Developing a Robust Protocol for Your Systematic Review

Published: 📅January 10, 2025 ⌚3 min read

Learning Objectives

  1. Understand the crucial role of a protocol in conducting a rigorous and transparent systematic review.
  2. Identify the essential components of a well-structured protocol.
  3. Develop a comprehensive protocol for your own systematic review, ensuring its reproducibility and minimizing bias.

Introduction

A protocol is a predefined written plan that outlines the objectives, methods, and analysis plan of your systematic review. It serves as a roadmap, guiding your research process and ensuring consistency and transparency. Developing a thorough protocol before commencing your review is crucial for minimizing bias, enhancing reproducibility, and facilitating efficient project management. A registered protocol demonstrates a commitment to conducting a rigorous and unbiased review.

A comprehensive protocol should include the following key elements:

1. Rationale and Background

  • Problem Statement: Clearly define the research problem or clinical uncertainty that your review aims to address. Justify the need for a new systematic review on this topic. Have other reviews been conducted? If so, what gap in the literature will your review address?
  • Stakeholder Engagement: Briefly describe any involvement of patients, clinicians, or policymakers in shaping the research question or review scope.

2. Research Questions and Objectives

  • PICO Question: Frame your primary research question using the PICO framework (Population, Intervention, Comparison, Outcome). This ensures a focused and answerable question. Example: In adults with type 2 diabetes (P), does metformin compared to sulfonylureas (I vs. C), reduce HbA1c levels (O)?
  • Secondary Objectives: Outline any secondary research questions or outcomes of interest.

3. Search Strategy

  • Information Sources: Specify the electronic databases you will search (e.g., PubMed, Embase, Cochrane Library). Include grey literature sources (e.g., conference abstracts, clinical trial registries) if relevant.
  • Search Terms: Detail the keywords, MeSH terms, and other search strategies you will employ. Provide a reproducible search string for at least one database.
  • Search Period: Define the timeframe for your literature search (e.g., inception to present, specific date range).
  • Language Restrictions: State whether you will limit your search to specific languages and justify your decision.

4. Eligibility Criteria

  • Inclusion Criteria: Define the specific characteristics of studies that will be included in your review (e.g., study design, population characteristics, intervention, outcome measures).
  • Exclusion Criteria: Clearly state the reasons for excluding studies (e.g., language, publication status, poor methodological quality).

5. Study Selection and Data Extraction

  • Study Selection Process: Describe the process for screening titles/abstracts and full-text articles. Specify the number of reviewers involved and how disagreements will be resolved. Will you use a blinding process?
  • Data Extraction Methods: Develop a standardized data extraction form to collect relevant information from included studies (e.g., study characteristics, participant demographics, outcome data). Specify the number of reviewers involved in data extraction and how discrepancies will be handled. What software will you use to manage data extraction?

6. Risk of Bias Assessment

  • Assessment Tools: Identify the appropriate tools you will use to assess the risk of bias in included studies (e.g., Cochrane Risk of Bias tool, ROBINS-I). Justify your tool selection.
  • Bias Assessment Process: Detail how the risk of bias assessment will be conducted (e.g., number of reviewers, blinding, conflict resolution).

7. Data Synthesis and Analysis

  • Data Analysis Methods: Specify the planned statistical methods for analyzing the extracted data (e.g., meta-analysis, narrative synthesis). If conducting a meta-analysis, state the effect measure you will use (e.g., odds ratio, risk difference).
  • Heterogeneity Assessment: Outline your plan for assessing and addressing heterogeneity among included studies (e.g., I² statistic, subgroup analysis, meta-regression).
  • Software: Indicate the software you will use for data analysis (e.g., RevMan, Stata).

Conclusion

Developing a robust protocol is an essential foundation for a high-quality systematic review. By clearly outlining your research plan, you ensure transparency, minimize bias, and enhance the reproducibility of your findings. Using available resources and tools, like those provided by EviSynth, can streamline the protocol development process and facilitate efficient project management.