write-systematic-review

name	write-systematic-review
description	Use when planning or writing a systematic review of scientific literature — following PRISMA guidelines to search, screen, extract, and synthesize evidence from primary studies with transparent, reproducible methodology.
source	Page et al. (2021) "PRISMA 2020 Statement" (BMJ); Cochrane Handbook for Systematic Reviews of Interventions (Higgins et al., 2022); Moher et al. (2009) "Preferred Reporting Items for Systematic Reviews and Meta-Analyses" (PLOS Medicine)
tags	["systematic-review","prisma","evidence-synthesis","literature-review","meta-analysis","research-methodology"]

Write Systematic Review

Conduct and report a systematic review following PRISMA 2020 standards — with pre-registered protocol, comprehensive search, transparent screening, risk-of-bias assessment, and synthesis of evidence quality.

Why This Is Best Practice

Why best: Systematic reviews with pre-registered protocols and dual independent screening produce reproducible, low-bias evidence syntheses that individual studies and narrative reviews cannot match. Adopted by: Cochrane Collaboration (the gold standard for systematic reviews), WHO, NIH systematic evidence review programs, NICE (UK clinical guidelines), FDA Evidence-Based Medicine framework, and virtually all clinical guideline bodies require systematic reviews as the primary evidence base for recommendations. Impact: Ioannidis (2005) "Why Most Published Research Findings Are False" demonstrated that individual studies frequently yield false positives — systematic reviews, by pooling and assessing evidence quality, are the most reliable way to estimate true effect sizes. The PRISMA statement is endorsed by >700 journals (EQUATOR network); systematic reviews using PRISMA have significantly higher citation rates and lower retraction rates than narrative reviews.

Steps

1. Register the protocol before searching

Pre-registration is mandatory for credible systematic reviews:

• Register on PROSPERO (www.crd.york.ac.uk/prospero) — the international register for systematic reviews
• Record: research question, PICO elements, search strategy, inclusion/exclusion criteria, outcomes, planned synthesis method
• Registration prevents selective reporting and outcome-switching — the primary bias in non-registered reviews

2. Formulate the research question using PICO

Structure the question:

• P (Population): who are the participants? What condition/context?
• I (Intervention/Exposure): what is being done or examined?
• C (Comparator): what is it compared to?
• O (Outcome): what outcomes matter? Primary and secondary?

Example: In adults with Type 2 diabetes (P), does GLP-1 agonist therapy (I) compared to SGLT-2 inhibitors (C) reduce cardiovascular mortality (O)?

3. Design the comprehensive search strategy

Search must be comprehensive and reproducible:

• Databases: search at minimum MEDLINE (PubMed), EMBASE, CENTRAL (Cochrane); add discipline-specific databases (PsycINFO, CINAHL, etc.)
• Search terms: combine MeSH terms with free-text synonyms using Boolean operators (AND, OR, NOT); work with a research librarian for complex searches
• Time span: search all years unless specific rationale for cutoff
• Additional sources: grey literature (clinical trial registries, conference abstracts, regulatory submissions); reference lists of included studies; forward citation of key papers

Document the exact search string for each database (required for PRISMA flow diagram).

4. Screen titles/abstracts then full texts

Two-phase screening:

1. Title/abstract screening: apply inclusion/exclusion criteria; two independent reviewers screen all records; resolve disagreements by discussion or third reviewer
2. Full-text screening: retrieve and assess all articles that passed abstract screening; document reason for exclusion

Use systematic review software (Covidence, Rayyan, DistillerSR) to manage screening and track decisions.

Calculate inter-rater reliability (Cohen's kappa ≥ 0.7 = acceptable agreement).

5. Extract data systematically

Create a data extraction form before extraction begins:

• Study characteristics: authors, year, country, study design, sample size, follow-up duration
• Participant characteristics: demographics, inclusion/exclusion criteria
• Intervention details: dose, duration, comparator
• Outcomes: measures, results, units, time points
• Risk of bias elements (see step 6)

Extract with two independent reviewers for key outcome data; verify against source.

6. Assess risk of bias

Every included study must be assessed for methodological quality:

• RCTs: use Cochrane Risk of Bias 2 (RoB 2) tool: randomization, allocation concealment, blinding, selective outcome reporting
• Observational studies: use ROBINS-I tool
• Diagnostic accuracy: use QUADAS-2

Summarize at the study level and domain level. High-risk-of-bias studies downgrade the certainty of evidence.

7. Synthesize evidence and assess certainty (GRADE)

Narrative synthesis: when pooling is not appropriate (heterogeneous methods/populations); describe patterns, consistencies, and gaps

Meta-analysis: when ≥2 studies report the same outcome with compatible methods; use random-effects model (DerSimonian-Laird) as default for clinical heterogeneity; report I² for heterogeneity assessment

GRADE assessment: rate evidence certainty for each outcome:

• High: consistent, direct, precise evidence from RCTs
• Moderate: one downgrade (risk of bias, inconsistency, imprecision, indirectness, publication bias)
• Low/Very low: multiple downgrades

Common Mistakes

• No pre-registration: Allows post-hoc outcome selection — primary driver of systematic review bias.
• Single-reviewer screening: Increases miss rate for relevant studies; requires dual independent screening.
• Narrative review disguised as systematic: Using the word "systematic" without a registered protocol, comprehensive search, and risk-of-bias assessment is misleading — and journals increasingly desk-reject these.

When NOT to Use

• Research question with <5 existing primary studies: scoping review or narrative review is more appropriate; meta-analysis with too few studies yields unreliable pooled estimates.