Methodology · search to forest
From search to forest plot
A practical workflow for moving from a focused review question to a first defensible quantitative synthesis.
1. Start with a focused question
Use PICO, PEO, or another suitable framework to define eligibility criteria before searching. Specify the population, intervention or exposure, comparator, outcome, timepoint, study design, and any special limits that should guide screening.
2. Search and import candidate records
Add studies individually, import a reference-manager export, or use the search assistant to draft source-appropriate searches from your protocol. Optional source coverage and citation chasing can broaden recall, while deduplication keeps repeated records from inflating the screening workload.
NOTE · Candidate records are not included studies
3. Screen with explicit rationales
Capture inclusion and exclusion decisions with reasons. Use dual review when the protocol requires independent judgement, and resolve conflicts before finalising the included study set.
4. Retrieve full text and extract endpoint data
Retrieve or upload source documents, including supplements. Then extract the values needed for the pre-specified endpoint: events and totals, means and standard deviations, time-to-event estimates, or other protocol-defined fields. Review low-confidence or conflicting values before pooling.
5. Run the model and sanity checks
Run the planned fixed-effect or random-effects model, then inspect the forest plot, heterogeneity, study weights, effect direction, and sensitivity checks. If the result is unstable, revisit eligibility, effect measures, extraction, and subgroup assumptions before reporting.
6. Pin, explain, and report
Pin the final plot, model summary, certainty assessment, and important review decisions to the Evidence Board before generating a report. A defensible report should explain why this model, measure, included set, and interpretation are appropriate for the protocol.
If you are new to the platform, begin with the quickstart guide. For deeper statistical interpretation, see statistical analysis.