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Plot discontinuation

Source: R/plots.R
plotSurvivalDiscontinuation.Rd

Plot discontinuation

Usage

plotSurvivalDiscontinuation(
  result,
  facet = "cohort_name",
  colour = c("variable_name", strataColumns(result)),
  ribbon = TRUE,
  style = NULL
)

Arguments

result

A summarised_result object.

facet

Columns to facet by. See options with availablePlotColumns(result). Formula is also allowed to specify rows and columns.

colour

Columns to color by. See options with availablePlotColumns(result).

ribbon

Whether to plot a ribbon with the confidence intervals.

style

Visual theme to apply. Character, or NULL. If a character, this may be either the name of a built-in style (see plotStyle()), or a path to a .yml file that defines a custom style. If NULL, the function will use the explicit default style, unless a global style option is set (see visOmopResults::setGlobalPlotOptions()) or a _brand.yml file is present (in that order). Refer to the visOmopResults package vignette on styles to learn more.

Value

Plot probability to continue the drug over over time

Examples

# \donttest{
library(DrugUtilisation)

cdm <- mockDrugUtilisation()

result <- cdm$cohort1 |>
  summariseSurvivalDiscontinuation(followUpDays = 365)
#> ℹ Calculating discontinuation for cohort_1.
#> ℹ Subsetting table to cohort of interest.
#> ℹ Preparing discontinuation (outcome) cohort.
#> ℹ Estimate single event survival for cohort: cohort_1 and outcome:
#>   discontinuation_of_cohort_1.
#> - Getting survival for target cohort 'cohort_1' and outcome cohort
#> 'discontinuation_of_cohort_1'
#> Getting overall estimates
#> `eventgap`, `outcome_washout`, `censor_on_cohort_exit`, `follow_up_days`, and
#> `minimum_survival_days` casted to character.
#> ✔ Discontinuation analysis for cohort_1 completed in 1s.
#> ℹ Calculating discontinuation for cohort_2.
#> ℹ Subsetting table to cohort of interest.
#> ℹ Preparing discontinuation (outcome) cohort.
#> ℹ Estimate single event survival for cohort: cohort_2 and outcome:
#>   discontinuation_of_cohort_2.
#> - Getting survival for target cohort 'cohort_2' and outcome cohort
#> 'discontinuation_of_cohort_2'
#> Getting overall estimates
#> `eventgap`, `outcome_washout`, `censor_on_cohort_exit`, `follow_up_days`, and
#> `minimum_survival_days` casted to character.
#> ✔ Discontinuation analysis for cohort_2 completed in 1s.
#> ℹ Calculating discontinuation for cohort_3.
#> ℹ Subsetting table to cohort of interest.
#> ℹ Preparing discontinuation (outcome) cohort.
#> ℹ Estimate single event survival for cohort: cohort_3 and outcome:
#>   discontinuation_of_cohort_3.
#> - Getting survival for target cohort 'cohort_3' and outcome cohort
#> 'discontinuation_of_cohort_3'
#> Getting overall estimates
#> `eventgap`, `outcome_washout`, `censor_on_cohort_exit`, `follow_up_days`, and
#> `minimum_survival_days` casted to character.
#> ✔ Discontinuation analysis for cohort_3 completed in 1s.

plotSurvivalDiscontinuation(result)
#> Warning: Removed 232 rows containing missing values or values outside the scale range
#> (`geom_ribbon()`).

# }