Package 'IncidencePrevalence'

Run benchmark of incidence and prevalence analyses

Description

Run benchmark of incidence and prevalence analyses

Usage

benchmarkIncidencePrevalence(cdm, analysisType = "all")

Arguments

cdm	A CDM reference object
analysisType	A string of the following: "all", "only incidence", "only prevalence"

Value

a tibble with time taken for different analyses

Examples

cdm <- mockIncidencePrevalence(
  sampleSize = 100,
  earliestObservationStartDate = as.Date("2010-01-01"),
  latestObservationStartDate = as.Date("2010-01-01"),
  minDaysToObservationEnd = 364,
  maxDaysToObservationEnd = 364,
  outPre = 0.1
)

timings <- benchmarkIncidencePrevalence(cdm)

---

Collect population incidence estimates

Description

Collect population incidence estimates

Usage

estimateIncidence(
  cdm,
  denominatorTable,
  outcomeTable,
  denominatorCohortId = NULL,
  outcomeCohortId = NULL,
  interval = "years",
  completeDatabaseIntervals = TRUE,
  outcomeWashout = Inf,
  repeatedEvents = FALSE,
  strata = list(),
  includeOverallStrata = TRUE
)

Arguments

cdm	A CDM reference object
denominatorTable	A cohort table with a set of denominator cohorts (for example, created using the generateDenominatorCohortSet() function).
outcomeTable	A cohort table in the cdm reference containing a set of outcome cohorts.
denominatorCohortId	The cohort definition ids or the cohort names of the denominator cohorts of interest. If NULL all cohorts will be considered in the analysis.
outcomeCohortId	The cohort definition ids or the cohort names of the outcome cohorts of interest. If NULL all cohorts will be considered in the analysis.
interval	Time intervals over which incidence is estimated. Can be "weeks", "months", "quarters", "years", or "overall". ISO weeks will be used for weeks. Calendar months, quarters, or years can be used, or an overall estimate for the entire time period observed (from earliest cohort start to last cohort end) can also be estimated. If more than one option is chosen then results will be estimated for each chosen interval.
completeDatabaseIntervals	TRUE/ FALSE. Where TRUE, incidence will only be estimated for those intervals where the denominator cohort captures all the interval.
outcomeWashout	The number of days used for a 'washout' period between the end of one outcome and an individual starting to contribute time at risk. If Inf, no time can be contributed after an event has occurred.
repeatedEvents	TRUE/ FALSE. If TRUE, an individual will be able to contribute multiple events during the study period (time while they are present in an outcome cohort and any subsequent washout will be excluded). If FALSE, an individual will only contribute time up to their first event.
strata	Variables added to the denominator cohort table for which to stratify estimates.
includeOverallStrata	Whether to include an overall result as well as strata specific results (when strata has been specified).

Value

Incidence estimates

Examples

cdm <- mockIncidencePrevalence(sampleSize = 1000)
cdm <- generateDenominatorCohortSet(
  cdm = cdm, name = "denominator",
  cohortDateRange = c(as.Date("2008-01-01"), as.Date("2018-01-01"))
)
inc <- estimateIncidence(
  cdm = cdm,
  denominatorTable = "denominator",
  outcomeTable = "outcome"
)

---

Estimate period prevalence

Description

Estimate period prevalence

Usage

estimatePeriodPrevalence(
  cdm,
  denominatorTable,
  outcomeTable,
  denominatorCohortId = NULL,
  outcomeCohortId = NULL,
  interval = "years",
  completeDatabaseIntervals = TRUE,
  fullContribution = FALSE,
  strata = list(),
  includeOverallStrata = TRUE
)

Arguments

cdm	A CDM reference object
denominatorTable	A cohort table with a set of denominator cohorts (for example, created using the generateDenominatorCohortSet() function).
outcomeTable	A cohort table in the cdm reference containing a set of outcome cohorts.
denominatorCohortId	The cohort definition ids or the cohort names of the denominator cohorts of interest. If NULL all cohorts will be considered in the analysis.
outcomeCohortId	The cohort definition ids or the cohort names of the outcome cohorts of interest. If NULL all cohorts will be considered in the analysis.
interval	Time intervals over which period prevalence is estimated. This can be "weeks", "months", "quarters", "years", or "overall". ISO weeks will be used for weeks. Calendar months, quarters, or years can be used as the period. If more than one option is chosen then results will be estimated for each chosen interval.
completeDatabaseIntervals	TRUE/ FALSE. Where TRUE, prevalence will only be estimated for those intervals where the database captures all the interval (based on the earliest and latest observation period start dates, respectively).
fullContribution	TRUE/ FALSE. Where TRUE, individuals will only be included if they in the database for the entire interval of interest. If FALSE they are only required to present for one day of the interval in order to contribute.
strata	Variables added to the denominator cohort table for which to stratify estimates.
includeOverallStrata	Whether to include an overall result as well as strata specific results (when strata has been specified).

Value

Period prevalence estimates

Examples

cdm <- mockIncidencePrevalence(sampleSize = 1000)
cdm <- generateDenominatorCohortSet(
  cdm = cdm, name = "denominator",
  cohortDateRange = c(as.Date("2008-01-01"), as.Date("2018-01-01"))
)
estimatePeriodPrevalence(
  cdm = cdm,
  denominatorTable = "denominator",
  outcomeTable = "outcome",
  interval = "months"
)

---

Estimate point prevalence

Description

Estimate point prevalence

Usage

estimatePointPrevalence(
  cdm,
  denominatorTable,
  outcomeTable,
  denominatorCohortId = NULL,
  outcomeCohortId = NULL,
  interval = "years",
  timePoint = "start",
  strata = list(),
  includeOverallStrata = TRUE
)

Arguments

cdm	A CDM reference object
denominatorTable	A cohort table with a set of denominator cohorts (for example, created using the generateDenominatorCohortSet() function).
outcomeTable	A cohort table in the cdm reference containing a set of outcome cohorts.
denominatorCohortId	The cohort definition ids or the cohort names of the denominator cohorts of interest. If NULL all cohorts will be considered in the analysis.
outcomeCohortId	The cohort definition ids or the cohort names of the outcome cohorts of interest. If NULL all cohorts will be considered in the analysis.
interval	Time intervals over which period prevalence is estimated. Can be "weeks", "months", "quarters", or "years". ISO weeks will be used for weeks. Calendar months, quarters, or years can be used as the period. If more than one option is chosen then results will be estimated for each chosen interval.
timePoint	where to compute the point prevalence
strata	Variables added to the denominator cohort table for which to stratify estimates.
includeOverallStrata	Whether to include an overall result as well as strata specific results (when strata has been specified).

Value

Point prevalence estimates

Examples

cdm <- mockIncidencePrevalence(sampleSize = 1000)
cdm <- generateDenominatorCohortSet(
  cdm = cdm, name = "denominator",
  cohortDateRange = c(as.Date("2008-01-01"), as.Date("2018-01-01"))
)
estimatePointPrevalence(
  cdm = cdm,
  denominatorTable = "denominator",
  outcomeTable = "outcome",
  interval = "months"
)

---

Identify a set of denominator populations

Description

generateDenominatorCohortSet() creates a set of cohorts that can be used for the denominator population in analyses of incidence, using estimateIncidence(), or prevalence, using estimatePointPrevalence() or estimatePeriodPrevalence().

Usage

generateDenominatorCohortSet(
  cdm,
  name,
  cohortDateRange = as.Date(c(NA, NA)),
  ageGroup = list(c(0, 150)),
  sex = "Both",
  daysPriorObservation = 0,
  requirementInteractions = TRUE
)

Arguments

cdm	A CDM reference object
name	Name of the cohort table to be created. Note if a table already exists with this name in the database (give the prefix being used for the cdm reference) it will be overwritten.
cohortDateRange	Two dates. The first indicating the earliest cohort start date and the second indicating the latest possible cohort end date. If NULL or the first date is set as missing, the earliest observation_start_date in the observation_period table will be used for the former. If NULL or the second date is set as missing, the latest observation_end_date in the observation_period table will be used for the latter.
ageGroup	A list of age groups for which cohorts will be generated. A value of list(c(0,17), c(18,30)) would, for example, lead to the creation of cohorts for those aged from 0 to 17, and from 18 to 30. In this example an individual turning 18 during the time period would appear in both cohorts (leaving the first cohort the day before their 18th birthday and entering the second from the day of their 18th birthday).
sex	Sex of the cohorts. This can be one or more of: "Male", "Female", or "Both".
daysPriorObservation	The number of days of prior observation observed in the database required for an individual to start contributing time in a cohort.
requirementInteractions	If TRUE, cohorts will be created for all combinations of ageGroup, sex, and daysPriorObservation. If FALSE, only the first value specified for the other factors will be used. Consequently, order of values matters when requirementInteractions is FALSE.

Value

A cdm reference

Examples

cdm <- mockIncidencePrevalence(sampleSize = 1000)
cdm <- generateDenominatorCohortSet(
  cdm = cdm,
  name = "denominator",
  cohortDateRange = as.Date(c("2008-01-01", "2020-01-01"))
)
cdm

---

Identify a set of denominator populations using a target cohort

Description

generateTargetDenominatorCohortSet() creates a set of cohorts that can be used for the denominator population in analyses of incidence, using estimateIncidence(), or prevalence, using estimatePointPrevalence() or estimatePeriodPrevalence().

Usage

generateTargetDenominatorCohortSet(
  cdm,
  name,
  targetCohortTable,
  targetCohortId = NULL,
  cohortDateRange = as.Date(c(NA, NA)),
  timeAtRisk = c(0, Inf),
  ageGroup = list(c(0, 150)),
  sex = "Both",
  daysPriorObservation = 0,
  requirementInteractions = TRUE
)

Arguments

cdm	A CDM reference object
name	Name of the cohort table to be created.
targetCohortTable	A cohort table in the cdm reference to use to limit cohort entry and exit (with individuals only contributing to a cohort when they are contributing to the cohort in the target table).
targetCohortId	The cohort definition ids or the cohort names of the cohorts of interest for the target table. If NULL all cohorts will be considered in the analysis.
cohortDateRange	Two dates. The first indicating the earliest cohort start date and the second indicating the latest possible cohort end date. If NULL or the first date is set as missing, the earliest observation_start_date in the observation_period table will be used for the former. If NULL or the second date is set as missing, the latest observation_end_date in the observation_period table will be used for the latter.
timeAtRisk	Lower and upper bound for the time at risk window to apply relative to the target cohort entry. A value of list(c(0, 30), c(31, 60)) would, for example, create one set of denominator cohorts with time up to the 30 days following target cohort entry and another set with time from 31 days following entry to 60 days. If time at risk start is after target cohort exit and/ or observation period end then no time will be contributed. If time at risk end is after cohort exit and/ or observation period, then only time up to these will be contributed.
ageGroup	A list of age groups for which cohorts will be generated. A value of list(c(0,17), c(18,30)) would, for example, lead to the creation of cohorts for those aged from 0 to 17, and from 18 to 30. In this example an individual turning 18 during the time period would appear in both cohorts (leaving the first cohort the day before their 18th birthday and entering the second from the day of their 18th birthday).
sex	Sex of the cohorts. This can be one or more of: "Male", "Female", or "Both".
daysPriorObservation	The number of days of prior observation observed in the database required for an individual to start contributing time in a cohort.
requirementInteractions	If TRUE, cohorts will be created for all combinations of ageGroup, sex, and daysPriorObservation. If FALSE, only the first value specified for the other factors will be used. Consequently, order of values matters when requirementInteractions is FALSE.

Value

A cdm reference

Examples

cdm <- mockIncidencePrevalence(sampleSize = 1000)
cdm <- generateTargetDenominatorCohortSet(
  cdm = cdm,
  name = "denominator",
  targetCohortTable = "target",
  cohortDateRange = as.Date(c("2008-01-01", "2020-01-01"))
)
cdm

---

Generate example subset of the OMOP CDM for estimating incidence and prevalence

Description

Generate example subset of the OMOP CDM for estimating incidence and prevalence

Usage

mockIncidencePrevalence(
  personTable = NULL,
  observationPeriodTable = NULL,
  targetCohortTable = NULL,
  outcomeTable = NULL,
  sampleSize = 1,
  outPre = 1,
  seed = 444,
  earliestDateOfBirth = NULL,
  latestDateOfBirth = NULL,
  earliestObservationStartDate = as.Date("1900-01-01"),
  latestObservationStartDate = as.Date("2010-01-01"),
  minDaysToObservationEnd = 1,
  maxDaysToObservationEnd = 4380,
  minOutcomeDays = 1,
  maxOutcomeDays = 10,
  maxOutcomes = 1
)

mockIncidencePrevalenceRef(
  personTable = NULL,
  observationPeriodTable = NULL,
  targetCohortTable = NULL,
  outcomeTable = NULL,
  sampleSize = 1,
  outPre = 1,
  seed = 444,
  earliestDateOfBirth = NULL,
  latestDateOfBirth = NULL,
  earliestObservationStartDate = as.Date("1900-01-01"),
  latestObservationStartDate = as.Date("2010-01-01"),
  minDaysToObservationEnd = 1,
  maxDaysToObservationEnd = 4380,
  minOutcomeDays = 1,
  maxOutcomeDays = 10,
  maxOutcomes = 1
)

Arguments

personTable	A tibble in the format of the person table.
observationPeriodTable	A tibble in the format of the observation period table.
targetCohortTable	A tibble in the format of a cohort table which can be used for stratification
outcomeTable	A tibble in the format of a cohort table which can be used for outcomes
sampleSize	The number of unique patients.
outPre	The fraction of patients with an event.
seed	The seed for simulating the data set. Use the same seed to get same data set.
earliestDateOfBirth	The earliest date of birth of a patient in person table.
latestDateOfBirth	The latest date of birth of a patient in person table.
earliestObservationStartDate	The earliest observation start date for patient format.
latestObservationStartDate	The latest observation start date for patient format.
minDaysToObservationEnd	The minimum number of days of the observational integer.
maxDaysToObservationEnd	The maximum number of days of the observation period integer.
minOutcomeDays	The minimum number of days of the outcome period default set to 1.
maxOutcomeDays	The maximum number of days of the outcome period default set to 10.
maxOutcomes	The maximum possible number of outcomes per person can have default set to 1.

Value

A cdm reference to a duckdb database with mock data.

Examples

cdm <- mockIncidencePrevalence(sampleSize = 100)
cdm

---

List of parameter options for IncidencePrevalence plot functions.

Description

Options are:

hideConfidenceInterval: Logical. Whether to show confidence intervals

line: Logical. Whether to plot a line using geom_line

point: Logical. Whether to plot points using geom_point

facetNcols -> Numeric. Number of facet columns

facetScales -> Character. Should scales be fixed ("fixed", the default), free ("free"), or free in one dimension ("free_x", "free_y")?

Usage

optionsPlot()

Value

List of available parameters and their default values.

Examples

optionsPlot()

---

Additional arguments for the functions tableIncidence.

Description

It provides a list of allowed inputs for .option argument in tableIncidence, and their given default values.

Usage

optionsTableIncidence()

Value

The default .options named list.

Examples

{
optionsTableIncidence()
}

---

Additional arguments for the functions tablePrevalence.

Description

It provides a list of allowed inputs for .option argument in tablePrevalence, and their given default values.

Usage

optionsTablePrevalence()

Value

The default .options named list.

Examples

{
optionsTablePrevalence()
}

---

Plot incidence results

Description

Plot incidence results

Usage

plotIncidence(
  result,
  x = "incidence_start_date",
  y = "incidence_100000_pys",
  ylim = c(0, NA),
  ribbon = FALSE,
  facet = NULL,
  colour = NULL,
  options = list()
)

Arguments

result	Incidence results
x	Variable to plot on x axis
y	Variable to plot on y axis. Options are: "incidence_100000_pys", "outcome_count", "denominator_count", "person_days"
ylim	Limits for the Y axis
ribbon	If TRUE, the plot will join points using a ribbon
facet	Variables to use for facets
colour	Variables to use for colours
options	A list of optional plot options. See optionsPlot() for the default parameters.

Value

A ggplot with the incidence results plotted

Examples

cdm <- mockIncidencePrevalence(sampleSize = 1000)
cdm <- generateDenominatorCohortSet(
  cdm = cdm, name = "denominator",
  cohortDateRange = c(as.Date("2008-01-01"), as.Date("2018-01-01"))
)
inc <- estimateIncidence(
  cdm = cdm,
  denominatorTable = "denominator",
  outcomeTable = "outcome"
)
plotIncidence(inc)

---

Plot prevalence results

Description

Plot prevalence results

Usage

plotPrevalence(
  result,
  x = "prevalence_start_date",
  y = "prevalence",
  ylim = c(0, NA),
  ribbon = FALSE,
  facet = NULL,
  colour = NULL,
  options = list()
)

Arguments

result	Prevalence results
x	Variable to plot on x axis
y	Variable to plot on y axis. Options are: "prevalence", "denominator_count", "outcome_count"
ylim	Limits for the Y axis
ribbon	If TRUE, the plot will join points using a ribbon
facet	Variables to use for facets
colour	Variables to use for colours
options	A list of optional plot options. See optionsPlot() for the default parameters.

Value

A ggplot with the prevalence results plotted

Examples

cdm <- mockIncidencePrevalence(sampleSize = 1000)
cdm <- generateDenominatorCohortSet(
  cdm = cdm, name = "denominator",
  cohortDateRange = c(as.Date("2014-01-01"), as.Date("2018-01-01"))
)
prev <- estimatePointPrevalence(
  cdm = cdm,
  denominatorTable = "denominator",
  outcomeTable = "outcome"
)
plotPrevalence(prev)

---

Table of incidence results

Description

Table of incidence results

Usage

tableIncidence(
  result,
  type = "gt",
  header = c("estimate_name"),
  groupColumn = character(),
  settingsColumn = omopgenerics::settingsColumns(result),
  hide = character(),
  .options = list(),
  settingsColumns = lifecycle::deprecated()
)

Arguments

result	Incidence results
type	Type of table. Can be "gt", "flextable", or "tibble"
header	A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header. The header vector can contain one of the following variables: "cdm_name", "denominator_cohort_name", "outcome_cohort_name", "incidence_start_date", "incidence_end_date", "estimate_name", variables in the strata_name column, and any of the settings columns specified in settingsColumn argument. The header can also include other names to use as overall header labels
groupColumn	Variables to use as group labels. Allowed columns are the same as in header
settingsColumn	Variables from the settings atribute to dispaly in the table
hide	Table columns to exclude, options are the ones described in header
.options	Table options to apply
settingsColumns

Value

Table of results

Examples

cdm <- mockIncidencePrevalence(sampleSize = 1000)
cdm <- generateDenominatorCohortSet(
  cdm = cdm, name = "denominator",
  cohortDateRange = c(as.Date("2008-01-01"), as.Date("2018-01-01"))
)
inc <- estimateIncidence(
  cdm = cdm,
  denominatorTable = "denominator",
  outcomeTable = "outcome"
)
tableIncidence(inc)

---

Table of incidence attrition results

Description

Table of incidence attrition results

Usage

tableIncidenceAttrition(
  result,
  type = "gt",
  header = "variable_name",
  groupColumn = c("cdm_name", "variable_level"),
  settingsColumn = omopgenerics::settingsColumns(result),
  hide = "estimate_name",
  settingsColumns = lifecycle::deprecated()
)

Arguments

result	A summarised_result object. Output of summariseCohortAttrition().
type	Type of table. Check supported types with visOmopResults::tableType().
header	Columns to use as header. See options with colnames(omopgenerics::splitAll(result)). Variables in settingsColumn are also allowed
groupColumn	Variables to use as group labels. Allowed columns are the same as in header
settingsColumn	Variables from the settings atribute to dispaly in the table
hide	Table columns to exclude, options are the ones described in header
settingsColumns

Value

A visual table.

---

Table of prevalence results

Description

Table of prevalence results

Usage

tablePrevalence(
  result,
  type = "gt",
  header = c("estimate_name"),
  groupColumn = character(),
  settingsColumn = omopgenerics::settingsColumns(result),
  hide = character(),
  .options = list(),
  settingsColumns = lifecycle::deprecated()
)

Arguments

result	Prevalence results
type	Type of table. Can be "gt", "flextable", or "tibble"
header	A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header. The header vector can contain one of the following variables: "cdm_name", "denominator_cohort_name", "outcome_cohort_name", "prevalence_start_date", "prevalence_end_date", "estimate_name", variables in the strata_name column, and any of the settings columns specified in settingsColumn argument. The header can also include other names to use as overall header labels
groupColumn	Variables to use as group labels. Allowed columns are the same as in header
settingsColumn	Variables from the settings atribute to dispaly in the table
hide	Table columns to exclude, options are the ones described in header
.options	Table options to apply
settingsColumns

Value

Table of prevalence results

Examples

cdm <- mockIncidencePrevalence(sampleSize = 1000)
cdm <- generateDenominatorCohortSet(
  cdm = cdm, name = "denominator",
  cohortDateRange = c(as.Date("2008-01-01"), as.Date("2018-01-01"))
)
prev <- estimatePointPrevalence(
  cdm = cdm,
  denominatorTable = "denominator",
  outcomeTable = "outcome",
  interval = "months"
)
tablePrevalence(prev)

---

Table of prevalence attrition results

Description

Table of prevalence attrition results

Usage

tablePrevalenceAttrition(
  result,
  type = "gt",
  header = "variable_name",
  groupColumn = c("cdm_name", "variable_level"),
  settingsColumn = omopgenerics::settingsColumns(result),
  hide = "estimate_name",
  settingsColumns = lifecycle::deprecated()
)

Arguments

result	A summarised_result object. Output of summariseCohortAttrition().
type	Type of table. Check supported types with visOmopResults::tableType().
header	Columns to use as header. See options with colnames(omopgenerics::splitAll(result)). Variables in settingsColumn are also allowed
groupColumn	Variables to use as group labels. Allowed columns are the same as in header
settingsColumn	Variables from the settings atribute to dispaly in the table
hide	Table columns to exclude, options are the ones described in header
settingsColumns

Value

A visual table.

---