Package 'TrialFlowR'

Title: Clinical Trial Flow and Participant Disposition
Description: Summarizes participant flow and disposition in clinical trials, including CONSORT-style randomized controlled trials, parallel-group, crossover, cluster randomized, and multi-arm trials. Provides functions for screening failures, exclusions and reasons, allocation, follow-up, loss to follow-up, withdrawals, intention-to-treat and per-protocol populations, and participant-disposition summaries. The methods are based on established principles for reporting participant flow and disposition in randomized trials; see Schulz et al. (2010) <doi:10.1136/bmj.c332>.
Authors: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <[email protected]>
License: MIT + file LICENSE
Version: 1.0.0
Built: 2026-09-18 16:48:32 UTC
Source: https://github.com/cran/TrialFlowR

Help Index

Add a participant-flow stage

Description

Adds a new participant-flow stage to an existing trial_flow object.

Usage

add_flow_stage(object, stage_name, ids = NULL)

Arguments

object

A trial_flow object.
stage_name

Name of the new stage.
ids

Optional participant IDs. If NULL, all participants are used.

Value

An updated trial_flow object.

Examples

dat <- data.frame(
  id = 1:4,
  stage = c("Screened", "Screened", "Randomized", "Randomized"),
  group = c("A", "B", "A", "B")
)

x <- trial_flow(
  dat,
  id = "id",
  stage = "stage",
  group = "group"
)

x2 <- add_flow_stage(
  x,
  stage_name = "Completed",
  ids = c(3, 4)
)

x2

Count participants by flow stage and group

Description

Counts participants represented at each flow stage, optionally separated by treatment or trial group.

Usage

flow_counts(object, include_group = TRUE)

Arguments

object

A trial_flow object.
include_group

Logical; include group in the result.

Value

A data frame of participant counts.

Examples

dat <- data.frame(
  id = 1:6,
  stage = c(
    "Screened",
    "Screened",
    "Randomized",
    "Randomized",
    "Completed",
    "Completed"
  ),
  group = c("A", "B", "A", "B", "A", "B")
)

x <- trial_flow(
  dat,
  id = "id",
  stage = "stage",
  group = "group"
)

flow_counts(x)

Summarize participant disposition

Description

Summarizes participant disposition by stage, reason, and optionally treatment or trial group.

Usage

participant_disposition(data, stage, reason = NULL, group = NULL)

Arguments

data

A participant-level data frame.
stage

Disposition-stage column.
reason

Optional reason column.
group

Optional treatment or trial-group column.

Value

A data frame of disposition counts.

Examples

dat <- data.frame(
  stage = c(
    "Screened",
    "Excluded",
    "Randomized",
    "Withdrawn"
  ),
  reason = c(
    NA,
    "Ineligible",
    NA,
    "Adverse event"
  ),
  group = c(
    NA,
    NA,
    "Treatment",
    "Treatment"
  )
)

participant_disposition(
  dat,
  stage = "stage",
  reason = "reason",
  group = "group"
)

Summarize participant populations

Description

Summarizes the number of participants in the overall, intention-to-treat, and per-protocol populations.

Usage

population_summary(data, itt, pp)

Arguments

data

A participant-level data frame.
itt

ITT logical vector or column name.
pp

Per-protocol logical vector or column name.

Value

A data frame with population counts.

Examples

dat <- data.frame(
  id = 1:6,
  itt = c(TRUE, TRUE, TRUE, TRUE, TRUE, FALSE),
  pp = c(TRUE, TRUE, TRUE, FALSE, TRUE, FALSE)
)

population_summary(
  dat,
  itt = "itt",
  pp = "pp"
)

Create a clinical trial participant-flow object

Description

Creates an object representing participant flow through the stages of a clinical trial.

Usage

trial_flow(
  data,
  id,
  stage,
  group = NULL,
  design = c("parallel", "crossover", "cluster", "multi-arm", "other"),
  ...
)

Arguments

data

A data frame with one row per participant.
id

Participant identifier column.
stage

Flow-stage column.
group

Optional treatment or trial-group column.
design

Trial design.
...

Additional arguments.

Value

An object of class trial_flow.

Examples

dat <- data.frame(
  id = 1:6,
  stage = c(
    "Screened",
    "Screened",
    "Randomized",
    "Randomized",
    "Completed",
    "Completed"
  ),
  group = c("A", "B", "A", "B", "A", "B")
)

x <- trial_flow(
  dat,
  id = "id",
  stage = "stage",
  group = "group",
  design = "parallel"
)

x