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systematic-review-prisma

Writing & research

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Updated 10-21 16:20

About this skill

Systematic Reviews with PRISMA 2020

A systematic review is judged on transparency and reproducibility: another team should be able to rerun your searches and reach the same included set. Work in the phases below and keep an audit trail (dates, counts, decisions) as you go. Retrofitting a trail at the end is how reviews fail peer review.

Phase 1: Protocol (before searching)

  1. Frame the question with PICO (Population, Intervention, Comparator, Outcome); use PECO for exposures, SPIDER for qualitative work, PCC for scoping reviews.
  2. Pre-specify eligibility criteria, primary/secondary outcomes, databases, date limits, languages, risk-of-bias tool and synthesis method.
  3. Register the protocol before screening starts: PROSPERO (health, human outcomes) or OSF Registries (everything else). Record the registration ID for the manuscript.
  4. Use the PRISMA-P checklist to write the protocol. Scoping reviews follow PRISMA-ScR.

Phase 2: Search

  • Build one concept block per PICO element: controlled vocabulary (MeSH in PubMed, Emtree in Embase) OR free-text synonyms, then AND the blocks.
  • Translate the syntax per database (field tags differ: [tiab] PubMed, :ti,ab Embase, TITLE-ABS-KEY() Scopus, TS= Web of Science). Never paste one string everywhere.
  • Validate sensitivity: the search must retrieve a pre-assembled set of known relevant papers.
  • Search at least two bibliographic databases, plus trial registers, and do forward and backward citation searching of included studies.
  • Record, per database: platform, exact string, date run, and hit count. These go in the supplement verbatim (PRISMA item 7), and PRISMA-S covers search reporting in detail.

Example PubMed block structure:

("Diabetes Mellitus, Type 2"[Mesh] OR "type 2 diabetes"[tiab] OR T2DM[tiab])
AND ("Metformin"[Mesh] OR metformin[tiab])
AND (randomized controlled trial[pt] OR randomi*[tiab] OR placebo[tiab])

Phase 3: Deduplicate and screen

python scripts/dedupe_records.py pubmed.ris embase.ris scopus.csv wos.bib \
  -o screening.csv --summary dedup-counts.json

The output CSV has screen_title_abstract, screen_full_text and exclusion_reason columns for screening in a spreadsheet, or import it into Rayyan, Covidence or ASReview.

  • Two independent reviewers screen titles/abstracts, then full texts. Report agreement (Cohen's kappa) and how conflicts were resolved.
  • Full-text exclusions need one primary reason each, drawn from a fixed list. These become the "Reports excluded" box in the flow diagram.
  • AI-assisted screening (active learning, LLM triage) must be described, validated against human decisions, and never used as the sole reviewer for exclusions.

Phase 4: Extraction and risk of bias

  • Pilot a data-extraction form on 3-5 studies. Extract in duplicate where feasible.
  • Risk-of-bias tool by design: RoB 2 (randomized trials), ROBINS-I (non-randomized interventions), ROBINS-E (exposures), QUADAS-2 (diagnostic accuracy), Newcastle-Ottawa (observational, commonly used), CASP/JBI (qualitative).
  • Rate certainty of evidence per outcome with GRADE and present a Summary of Findings table.

Phase 5: Synthesis

  • Meta-analysis only when studies are sufficiently similar. Use random-effects by default for clinical and methodological heterogeneity. Report I², tau² and prediction intervals.
  • Pre-specified subgroup and sensitivity analyses only. Label post hoc analyses as such.
  • Small-study effects: funnel plot + Egger's test when there are ≥10 studies.
  • Without meta-analysis, follow SWiM (Synthesis Without Meta-analysis) guidance.
  • R metafor/meta or Python statsmodels (see the statistical-analysis skill) for computation.

Phase 6: Report

Generate the flow diagram from your recorded counts; the script refuses inconsistent arithmetic:

python scripts/prisma_flow.py --template > prisma-counts.json   # fill in
python scripts/prisma_flow.py prisma-counts.json > prisma.mmd    # Mermaid for Markdown/Quarto
python scripts/prisma_flow.py prisma-counts.json --format dot -o prisma.dot && dot -Tsvg prisma.dot -o prisma.svg

Complete the 27-item PRISMA 2020 checklist (references/prisma-2020-checklist.md) with the page/section where each item is reported, and submit it with the manuscript. The abstract must follow the PRISMA 2020 for Abstracts checklist (12 items).

Integrity rules

  • Never fabricate search counts, studies or screening decisions. Every number in the flow diagram must come from the recorded logs.
  • Verify each included study's bibliographic record (citation-verification) and report exact search dates.

Common reasons reviews are rejected

  • Protocol not registered, or registered after screening began without explanation.
  • One database only, no grey literature or register search.
  • Search strings not reported in full or not reproducible.
  • Single-reviewer screening with no justification.
  • Flow-diagram numbers that do not add up (the script prevents this).
  • Pooling clinically heterogeneous studies; ignoring risk of bias in the synthesis.
  • Conclusions stronger than the GRADE certainty supports.

Related skills

literature-review (narrative and scoping searches), citation-verification, statistical-analysis, scientific-writing, peer-review.