Introduction
Reproducible reports are an important part of good
practices. We often need to report the results from a
table in the text of an R markdown report. Inline
reporting has been made simple with inline_text()
.
The inline_text()
function reports statistics from
{gtsummary} tables inline in an R markdown
report.
Example data set
We’ll be using the trial
data set throughout this example.
- This set contains data from 200 patients who received one of two types of chemotherapy (Drug A or Drug B). The outcomes are tumor response and death.
For brevity in the tutorial, let’s keep a subset of the variables from the trial data set.
Inline results from tbl_summary()
First create a basic summary table using tbl_summary()
(review tbl_summary()
vignette for detailed overview of this function if needed).
tab1 <- tbl_summary(trial2, by = trt)
tab1
Characteristic |
Drug A N = 98^{1} |
Drug B N = 102^{1} |
---|---|---|
Marker Level (ng/mL) | 0.84 (0.23, 1.60) | 0.52 (0.18, 1.21) |
Unknown | 6 | 4 |
T Stage | ||
T1 | 28 (29%) | 25 (25%) |
T2 | 25 (26%) | 29 (28%) |
T3 | 22 (22%) | 21 (21%) |
T4 | 23 (23%) | 27 (26%) |
^{1} Median (Q1, Q3); n (%) |
To report the median (IQR) of the marker levels in each group, use the following commands inline.
The median (IQR) marker level in the Drug A and Drug B groups are
`r inline_text(tab1, variable = marker, column = "Drug A")`
and`r inline_text(tab1, variable = marker, column = "Drug B")`
, respectively.
Here’s how the line will appear in your report.
The median (IQR) marker level in the Drug A and Drug B groups are 0.84 (0.23, 1.60) and 0.52 (0.18, 1.21), respectively.
If you display a statistic from a categorical variable, include the
level
argument.
`r inline_text(tab1, variable = stage, level = "T1", column = "Drug B")`
resolves to “25 (25%)”
Inline results from tbl_regression()
Similar syntax is used to report results from tbl_regression()
and tbl_uvregression()
tables. Refer to the tbl_regression()
vignette if you need detailed guidance on using these functions.
Let’s first create a regression model.
# build logistic regression model
m1 <- glm(response ~ age + stage, trial, family = binomial(link = "logit"))
Now summarize the results with tbl_regression()
;
exponentiate to get the odds ratios.
tbl_m1 <- tbl_regression(m1, exponentiate = TRUE)
tbl_m1
Characteristic | OR^{1} | 95% CI^{1} | p-value |
---|---|---|---|
Age | 1.02 | 1.00, 1.04 | 0.091 |
T Stage | |||
T1 | — | — | |
T2 | 0.58 | 0.24, 1.37 | 0.2 |
T3 | 0.94 | 0.39, 2.28 | 0.9 |
T4 | 0.79 | 0.33, 1.90 | 0.6 |
^{1} OR = Odds Ratio, CI = Confidence Interval |
To report the result for age
, use the following commands
inline.
`r inline_text(tbl_m1, variable = age)`
Here’s how the line will appear in your report.
1.02 (95% CI 1.00, 1.04; p=0.091)
It is reasonable that you’ll need to modify the text. To do this, use
the pattern
argument. The pattern
argument
syntax follows glue::glue()
format with referenced R
objects being inserted between curly brackets. The default is
pattern = "{estimate} ({conf.level*100}% CI {conf.low}, {conf.high}; {p.value})"
.
You have access the to following fields within the pattern
argument.
Parameter | Description |
---|---|
{estimate} |
primary estimate (e.g. model coefficient, odds ratio) |
{conf.low} |
lower limit of confidence interval |
{conf.high} |
upper limit of confidence interval |
{p.value} |
p-value |
{conf.level} |
confidence level of interval |
{N} |
number of observations |
Age was not significantly associated with tumor response
`r inline_text(tbl_m1, variable = age, pattern = "(OR {estimate}; 95% CI {conf.low}, {conf.high}; {p.value})")`
.
Age was not significantly associated with tumor response (OR 1.02; 95% CI 1.00, 1.04; p=0.091).
If you’re printing results from a categorical variable, include the
level
argument,
e.g. inline_text(tbl_m1, variable = stage, level = "T3")
resolves to “0.94 (95% CI 0.39, 2.28; p=0.9)”.
The inline_text
function has arguments for rounding the
p-value (pvalue_fun
) and the coefficients and confidence
interval (estimate_fun
). These default to the same rounding
performed in the table, but can be modified when reporting inline.
For more details about inline code, review to the RStudio documentation page.