab, so you will not need to bring a laptop. This course will use Stata v15.

Recommended reading

Systematic Reviews in Health Care: Meta-analysis in Context, edited by Matthias Egger, George Davey Smith and Doug Altman (BMJ Books, 2001)

Introduction to Meta-analysis, by Michael Borenstein, Larry Hedges, Julian Higgins and Hannah Rothstein (Wiley-Blackwell, 2009)

Cochrane Handbook for Systematic Reviews of Interventions, edited by Julian Higgins and Sally Green (Wiley-Blackwell, 2008)

Meta-analysis in Stata, edited by Tom Palmer and Jonathan Sterne. (Stata Press, 2016)

Due to demand this course runs twice

Apply for your preferred date only. You cannot be on the waiting list for both courses or hold a place on one and be on the waiting list for the other. When the 'A' course has passed, remaining applicants will be offered the opportunity to transfer to the 'B' course if there are any remaining spaces at that time or be added to the waiting list if not.  

Booking

Bookings for the December 2018 and May 2019 courses have now closed.

Quality of teaching was excellent. It was great hearing practical advice from experts with hands-on experience. It was useful to get information about the most recent and high-quality measures and tools. I also found the lab classes and practicals valuable in understanding how to make use of this new knowledge in a practical sense.

Course feedback, December 2017

The instructors are what makes this course better than other courses with comparable content. It was clear that they all were experts in their topics.

Course feedback, June 2018

Course fee

£880

More information on course fees, fee waivers and reduced prices.

Course venue

Bristol Medical School
Canynge Hall
39 Whatley Road
Bristol
BS8 2PS
United Kingdom

Map and directions

Course refreshments

We provide morning and afternoon refreshment breaks, including tea and coffee, biscuits and fresh fruit.

If you have specific dietary needs we ask that you let us know in advance.

Lunch is not included. There are a range of local cafes and supermarkets nearby for students to purchase lunch. 

Accommodation

Information about accommodation in the area.

Contacts

For further information please email short-course@bristol.ac.uk.

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