Assessing drug restart and switching after treatment • DrugUtilisation

Introduction

Obtaining information on drug restart or switching to another drug after discontinuation of the original treatment is often of interest in drug utilisation studies. In this vignette, we show how to assess drug switching and restart with this package.

Data

Connect to mock data

For this vignette we will use mock data contained in the DrugUtilisation package.

library(DrugUtilisation)

cdm <- mockDrugUtilisation(numberIndividual = 200)

Generate study cohorts

We will examine the patterns of drug restart and switching among patients taking metformin as an example. Specifically, we will investigate whether patients restart metformin after discontinuation, switch to insulin, try both medications, or remain untreated.

For this we will need two cohorts: one of patients exposed to metformin and another of patients exposed to insulin.

# codelists
metformin <- CodelistGenerator::getDrugIngredientCodes(cdm = cdm, name = "metformin")
insulin <- CodelistGenerator::getDrugIngredientCodes(cdm = cdm, name = "insulin detemir")

cdm <- generateDrugUtilisationCohortSet(
  cdm = cdm, name = "metformin", conceptSet = metformin
)
cdm$metformin |>
  cohortCount()
#> # A tibble: 1 × 3
#>   cohort_definition_id number_records number_subjects
#>                  <int>          <int>           <int>
#> 1                    1            107              92

cdm <- generateDrugUtilisationCohortSet(
  cdm = cdm, name = "insulin", conceptSet = insulin
)
cdm$insulin |>
  cohortCount()
#> # A tibble: 1 × 3
#>   cohort_definition_id number_records number_subjects
#>                  <int>          <int>           <int>
#> 1                    1             93              85

Assess drug restart

The summariseDrugRestart() function analyses the outcomes within a treatment cohort following the first exposure to a specific drug. It categorises the events into four distinct groups:

Restarting the same treatment.
Switching to a different treatment.
Restarting the same treatment while also switching to another.
Discontinuing treatment altogether (neither the original treatment nor any potential switch).

The figure below illustrates the analysis, focusing on the outcomes after the initial exposure to a particular drug (in blue), with consideration of a specific switch drug (in orange). This study examines what occurs within 100, 180, and 365 days following first treatment discontinuation in the cohort.

Now, let’s use the function to assess metformin restart and switch to insulin after the first metformin treatment.

results <- cdm$metformin |>
  summariseDrugRestart(
    switchCohortTable = "insulin",
    switchCohortId = NULL,
    strata = list(),
    followUpDays = Inf,
    censorDate = NULL,
    restrictToFirstDiscontinuation = TRUE
  )

results |>
  dplyr::glimpse()
#> Rows: 8
#> Columns: 13
#> $ result_id        <int> 1, 1, 1, 1, 1, 1, 1, 1
#> $ cdm_name         <chr> "DUS MOCK", "DUS MOCK", "DUS MOCK", "DUS MOCK", "DUS …
#> $ group_name       <chr> "cohort_name", "cohort_name", "cohort_name", "cohort_…
#> $ group_level      <chr> "6809_metformin", "6809_metformin", "6809_metformin",…
#> $ strata_name      <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ strata_level     <chr> "overall", "overall", "overall", "overall", "overall"…
#> $ variable_name    <chr> "Drug restart till end of observation", "Drug restart…
#> $ variable_level   <chr> "restart", "restart", "switch", "switch", "restart an…
#> $ estimate_name    <chr> "count", "percentage", "count", "percentage", "count"…
#> $ estimate_type    <chr> "integer", "percentage", "integer", "percentage", "in…
#> $ estimate_value   <chr> "13", "14.1304347826087", "3", "3.26086956521739", "2…
#> $ additional_name  <chr> "follow_up_days", "follow_up_days", "follow_up_days",…
#> $ additional_level <chr> "inf days", "inf days", "inf days", "inf days", "inf …

We could be interested in getting these results in different follow-up periods since the first metformin exposure ended. For instance, next we get the results in the first 180 days, the first year, and until the end of observation.

results <- cdm$metformin |>
  summariseDrugRestart(
    switchCohortTable = "insulin",
    switchCohortId = NULL,
    strata = list(),
    followUpDays = c(180, 365, Inf),
    censorDate = NULL,
    restrictToFirstDiscontinuation = TRUE
  )

Other options that this function allows are:

restrictToFirstDiscontinuation

By default this argument is set to TRUE, which means that we only consider the firsts exposure of the subject. If FALSE, the analysis is conducted on a record level, considering all exposures in the cohort, as the following image illustrates:

censorEndDate

This argument allows to stop considering restart and switch events after a certain date, which must specified as a column in the cohort.

incident

This argument is by default TRUE, which means we will only consider switch treatments starting after discontinuation. If set to FALSE, we will allow switch treatments starting before the discontinuation of the treatment and ending afterwards.

followUpDays

The follow-up of the individuals will be set to Inf by default, i.e. we will follow them up for as long as possible. However, we can restrict the follow-up period to any other time interval as seen in the previous example.

strata

This argument must be a list pointing to columns or combinations of columns in the cohort to use as strata. It will produce stratified estimates as well as for the overall cohort.

For instance, we reproduce the last calculation but this time straifying by sex. We first use PatientProfiles to add a column indicating the sex, which later we use in strata.

results <- cdm$cohort1 |>
  PatientProfiles::addSex(name = "cohort1") |>
  summariseDrugRestart(
    switchCohortTable = "insulin",
    switchCohortId = NULL,
    strata = list("sex"),
    followUpDays = c(180, 365, Inf),
    censorDate = NULL,
    restrictToFirstDiscontinuation = TRUE
  )

Visualise drug restart

The package has table and plot functions to help visualising the results from summariseDrugRestart().

Table

The function tableDrugRestart() will create a gt, flextable or tibble table from the summarised_result object created with summariseDrugRestart(). This function offers multiple customisation options to format the resulting table according to the user preferences.

results |>
  tableDrugRestart()

			CDM name
			DUS MOCK
Sex	Treatment	Estimate name	Cohort name
Sex	Treatment	Estimate name	cohort_1	cohort_2	cohort_3
Drug restart in 180 days
overall	restart	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	switch	N (%)	3 (4.55 %)	3 (5.88 %)	4 (4.82 %)
	restart and switch	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	untreated	N (%)	63 (95.45 %)	48 (94.12 %)	79 (95.18 %)
Female	restart	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	switch	N (%)	2 (6.90 %)	2 (7.41 %)	3 (7.69 %)
	restart and switch	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	untreated	N (%)	27 (93.10 %)	25 (92.59 %)	36 (92.31 %)
Male	restart	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	switch	N (%)	1 (2.70 %)	1 (4.17 %)	1 (2.27 %)
	restart and switch	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	untreated	N (%)	36 (97.30 %)	23 (95.83 %)	43 (97.73 %)
Drug restart in 365 days
overall	restart	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	switch	N (%)	3 (4.55 %)	5 (9.80 %)	5 (6.02 %)
	restart and switch	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	untreated	N (%)	63 (95.45 %)	46 (90.20 %)	78 (93.98 %)
Female	restart	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	switch	N (%)	2 (6.90 %)	3 (11.11 %)	4 (10.26 %)
	restart and switch	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	untreated	N (%)	27 (93.10 %)	24 (88.89 %)	35 (89.74 %)
Male	restart	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	switch	N (%)	1 (2.70 %)	2 (8.33 %)	1 (2.27 %)
	restart and switch	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	untreated	N (%)	36 (97.30 %)	22 (91.67 %)	43 (97.73 %)
Drug restart till end of observation
overall	restart	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	switch	N (%)	5 (7.58 %)	8 (15.69 %)	8 (9.64 %)
	restart and switch	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	untreated	N (%)	61 (92.42 %)	43 (84.31 %)	75 (90.36 %)
Female	restart	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	switch	N (%)	4 (13.79 %)	5 (18.52 %)	6 (15.38 %)
	restart and switch	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	untreated	N (%)	25 (86.21 %)	22 (81.48 %)	33 (84.62 %)
Male	restart	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	switch	N (%)	1 (2.70 %)	3 (12.50 %)	2 (4.55 %)
	restart and switch	N (%)	0 (0.00 %)	0 (0.00 %)	0 (0.00 %)
	untreated	N (%)	36 (97.30 %)	21 (87.50 %)	42 (95.45 %)

Plot

The plotDrugRestart() function creates a bar plot depicting the percentage of drug restart events for each cohort, stratum, and follow-up time (specified in the variable_name column of the summarised result). This function offers customisation options for colours, facetting, and handling of strata.

results |>
  plotDrugRestart(facet = cohort_name + sex ~ follow_up_days)

Adding the information to an existing cohort

We can directly add the drug restart information to an existing cohort as a column instead of asking for a summarising object. In this case we will use the function addDrugRestart(), which will add one column per follow-up window we ask for:

cdm$metformin |>
  addDrugRestart(
    switchCohortTable = "insulin",
    switchCohortId = NULL,
    followUpDays = c(180, 365, Inf),
    censorDate = NULL
  ) |>
  gt::gt()

cohort_definition_id	subject_id	cohort_start_date	cohort_end_date	drug_restart_180	drug_restart_365	drug_restart_inf
1	7	2010-01-08	2011-05-13	untreated	untreated	untreated
1	11	2007-04-03	2007-05-07	untreated	untreated	untreated
1	12	1991-08-30	1994-01-03	untreated	untreated	untreated
1	19	2011-12-01	2014-01-15	untreated	untreated	untreated
1	35	2014-12-01	2016-04-11	untreated	untreated	untreated
1	36	1999-08-07	2004-01-08	untreated	untreated	untreated
1	45	2020-11-27	2020-12-18	untreated	untreated	untreated
1	47	2016-02-29	2016-09-10	untreated	untreated	untreated
1	54	1990-06-01	1990-06-26	untreated	untreated	untreated
1	59	2021-10-24	2022-03-31	untreated	untreated	untreated
1	65	2004-09-04	2015-07-24	untreated	untreated	untreated
1	67	2009-09-27	2012-08-13	untreated	untreated	untreated
1	68	2003-04-21	2007-10-04	untreated	untreated	untreated
1	69	2021-01-06	2021-01-19	untreated	untreated	untreated
1	74	2008-03-21	2017-06-02	untreated	untreated	untreated
1	76	2013-05-10	2019-10-08	untreated	untreated	untreated
1	80	2018-08-03	2018-09-08	untreated	untreated	untreated
1	86	2008-04-13	2013-09-23	untreated	untreated	untreated
1	92	2022-09-29	2022-10-11	untreated	untreated	untreated
1	95	2000-12-05	2001-09-12	untreated	untreated	untreated
1	98	2016-05-09	2017-03-17	untreated	untreated	untreated
1	107	2021-07-04	2021-07-08	untreated	untreated	untreated
1	110	1980-11-27	1984-11-11	untreated	untreated	untreated
1	114	2021-03-19	2021-06-24	untreated	untreated	untreated
1	118	2010-04-22	2013-07-06	untreated	untreated	untreated
1	121	2020-05-04	2021-09-09	untreated	untreated	untreated
1	128	2021-09-30	2021-10-07	untreated	untreated	untreated
1	129	2020-11-08	2020-11-22	untreated	untreated	untreated
1	143	2020-11-20	2020-11-21	untreated	untreated	untreated
1	144	2011-12-07	2013-03-06	untreated	untreated	untreated
1	155	1999-08-04	2001-12-26	untreated	untreated	untreated
1	166	2004-01-31	2014-03-25	untreated	untreated	untreated
1	171	2000-01-18	2002-04-03	untreated	untreated	untreated
1	172	2003-07-30	2005-08-24	untreated	untreated	untreated
1	174	2019-05-21	2019-06-13	untreated	untreated	untreated
1	179	2017-08-07	2017-08-11	untreated	untreated	untreated
1	185	1993-07-02	1999-05-12	untreated	untreated	untreated
1	191	2020-05-17	2020-05-19	untreated	untreated	untreated
1	194	2022-02-16	2022-03-10	untreated	untreated	untreated
1	22	1958-05-12	1975-05-23	untreated	untreated	untreated
1	152	2021-10-24	2021-12-02	untreated	untreated	untreated
1	116	2019-01-28	2019-03-06	untreated	untreated	untreated
1	103	2014-10-08	2020-01-23	untreated	untreated	untreated
1	16	2019-03-19	2019-10-19	untreated	untreated	untreated
1	48	2021-07-21	2021-12-05	untreated	untreated	untreated
1	151	2005-05-06	2007-12-30	untreated	untreated	untreated
1	4	2010-07-25	2011-12-11	untreated	untreated	untreated
1	21	2015-10-09	2018-01-10	untreated	untreated	untreated
1	25	2006-05-08	2009-02-17	untreated	untreated	untreated
1	31	2019-07-28	2019-12-28	untreated	untreated	untreated
1	34	2018-09-26	2018-10-02	untreated	untreated	untreated
1	38	2000-03-27	2003-07-03	untreated	untreated	untreated
1	40	2022-07-02	2022-07-09	untreated	untreated	untreated
1	43	1972-03-04	1990-03-14	untreated	untreated	untreated
1	51	2014-09-11	2017-09-02	untreated	untreated	untreated
1	56	2017-05-04	2018-03-04	untreated	untreated	untreated
1	57	2010-12-03	2013-03-16	untreated	untreated	untreated
1	66	2006-09-07	2006-09-25	untreated	untreated	untreated
1	70	2018-01-01	2018-08-23	untreated	untreated	untreated
1	71	2010-10-25	2011-12-13	untreated	untreated	untreated
1	73	2019-09-04	2019-10-15	untreated	untreated	untreated
1	82	2004-02-25	2008-06-14	untreated	untreated	untreated
1	99	2021-05-16	2021-06-22	untreated	untreated	untreated
1	102	2009-03-20	2009-09-23	untreated	untreated	untreated
1	108	2001-09-04	2007-10-06	untreated	untreated	untreated
1	111	2021-03-01	2022-06-28	untreated	untreated	untreated
1	124	2021-07-09	2022-08-07	untreated	untreated	untreated
1	125	2013-01-13	2013-07-15	untreated	untreated	untreated
1	127	2019-09-07	2019-09-15	untreated	untreated	untreated
1	130	2019-01-01	2019-07-20	untreated	untreated	untreated
1	132	2007-05-18	2008-04-24	untreated	untreated	untreated
1	134	2016-04-21	2017-01-31	untreated	untreated	untreated
1	137	2020-06-16	2020-07-01	untreated	untreated	untreated
1	140	1997-04-09	1999-02-14	untreated	untreated	untreated
1	158	2015-01-16	2018-11-30	untreated	untreated	untreated
1	169	2016-03-29	2020-10-15	untreated	untreated	untreated
1	175	2022-09-13	2022-09-27	untreated	untreated	untreated
1	181	1987-06-02	1997-12-15	untreated	untreated	untreated
1	187	1994-10-31	1996-09-28	untreated	untreated	untreated
1	192	1981-09-01	1985-05-07	untreated	untreated	untreated
1	199	2020-04-16	2020-04-25	untreated	untreated	untreated
1	196	2000-11-04	2004-05-07	untreated	untreated	untreated
1	177	2022-02-05	2022-03-17	untreated	untreated	untreated
1	20	2018-01-25	2018-03-07	untreated	untreated	untreated
1	78	2016-08-20	2016-11-02	untreated	untreated	untreated
1	123	1982-07-20	1982-08-03	untreated	untreated	untreated
1	116	2016-12-01	2017-06-29	untreated	untreated	restart
1	103	2010-11-18	2014-07-23	restart	restart	restart
1	19	2009-03-10	2011-04-27	untreated	restart	restart
1	69	2020-04-28	2020-10-03	restart	restart	restart
1	98	2014-07-10	2016-02-06	restart	restart	restart
1	4	2009-05-01	2009-11-27	untreated	restart	restart
1	54	1987-06-05	1990-04-03	restart	restart	restart
1	99	2020-03-12	2020-04-10	untreated	untreated	restart
1	121	2019-05-17	2019-11-13	restart	restart	restart
1	128	2021-08-20	2021-08-20	restart	restart	restart
1	129	2020-01-10	2020-08-31	restart	restart	restart
1	59	2019-09-08	2020-06-19	untreated	untreated	restart
1	29	2022-12-12	2022-12-15	switch	switch	switch
1	136	2014-09-03	2015-10-01	untreated	switch	switch
1	15	2012-11-05	2019-04-21	switch	switch	switch
1	177	2012-12-18	2014-07-01	untreated	untreated	restart and switch
1	136	2012-12-09	2013-11-15	untreated	restart	restart and switch
1	183	1999-12-27	2003-01-03	untreated	untreated	untreated
1	191	2019-11-02	2020-04-17	restart	restart	restart
1	186	2004-12-30	2006-09-08	untreated	untreated	switch
1	3	2001-07-12	2002-03-10	untreated	untreated	untreated