The Course

Master the use of meta-analysis in cardio

Course Details

Course Directors

G.Savarese (Sweden) and G. Rosano (UK)


Meta-analyses represent the top of the scientific evidence and their results constitute the pillars of medical guidelines.

Meta-analyses are increasingly popular. A meta-analysis is capable of generating new knowledge and answer important research questions in light of apparently heterogeneous data and empirical estimates. Access to patient level datasets is not needed for performing aggregated data meta-analyses, allowing researchers to generate new evidence based on data from available published literature.

Cons of this approach are that many low-quality meta-analyses are published, and often even important peer-reviewed journals are not able to correctly judge on the methodological quality of this type of study design.


The goal of this course is to provide participants with the knowledge and skills to independently perform and publish a meta-analysis or a systematic review for a high-impact journal.


Session 2

Module 1: September 28th 2022

Module 2: October 12th 2022

Module 3: Oct. 24th and 25th 2022

Module 4: November 9th 2022

Module 5: November 23th 2022

Module 6: December 5th 2022

Session 2

Module 1: September 28th 2022

Module 2: October 12th 2022

Module 3: Oct. 24th and 25th 2022

Module 4: November 9th 2022

Module 5: November 23th 2022

Module 6: December 5th 2022


Module 1 –
(3 hours) –
17h00 – 20h00
CET – Online

• Introduction (5 min)
• Why conduct a meta-analysis? (30 min) (Rosano G)
• Systematic reviews and meta-analyses: definitions, protocols, literature search, studies selection and quality assessment (1 hr) (Savarese G)
• 10 min break
• Design of a meta-analysis (1hr15) (Orsini N and Savarese G)
• Conclusion

Savarese G
Rosano G

Orsini N

Module 2 –

• – Measures of effects (hazard ratios, odds ratios, relative risks)
– Test of hypothesis, heterogeneity
– Fixed effect model, random effects model, publication bias
– Sensitivity analyses (Meta-regression, subgroup analyses and leave-one-out meta-analysis)

Orsini N
Savarese G

Module 3 –
2 days ‘Face
to Face’
(Or ‘Hybrid’
for those
who cannot

Day 1 (6 hr)

• Hands on (3 hr):
1. Introduction and key elements of Stata
2. Create a dataset on Stata
3. Data checking
4. Estimatation and interpretation of the statistical models
5. Data visualization (Forest Plot)
6. Statistical assessment of heterogeneity

• Supervised lab (3 hr)

Day 2 (6 hr)

• Hands on (1.5 hr):
1. Publication bias (Funnel plot)
2. Sensitivity analysis (Subgroup analysis and leave one out meta-analysis)
3. Meta-regression

• Supervised lab (1.5 hr)

• Inspirational talks (Chair: Rosano G):
1. Meta-analysis on intravenous iron and EMPEROR-pooled: methodological aspects and clinical implications (Anker A) (30 min)
2. Pooling PARADIGM-HF and PARAGON-HF: methodological and clinical implications (30 min)
3. Discussion (15 min)

• Participants will then choose a topic to perform a meta-analysis in small groups guided by the faculty (1 hr). Aim is 1 manuscript / analysis for each group almost finalized by course end

Orsini N
Savarese G
Rosano G
Anker S
Lund L

Module 4 –
(3 hours)

• Filling the gaps: discussion on the methodology of the meta-analyses assigned to participants

Savarese G
Orsini N

Module 5 –
(3 hours)

• How to write a meta-analysis and get it published

Rosano G
Metra M

Module 6 –
(3 hours)

• Follow-up discussion on the results of meta-analyses performed by participants

Rosano G
Savarese G

Orsini N


Course participants should have:

  • Background education in medicine, biomedicine or biostatistics.
  • Note that a specific knowledge in cardiology is not required. Participants could be interested in different fields since the methodology will also be appliable to non-cardiovascular research.

Educational Objectives

At the end of the course, the participants will be able to:

  • Perform a well-structured literature search to be used for a meta-analysis or a systematic review
  • Extract data from published literature and prepare a dataset to be used for qualitative or quantitative analyses
  • Run a meta-analysis, including assessment of heterogeneity, meta-regression analysis, one study removed meta-analysis, assessment of publication bias, subgroup analyses
  • Write a manuscript which will fulfill all the requirements for reporting the results of a meta-analysis
  • Critically discuss published meta-analyses and systematic reviews

Teaching & Learning Tools

Participants will be provided with:

  • A trial version of the STATA software
  • Important reading material to facilitate learning
  • Power point presentations shown during the course



Meet and learn from experts in the field of meta-analyses



Receive training and personal guidance on your results



In-person or Zoom sessions, along with some pre-recorded videos

Join Us for This Intensive Course
Boost Your Career With This Advanced Course On Meta Analyses

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