Systematic Reviews

Systematic reviews and meta-analyses synthesize evidence across multiple studies, requiring a transparent account of the literature search and selection process. The PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement prescribes a flow diagram with a distinctive structure: multiple parallel identification streams converge into a single screening flow, with progressive exclusions at each stage. The MOOSE (Meta-analysis of Observational Studies in Epidemiology) guidelines follow a similar pattern for observational evidence synthesis.

In selecta, systematic review diagrams are built around the following core functions:

Function Purpose
sources() Define parallel identification streams (the entry point, replacing enroll())
combine() Merge streams into a single flow after deduplication

Thus, the systematic review pipeline adheres to the following basic structure:

sources(...) |>
  phase("Identification") |>
  combine(label) |>
  exclude(label, n, reasons) |>
  phase("Screening") |>
  exclude(label, n) |>
  phase("Included") |>
  endpoint(label) |>
  flowchart()

where sources() is the entry point, and combine() merges parallel columns into a single downstream flow. This vignette demonstrates the full range of systematic review diagrams supported by selecta.

n.b.: To ensure correct font rendering and figure sizing, the diagrams below are displayed using a vignette-only helper function (queue_flow()) that applies recommended dimensions from recdims() via the ragg graphics device, with the standard output function applied afterwards (flowchart()). In practice, replace this queue_flow()/flowchart() workflow with a call to flowsave() for equivalent printed results:

flowsave(flow, "consort.pdf")
flowsave(flow, "consort.png", dpi = 300)

Using flowsave() ensures that the figure dimensions are always large enough to accommodate the diagram content, and it is the preferred method for saving flow diagram outputs in selecta.

Preliminaries

library(selecta)

The examples in this vignette use manual mode exclusively, as systematic review diagrams are typically constructed from summary counts reported during the search and screening process rather than from a row-level dataset.

PRISMA — Three-Column Layout

The PRISMA 2020 flow diagram uses up to three columns to organize sources: studies from previous reviews (left), databases and registers (center), and other methods such as citation searching and gray literature (right). Each column receives a header label and one source box listing individual databases or methods with their counts.

Example 1: Full Three-Column PRISMA Diagram

The sources() function accepts named vector arguments, where each argument defines a source group (column) and its named elements list the individual sources:

example1 <- sources(
    previous  = c("Previous review" = 12, "Previous reports" = 15),
    databases = c("PubMed" = 1234, "Embase" = 567, "CENTRAL" = 89),
    other     = c("Citation search" = 55, "Websites" = 34),
    headers   = c(previous  = "Previous studies",
                  databases = "Databases and registers",
                  other     = "Other methods")
) |>
    phase("Identification") |>
    combine("Records after deduplication") |>
    exclude("Duplicates removed", n = 340,
            included_label = "Records screened") |>
    phase("Screening") |>
    exclude("Records excluded", n = 800,
            reasons = c("Irrelevant title/abstract" = 600,
                        "No full text available" = 200),
            included_label = "Reports assessed") |>
    exclude("Reports excluded", n = 190,
            reasons = c("Wrong population" = 80,
                        "Wrong intervention" = 60,
                        "Wrong outcome" = 30,
                        "Insufficient data" = 20)) |>
    phase("Analysis") |>
    endpoint("Studies included in review")
flowchart(example1)

The headers argument maps group names to display labels for the column headers. If omitted, the argument names are title-cased and used directly (e.g., databases becomes “Databases”).

The combine() function inserts an inverted-Y convergence arrow connecting the parallel source columns into a single downstream node. All subsequent pipeline steps operate on the merged record pool.

Example 2: Three-Column Count-First Layout

Like other diagram types, convergence-style diagrams can also be formatted to have counts displayed before the category title.

flowchart(example1, count_first = TRUE)

PRISMA — Two-Column Layout

Many systematic reviews search only databases and one additional source category. A two-column layout omits the “Previous studies” column:

Example 3: Two-Column Sources

example3 <- sources(
    databases = c("PubMed" = 1234, "Embase" = 567, "CENTRAL" = 89),
    other     = c("Citation search" = 55, "Gray literature" = 34),
    headers   = c(databases = "Databases and registers",
                  other     = "Other methods")
) |>
    phase("Identification") |>
    combine("Records after deduplication") |>
    exclude("Duplicates removed", n = 340,
            included_label = "Records screened") |>
    phase("Screen") |>
    exclude("Records excluded", n = 900) |>
    phase("Analysis") |>
    endpoint("Studies included in review")
flowchart(example3)

PRISMA — Single-Column Layout

For simple reviews that search a single set of databases without grouping, sources() accepts individual scalar arguments. These are consolidated into a single source box with no column header:

Example 4: Flat Source List

example4 <- sources(PubMed = 1234, Embase = 567, CENTRAL = 89) |>
    phase("Identification") |>
    combine("Records identified") |>
    exclude("Duplicates removed", n = 340,
            included_label = "Records screened") |>
    phase("Screen") |>
    exclude("Records excluded", n = 800) |>
    phase("Analysis") |>
    endpoint("Studies included")
flowchart(example4)

In this layout, no column headers are rendered and the source box appears as a single centered node above the convergence point.

MOOSE — Observational Meta-Analysis

The MOOSE (Meta-analysis of Observational Studies in Epidemiology) guidelines prescribe a flow diagram structurally similar to PRISMA, tailored for observational evidence synthesis. The same sources() and combine() functions are used; only the labels and exclusion reasons reflect the observational context:

Example 5: MOOSE Flow Diagram

example5 <- sources(
    databases = c("PubMed" = 892, "Embase" = 445, "Scopus" = 312),
    gray      = c("Conference abstracts" = 67, "Dissertations" = 23),
    headers   = c(databases = "Electronic databases",
                  gray      = "Gray literature")
) |>
    phase("Identification") |>
    combine("Records after deduplication") |>
    exclude("Duplicates removed", n = 420,
            included_label = "Records screened") |>
    phase("Screen") |>
    exclude("Records excluded", n = 850,
            reasons = c("Not observational design" = 380,
                        "Irrelevant exposure" = 290,
                        "Pediatric population" = 180),
            included_label = "Full-text articles assessed") |>
    exclude("Full-text articles excluded", n = 195,
            reasons = c("No relevant outcome" = 85,
                        "Insufficient follow-up" = 60,
                        "High risk of bias" = 50)) |>
    phase("Analysis") |>
    endpoint("Studies included in meta-analysis")
flowchart(example5)

Source Group Structure

The sources() function distinguishes between two input patterns based on the structure of its arguments:

Pattern Input Layout Headers
Flat Scalar named arguments Single column, no header None
Grouped Named vector arguments One column per group Auto or custom

Flat sources (e.g., sources(PubMed = 1234, Embase = 567)) treat each argument as an individual database. All sources are consolidated into a single box.

Grouped sources (e.g., sources(databases = c("PubMed" = 1234, "Embase" = 567))) treat each argument as a group. The argument name identifies the group, and its named elements list the individual databases within that group. Each group is rendered as a separate column with an optional header.

Up to three groups are supported, matching the three-column PRISMA 2020 template. The headers argument provides custom display labels; when omitted, group names are title-cased automatically.

Saving to File

The flowsave() function saves the diagram to a file (PDF, PNG, SVG, or TIFF) with auto-computed dimensions:

flowsave(example1, "prisma_3col.pdf")
flowsave(example1, "prisma_3col.png", dpi = 300)

Explicit dimensions override the automatic calculation:

flowsave(example1, "prisma_3col.pdf", width = 10, height = 12)

All visual parameters accepted by flowchart() are also accepted by flowsave():

flowsave(example1, "prisma_poster.pdf",
         cex = 1.1, cex_side = 0.85, cex_phase = 1.1)

Further Reading