Meta-Analysis of Clinical and Basic Science Research

July 10 - July 26, 2023

Part of the Summer Institute in Innovative Methodologies

Evidence-based medical practice is based on the consolidation of best research evidence with clinical and patient expertise. Systematic reviews and meta-analyses are important tools for synthesizing evidence needed to inform clinical decision making and policy. In clinical research, systematic review and meta-analysis are regarded as the cornerstone of evidence-based medicine. In basic science, attempts to evaluate prior literature in such rigorous and quantitative manner are rare, and narrative reviews are prevalent. Regardless, methods to synthesize basic research to inform translational studies are required to minimize the translational gap between bench and bedside.

The goal of this course is to provide a theoretical foundation, computational resources and workflow outline for performing a systematic or rapid review followed by meta-analysis of a clinical or basic research topic. Participants will design and conduct a rapid-review-based meta-analysis over the duration of the course. This will serve as a working example to facilitate discussion of the meta-analytic process and will be used to highlight challenges and obstacles that one may encounter during data synthesis. We will discuss each step of the meta-analytic process including search strategy design, data extraction, analysis of heterogeneity, data-synthesis and meta-regression along with emerging trends. By the end of the course, participants will be equipped with the tools and knowledge to conduct a meta-analysis in their field of interest.

We will only use open source software and you can bring your own data to analyze in our course. All our course contents will be offered online using McGill’s management system, MyCourses. Course contents will be delivered using videos, in-person interactive workshops via Zoom and much more. Come join us this summer to learn meta-analysis in your field of interest.


Day 1 Monday, July 10


9:00am - 11:00am

Lecture 1 Introductions, overview of the course, discussion of expectations

In person remotely

To be completed by July 11

Lecture 2 Introduction to quantitative literature reviews: Hierarchy of evidence, PRISMA, research question

Lecture 3 Search strategy & article retrieval: Database search and retrieval, introduction to Endnote/Rayyan

On your own

Day 2 Tuesday, July 11


9:00am - 11:00am

Discussion of lectures 2, 3

Project planning: research question, search strategy for rapid review

In person remotely

Independent work on formulating research question, search strategy for the rapid review, and identifying the set of papers

Individual/group work

Day 3 Wednesday, July 12


9:00am - 11:00am

Instructions for project presentations

Questions about independent projects

In person remotely

To be completed by July 14

Lecture 4 Data Acquisition Methods: Identifying data for extraction; quality assessments individual vs. aggregate data, graphical/tabular extraction

Lecture 5 Overview of Effect sizes, Data Preparation: Unit, error conversions, parameter assumptions

On your own

Day 4 – Thursday, July 13


Independent work on preparing a meta-analysis dataset, complete screening

individual/group work

Day 5 – Friday, July 14


9:00am - 11:00am

Discussion of lectures 4,5

Questions about the independent projects

In person remotely

Independent work on preparing a meta-analysis dataset, complete screening & data extraction

Individual/group work

Day 6 – Monday July 17


Scheduled individual meetings to work on the projects

In person remotely


Day 7 – Tuesday, July 18


9:00am - 12:00am

Mid-course project presentations

In person remotely



Day 8 – Wednesday, July 19


To be completed by July 20


Lecture 6 Introduction to different weighting schemes: fixed effect and random effects models

Lecture 7 Heterogeneity: quantifying extent of inconsistency between studies



On your own

Day 9 – Thursday, July 20


9:00am - 11:00am

Discussion of lectures 6, 7

Questions about independent projects

In person remotely

To be completed by July 24

Lecture 8 Advanced analysis: subgroup analysis, meta-regression

Lecture 9 Product of meta-analysis

On your own

Day 10 – Friday, July 21


Independent work on meta-analysis of your datasets

Individual/group work

Day 11 – Monday, July 24


9:00am - 11:00am

Discussion of lectures 8, 9

Questions regarding independent projects

In person remotely

Independent work on meta-analysis of your datasets

Individual/group work

Day 12 – Tuesday, July 25


Independent work on meta-analysis of your datasets

Individual/group work

Day 13 – Wednesday, July 26


9:00am - 12:00am

Presentations & Discussion of Projects Final discussion and reflections on the course

In person remotely

Instructors and Organizers

Svetlana V Komarova, PhD

Associate Professor, Division of Biomedical Sciences, Faculty of Dentistry, McGill University

Dr. Svetlana Komarova is an expert in systematic reviews and meta-analysis, who had extensively published on the subject. Dr. Komarova has diverse research interests in the basic science related to the physiology of bone cells, as well as the relationship between the function of bone cells and micro- and macroenvironment of the organism. She has successfully used the methodology of systematic reviews and meta-analysis to examine traditional clinical questions, such as how bone health is affected in patients with hematopoietic disorders (Steer et al., J Bone Miner Res 2017), and to questions related to cellular function, such as quantification of ATP release from mechanically stimulated cells (Mikolajewicz et al., J Cell Sci, 2018). Dr. Komarova develops computational support for the quantitative literature review projects, including the published guide to meta-analysis in basic science (Mikolajewicz & Komarova, Front Physiol, 2019) and ongoing studies that involve statistical modeling to assess the performance of different meta-analytic models as well as software support for data extraction and curation. Dr. Komarova developed the current course in 2017 and successfully gave it in the Summer Institute of 2018 and 2019.


Before June 1st

After June 1st

Students and trainees from McGill University and its affiliated hospital

$520 CAD

$580 CAD

Applicants working or studying in low- and middle-income countries

$600 CAD

$665 CAD

Other students and trainees from high income countries who are registered at a college or university

$730 CAD

$810 CAD

All other applicants

$1,030 CAD

$1145 CAD

A 12% discount will be granted to those participating in 2 Summer Institute courses. In addition, participants of previous editions of the Summer Institute can obtain a discount of 10% on their 20212 registration. To qualify for this discount, please contact Kendra McLaughlin (kendra.mclaughlin [at]

Fees include a course package and a certificate of participation.

Recommended Readings

Borenstein, M. (2009). Introduction to meta-analysis. Chichester, U.K.: John Wiley & Sons.

Potential Participants

All health researchers interested in conducting quantitative literature reviews will benefit from this Summer Institute. The institute is open to anyone with a background in research methodology and basic statistics who is interested in developing the skills needed to understand, design and carry out meta-analyses including:

  • professors
  • graduate students
  • postdoctoral trainees
  • clinicians


"I took the SR and meta analysis class with you last summer. I just wanted to tell you that that course almost landed me a job. I went through a series of interviews with a great company. Unfortunately the job didnt work out for me personally but I thank you for that course, it served greatly during the job interview"


“I enjoyed the friendly atmosphere of the class and the excellent material. Very useful and the instructors were amazing.”


“I was able to apply everything I learned during the morning to real examples in a group setting during the afternoon. This application of knowledge helped to clarify any questions or misunderstandings I had.”


“I liked the one-on-one interaction with the instructors. They took their time in explaining things and also gave us enough time to do our own project and apply the methods we learnt. Also, the organizers did an amazing job and everything was well organized and the food was great.”


“It was a very comprehensive course and well organized and the instructors were very knowledgeable, friendly and easy to approach even after classes whenever we needed help with our project.”

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