flowchart
is a package for drawing participant flow
diagrams directly from a dataframe using tidyverse. It provides a set of
functions that can be combined with |>
to create all
kinds of flowcharts from a dataframe in an easy way:
as_fc()
transforms a dataframe into a
fc
object that can be manipulated by the package.
fc_split()
splits a flowchart according to the
different values of a column in the dataframe.
fc_filter()
creates a filtered box from the
flowchart, based on the evaluation of an expression in the
dataframe.
fc_merge()
combines horizontally two different
flowcharts.
fc_stack()
combines vertically two different
flowcharts.
fc_modify()
allows to modify the parameters of the
flowchart which are stored in .$fc
.
fc_draw()
draws the flowchart created by the
previous functions.
fc_export()
allows to export the flowchart drawn to
the desired format.
We can install the stable version in CRAN:
Or the development version from GitHub:
We will use the built-in dataset safo
, which is a
randomly generated dataset from the SAFO trial1. SAFO is an
open-label, multicentre, phase III–IV superiority randomised clinical
trial designed to assess whether cloxacillin plus fosfomycin
administered during the first 7 days of therapy achieves better
treatment outcomes than cloxacillin alone in hospitalised patients with
meticillin-sensitive Staphylococcus aureus bacteraemia.
## # A tibble: 6 × 21
## id inclusion_crit exclusion_crit chronic_heart_failure expected_death_24h
## <int> <fct> <fct> <fct> <fct>
## 1 1 Yes No No No
## 2 2 No No No No
## 3 3 No No No No
## 4 4 No Yes No No
## 5 5 No No No No
## 6 6 No Yes No No
## # ℹ 16 more variables: polymicrobial_bacteremia <fct>,
## # conditions_affect_adhrence <fct>, susp_prosthetic_valve_endocard <fct>,
## # severe_liver_cirrhosis <fct>, acute_sars_cov2 <fct>,
## # blactam_fosfomycin_hypersens <fct>, other_clinical_trial <fct>,
## # pregnancy_or_breastfeeding <fct>, previous_participation <fct>,
## # myasthenia_gravis <fct>, decline_part <fct>, group <fct>, itt <fct>,
## # reason_itt <fct>, pp <fct>, reason_pp <fct>
The first step is to initialise the flowchart with
as_fc
. The last step, if we want to visualise the created
flowchart, is to draw the flowchart with fc_draw
. In
between we can combine the functions fc_split
.,
fc_filter
, fc_merge
, fc_stack
with the operator pipe (|>
or %>$
) to
create complex flowchart structures.
To initialize a flowchart from a dataset we have to use the
as_fc()
function:
## List of 2
## $ data: tibble [925 × 21] (S3: tbl_df/tbl/data.frame)
## $ fc : tibble [1 × 17] (S3: tbl_df/tbl/data.frame)
## - attr(*, "class")= chr "fc"
The safo_fc
object created is a fc
object,
which consists of a list containing the tibble of the dataframe
associated with the flowchart and the tibble that stores the flowchart
parameters. In this example, safo_fc$data
corresponds to
the safo
dataset while safo_fc$fc
contains the
parameters of the initial flowchart:
## # A tibble: 1 × 17
## id x y n N perc text type group just text_color text_fs
## <dbl> <dbl> <dbl> <int> <int> <chr> <chr> <chr> <lgl> <chr> <chr> <dbl>
## 1 1 0.5 0.5 925 925 100 "Ini… init NA cent… black 8
## # ℹ 5 more variables: text_fface <dbl>, text_ffamily <lgl>, text_padding <dbl>,
## # bg_fill <chr>, border_color <chr>
Alternatively, if a dataframe is not available, we can initialize a
flowchart using the N =
argument manually specifying the
number of rows:
The function fc_draw()
allows to draw the flowchart
associated to any fc
object. Following the last example, we
can draw the initial flowchart that has been previously created:
We can filter the flowchart using fc_filter()
specifying
the logic in which the filter is to be applied. For example, we can show
the number of patients that were randomized in the study:
safo |>
as_fc(label = "Patients assessed for eligibility") |>
fc_filter(!is.na(group), label = "Randomized", show_exc = TRUE) |>
fc_draw()
Percentages are calculated from the box in the previous level. See
‘Modify function arguments’ for more information on the
label=
and show_exc=
arguments.
Alternatively, if the column to filter is not available, we can use
the N =
argument to manually specify the number of rows of
the resulting filter:
We can split the flowchart into groups using fc_split()
specifying the grouping variable. The function will split the flowchart
into as many categories as the specified variable has. For example, we
can split the previous flowchart showing the patients allocated in the
two study treatments:
safo |>
dplyr::filter(!is.na(group)) |>
as_fc(label = "Randomized patients") |>
fc_split(group) |>
fc_draw()
Percentages are calculated from the box in the previous level.
Alternatively, if the column to split is not available, we can use
the N =
argument to manually specify the number of rows in
each group of the resulting split:
We can customize the flowchart either with the arguments provided by
each function in the process of creating it, or directly in the final
output using the function fc_modify
. We can also change the
box style for all boxes in the flowchart using an argument in
fc_draw
.
There are many different arguments in as_fc()
,
fc_filter()
, fc_split()
, and
fc_draw()
that allow you to customize the boxes created at
each step. Examples of how to use these arguments are given at the end
of the vignette: Customization
examples.
The function fc_modify
allows the user to customise the
created flowchart by modifying its parameters, which are stored in
.$fc
.
For example, let’s customize the following flowchart:
safo_fc <- safo |>
as_fc(label = "Patients assessed for eligibility") |>
fc_filter(!is.na(group), label = "Randomized", show_exc = TRUE)
safo_fc |>
fc_draw()
Previous to modifying it, we can use the function
fc_view()
to inspect the element $fc
that we
want to change:
## # A tibble: 3 × 17
## id x y n N perc text type group just text_color text_fs
## <int> <dbl> <dbl> <int> <int> <chr> <chr> <chr> <lgl> <chr> <chr> <dbl>
## 1 1 0.5 0.667 925 925 100 "Pat… init NA cent… black 8
## 2 2 0.5 0.333 215 925 23.24 "Ran… filt… NA cent… black 8
## 3 3 0.65 0.5 710 925 76.76 "Exc… excl… NA cent… black 6
## # ℹ 5 more variables: text_fface <dbl>, text_ffamily <lgl>, text_padding <dbl>,
## # bg_fill <chr>, border_color <chr>
Let’s customise the text in the exclusion box (id = 3
)
to specify different reasons for exclusion, and change the x
and y coordinate:
safo_fc |>
fc_modify(
~ . |>
mutate(
text = ifelse(id == 3, str_glue("- {sum(safo$inclusion_crit == 'Yes')} not met the inclusion criteria\n- {sum(safo$exclusion_crit == 'Yes')} met the exclusion criteria"), text),
x = case_when(
id == 3 ~ 0.75,
TRUE ~ x
),
y = case_when(
id == 1 ~ 0.8,
id == 2 ~ 0.2,
TRUE ~ y
)
)
) |>
fc_draw()
fc_merge()
and fc_stack()
allow you to
combine different flowcharts horizontally or vertically. This is very
useful when you need to combine flowcharts generated from different
dataframes, as shown here.
We can combine different flowcharts horizontally using
fc_merge()
. For example, we might want to represent the
flow of patients included in the ITT population with the flow of
patients included in the PP population.
# Create first flowchart for ITT
fc1 <- safo |>
as_fc(label = "Patients assessed for eligibility") |>
fc_filter(itt == "Yes", label = "Intention to treat (ITT)")
fc_draw(fc1)
We can combine different flowcharts vertically using
fc_stack()
. For example, we can combine the same two
flowcharts vertically instead of horizontally.
We can use the argument unite = TRUE
to connect two
stacked flowcharts. For example:
Once the flowchart has been drawn we can export it to the most
popular image formats, including both bitmap (png, jpeg, tiff, bmp) and
vector (svg, pdf) formats, using fc_export()
:
safo |>
as_fc(label = "Patients assessed for eligibility") |>
fc_filter(!is.na(group), label = "Randomized", show_exc = TRUE) |>
fc_draw() |>
fc_export("flowchart.png")
We can change the size and resolution of the stored image.
In this example, we will try to create a flowchart for the complete flow of patients in the SAFO study:
In this example, we will try to exactly reproduce the original flowchart of the SAFO study published in Nature Medicine: SAFO flowchart.
First, we need to do some pre-processing to reproduce the text in the larger boxes:
# Create labels for exclusion box:
label_exc <- paste(
c(str_glue("{sum(safo$inclusion_crit == 'Yes' | safo$exclusion_crit == 'Yes' | safo$decline_part == 'Yes', na.rm = T)} excluded:"),
map_chr(c("inclusion_crit", "decline_part", "exclusion_crit"), ~str_glue("{sum(safo[[.x]] == 'Yes', na.rm = TRUE)} {attr(safo[[.x]], 'label')}")),
map_chr(4:15, ~str_glue(" - {sum(safo[[.x]] == 'Yes')} {attr(safo[[.x]], 'label')}"))),
collapse = "\n")
label_exc <- gsub("exclusion criteria", "exclusion criteria:", label_exc)
safo1 <- safo |>
filter(group == "cloxacillin alone", !is.na(reason_pp)) |>
mutate(reason_pp = droplevels(reason_pp))
label_exc1 <- paste(
c(str_glue("{nrow(safo1)} excluded:"),
map_chr(levels(safo1$reason_pp), ~str_glue(" - {sum(safo1$reason_pp == .x)} {.x}"))),
collapse = "\n")
label_exc1 <- str_replace_all(label_exc1, c("resistant" = "resistant\n", "blood" = "blood\n"))
safo2 <- safo |>
filter(group == "cloxacillin plus fosfomycin", !is.na(reason_pp)) |>
mutate(reason_pp = droplevels(reason_pp))
label_exc2 <- paste(
c(str_glue("{nrow(safo2)} excluded:"),
map_chr(levels(safo2$reason_pp), ~str_glue(" - {sum(safo2$reason_pp == .x)} {.x}"))),
collapse = "\n")
label_exc2 <- str_replace_all(label_exc2, c("nosocomial" = "nosocomial\n", "treatment" = "treatment\n"))
Second, let’s create and customise the flowchart using the functions in the package:
safo |>
as_fc(label = "patients assessed for eligibility", text_pattern = "{N} {label}") |>
fc_filter(!is.na(group), label = "randomized", text_pattern = "{n} {label}", show_exc = TRUE,
just_exc = "left", text_pattern_exc = "{label}", label_exc = label_exc, text_fs_exc = 7) |>
fc_split(group, text_pattern = "{n} asssigned\n {label}") |>
fc_filter(itt == "Yes", label = "included in intention-to-treat\n population", show_exc = TRUE,
text_pattern = "{n} {label}",
label_exc = "patient did not receive allocated\n treatment (withdrew consent)",
text_pattern_exc = "{n} {label}", text_fs_exc = 7) |>
fc_filter(pp == "Yes", label = "included in per-protocol\n population", show_exc = TRUE,
just_exc = "left", text_pattern = "{n} {label}", text_fs_exc = 7) |>
fc_modify(
~.x |>
filter(n != 0) |>
mutate(
text = case_when(id == 11 ~ label_exc1, id == 13 ~ label_exc2, TRUE ~ text),
x = case_when(id == 3 ~ x + 0.15, id %in% c(11, 13) ~ x + 0.01, TRUE ~ x),
y = case_when(id %in% c(1, 3) ~ y + 0.05, id >= 2 ~ y - 0.05, TRUE ~ y)
)
) |>
fc_draw()
In this example, we will create a flowchart without any dataframe,
using the N
argument to manually specify the numbers to
display in the boxes:
The use of N=
argument can be combined with the use of a
dataframe. In this example, we will use the N=
argument in
a flowchart that uses a dataframe:
In this examples, we will explore some of the arguments to customize the following flowchart:
safo |>
as_fc(label = "Patients assessed for eligibility") |>
fc_filter(!is.na(group), label = "Randomized", show_exc = TRUE) |>
fc_split(group) |>
fc_draw()
We can add a title to the flowchart using the argument
title=
in the fc_draw()
function:
We can also add a title to a split in the flowchart, using the
argument title
in the fc_split()
function:
We can change the calculation of all percentages in a flowchart. By
default, percentages are calculated with respect to the box in the
previous level. With the argument perc_total=
we can change
it, to calculate it with respect to the initial box with the total
number of rows:
We can add/remove space to the distance between boxes in a split
using the argument offset
:
safo |>
as_fc(label = "Patients assessed for eligibility") |>
fc_filter(!is.na(group), label = "Randomized", show_exc = TRUE, perc_total = TRUE) |>
fc_split(group, offset = 0.1) |>
fc_draw()
safo |>
as_fc(label = "Patients assessed for eligibility") |>
fc_filter(!is.na(group), label = "Randomized", show_exc = TRUE, perc_total = TRUE) |>
fc_split(group, offset = -0.1) |>
fc_draw()
We can also add/remove space to the distance between the excluded box
in a filter using the argument offset_exc
:
We can change the corner style of the flowchart boxes using the
box_corners
argument with fc_draw
:
We can use expressions in the label of each box. Expressions allow you to use bold or italic text without having to change the font of all the box text. For example:
safo |>
as_fc(label = expression(paste("Patients ", italic("assessed"), " for ", bold("eligibility")))) |>
fc_draw()
Expressions even allow the use of formulas. For example:
We can perform an additional split only in one of the groups using
the argument sel_group=
:
safo |>
as_fc(label = "Patients assessed for eligibility") |>
fc_filter(!is.na(group), label = "Randomized", show_exc = TRUE) |>
fc_split(group) |>
fc_split(N = c(50, 60), sel_group = "cloxacillin alone") |>
fc_draw()
Then, we could also perform a filter in the other group:
safo |>
as_fc(label = "Patients assessed for eligibility") |>
fc_filter(!is.na(group), label = "Randomized", show_exc = TRUE) |>
fc_split(group) |>
fc_split(N = c(50, 60), sel_group = "cloxacillin alone") |>
fc_filter(N = 50, sel_group = "cloxacillin plus fosfomycin") |>
fc_draw()
If we want to select a group in a flowchart with more than two groups
we have to supply a vector in sel_group=
with the desired
groups to be selected:
Grillo, S., Pujol, M., Miró, J.M. et al. Cloxacillin plus fosfomycin versus cloxacillin alone for methicillin-susceptible Staphylococcus aureus bacteremia: a randomized trial. Nat Med 29, 2518–2525 (2023). https://doi.org/10.1038/s41591-023-02569-0↩︎