Evidence Synthesis Studies

Code:

PDICSS013_20

Acronym:

PDICSS013_20

Keywords
Classification	Keyword
OFICIAL	Health Sciences-Clinical and Health Serv. Research

Instance: 2023/2024 - 2S

Active?	Yes
Responsible unit:	Department of Community Medicine, Information and Health Decision Sciences
Course/CS Responsible:	PhD in Clinical and Health Services Research

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
PDICSS	13	Current Studies Plan	1	-	3	14	81

Teaching language

Suitable for English-speaking students

Objectives

The evidence synthesis studies such as systematic reviews and meta-analysis studies have emerged in order to address the massive and growing accumulation of scientific evidence with diferent study designs and quality levels on specific issues. This studies have a double objective: synthethize evidence and analyse and explain of the heterogeneity found. This curricular unit aims to address methodological issues and essential practices among evidence synthesis studies on that area of health research.

Learning outcomes and competences

At the end of this curricular unit, students should be able to: adequately define clinical research questions in this context; plan and conduct adequate bibliographic searches; define study selection criteria and assess the quality of included studies; extract and process data from included studies; understand and apply statistical methods in the context of a systematic review and meta-analysis; present, write, and critically appraise systematic reviews and meta-analysis.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Not applicable.

Program

Introduction to Scientific Research in Health and Medicine and Evidence Based Medicine.

Evidence synthesis studies – definitions and classification.

Systematic Reviews and Meta-analysis – operational phases.

Application of Review Manager to support the execution of systematic reviews and meta-analysis.

Research question formulation.

Bibliographic searches.

Studies selection.

Data extraction and processing.

Study quality assessment.

Statistical analysis in evidence synthesis studies – Meta-Analysis.

Meta-Analysis using Review Manager and the R platform with Metafor and Meta packages.

Assessing between study heterogeneity.

Publication and other bias in evidence synthesis studies.

Presenting a protocol for a systematic review and meta-analysis.

Writing and publishing a systematic review and meta-analysis.

Mandatory literature

Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors); Cochrane Handbook for Systematic Reviews of Interventions version 6.0 (updated July 2019). Cochrane, 2019. Available from www.training.cochrane.org/handbook, John Wiley & Sons Ltd., 2019. ISBN: 9781119536659
Sutton, A. J., Abrams, K.R., Jones, D. R., Sheldon, T. A. & Song, F.; Methods for Meta-analysis in Medical Research, John Wiley & Sons, Ltd., 2000
Borenstein, M., Hedges, L.V., Higgins, J.P.T., & Rothstein, H.R. ; Introduction to Meta-Analysis. , : John Wiley & Sons., 2009
Welton, N.J., Sutton, A.J., Cooper, N., Abrams, K.R., & Ades, A.E. ; Evidence Synthesis for Decision Making in Healthcare. , Wiley-Blackwell, 2012
Petitti, D.B. ; ). Meta-Analysis, Decision Analysis, and Cost-Effectiveness Analysis: Methods for Quantitative Synthesis in Medicine (2nd Ed). , New York: Oxford University Press, 2000

Teaching methods and learning activities

After the theoretical presentation of each topic students will perform practical assignments, individual and in group, typically using specific software. An e-learning platform will be used to support theoretical and practical classes.
Students are trained to use applied software tools to support the execution of systematic reviews and meta-analysis (Review Manager and R platform using the packages Metafor and Meta).

Formal Evaluation: Theoretical test (70%); Presentation of a work (30%)

Software

Software Review Manager (RevMan) [Computer program]. Version 5.4, The Cochrane Collaboration, 2020. Available at https://training.cochrane.org/online-learning/core-software-cochrane-reviews/revman
R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Apresentação/discussão de um trabalho científico	30,00
Teste	70,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	31,00
Frequência das aulas	20,00
Trabalho de investigação	15,00
Trabalho escrito	15,00
Total:	81,00

Eligibility for exams

Presence in 75% of the classes.
To be approved the student will have to obtain a minimum grade of 9.5 (in a scale 0-20) in the the final grade of the course (70% Final Written Examination + 30% Practical Work).

Calculation formula of final grade

Evaluation: Theoretical test (70%); Presentation of a practical work (30%)

Examinations or Special Assignments

In this course the students will have to complete a set of practical exercices as part of the practical examination.

Special assessment (TE, DA, ...)

Special assessment periods will be allowed for typical cases, including employed students and members of the students' representatives association.