Create server for dv.clinlines module

mod_clinical_timelines_server acts as central for managing the communication between main view and local filter module.

Usage

mod_clinical_timelines_server(
  module_id,
  data_name,
  dataset_list,
  basic_info = default_basic_info(),
  mapping = default_mapping(),
  drug_admin = default_drug_admin(),
  filter = NULL,
  subjid_var = "USUBJID",
  start_day = NULL,
  ms = 1000,
  receiver_id = NULL,
  afmm_param = NULL
)

Arguments

module_id

[character(1)]

A unique ID string to create a namespace. Must match the ID of mod_clinical_timelines_UI().

data_name

[shiny::reactive(character(1)]

A reactive string name of the selected set of dataset. Usually obtained from module manager.

dataset_list

[shiny::reactive(list(data.frame+))]

A reactive list of named datasets. Usually obtained from module manager.

basic_info

[list(character(1)+)]

A list of four elements: subject_level_dataset_name, trt_start_var, trt_end_var, and icf_date_var. Assigns the name of a subject level dataset and column names of treatment start and end, and informed consent variables.

mapping

[list(list(list(character(1)+)))]

A list of lists. It serves as instruction on which event to take from which data domain / dataset, and further from which variables to take the start and end values, etc., that will be plotted as clinical timelines. Elements need to follow a certain structure that is described in the Details section below.

drug_admin

[list(character(1)+) | NULL]

A list of named character strings that describes which variables to use to display drug administration events. Set it to NULL to deactivate them.

filter

[list(list(character(1)+)) | NULL]

A list that specifies information for local adverse events filters. Set to NULL (default) for no filters.

subjid_var

[character(1)]

Character name of the unique subject identifier column in all datasets (default is USUBJID). Must be a single value.

start_day

[integer(1) | NULL]

A single integer indicating the lower x-axis limit in case of study day display. Defaults to NULL, using the day of the earliest event to be displayed.

ms

[numeric(1)]

Single numeric value indicating how many milliseconds to wait before the plot re-renders. Defaults to 1000.

receiver_id

[character(1) | NULL]

Character string defining the ID of the module to which to send a subject ID. The module must exist in the module list. The default is NULL which disables communication.

afmm_param

[list]

Named list of a selection of arguments from module manager. Expects at least two elements: utils and module_names defining a character vector whose entries have the corresponding module IDs as names.

Value

A reactive subject id string in a list for communication between modules with an attribute code that contains the code to be used by the export functionality of dv.manager.

Details

The basic_info list must contain the following elements:

subject_level_dataset_name: Character name of the subject level analysis dataset (e.g. "adsl", "dm") as it is called in the datalist that is provided to the modulemanager.
trt_start_var: Character name of the variable that contains treatment start dates which must be present in the dataset mentioned in the data element.
trt_end_var: Character name of the variable that contains treatment end dates which must be present in the dataset mentioned in the data element.
icf_date_var: Character name of the variable that contains informed consent dates which must be present in the dataset mentioned in the data element.

The list provided to mapping must follow a strict hierarchy. It must contain one entry per dataset/domain that serves as basis for the events. These entries need to be named according to the names of the datalist that is provided to the modulemanager. The entries by oneself must again be lists.
These second level lists contain the variable names that are needed to plot the events, gathered in yet another lists, which are named according to the labels that shall be assigned to each event, and that contain the following elements each:

start_dt_var: Character name of the variable that contains either the event start dates (for interval events) or merely timepoints (e.g. milestones). The variable name must be present in the dataset under which the event is listed.
end_dt_var: Character name of the variable that contains the event end dates. Needs to be provided for interval events, but set to NULL for timepoints. The variable name must be present in the dataset under which the event is listed.
start_dy_var: Similar to start_dt_var, but refers to the study relative days (instead of dates). The variable name must be present in the dataset under which the event is listed. Can be set to NULL to let the module calculate the study days according to SDTM standard rules.
end_dy_var: Similar to end_dt_var, but refers to the study relative days (instead of dates). The variable name must be present in the dataset under which the event is listed. Can be set to NULL to let the module calculate the study days according to SDTM standard rules.
detail_var: Character name of the variable that contains further descriptive information that shall be displayed for the event. Can be set to NULL for no further information.

The structure of the mapping parameters for one single event is mentioned below. It is possible to define multiple events for one dataset, and multiple datasets in the mapping list.

mapping = list(
<data name> = list(
<event label> = list(
start_dt_var = <variable name>,
end_dt_var = <variable name or NULL>,
start_dy_var = <variable name or NULL>,
end_dy_var = <variable name or NULL>,
detail_var = <variable name or NULL>
)
)
)

If not NULL, the drug_admin list must contain the following elements:

dataset_name: Character name of the dataset that holds drug administration data (e.g. ex domain), as it is called in the datalist that is provided to the modulemanager.
start_var: Character name of the variable that contains the start dates (e.g. exposure start dates) which must be present in the dataset mentioned in the name element.
end_var: Character name of the variable that contains the end dates (e.g. exposure end dates) which must be present in the dataset mentioned in the name element.
detail_var: Character name of the variable that contains the treatment information. Must exist in the dataset mentioned in the name element.
label: Free-text character label for the drug administration event.
dose_var: Character name of the variable that contains the dosis level information. Must exist in the dataset mentioned in the name element.
dose_unit_var: Character name of the variable that contains the dosis unit. Must exist in the dataset mentioned in the name element.

If not NULL, filter defines local filters. So far, the following filters for adverse events are available:

serious_ae_var: Filter for serious adverse events.
soc_var: Filter for system organ classes.
pref_term_var: Filter for preferred terms.
drug_rel_ae_var: Filter for drug related adverse events.

The filter parameter must be a list that contains yet another list for adverse events filters, that is named ae_filter, and that holds the following elements:

dataset_name: Character name of the adverse events dataset. Must be available in in the datalist that is provided to the modulemanager.
label: Character value which is exactly the same as the name for the adverse events event defined in mapping.
serious_ae_var: Character name of the adverse events variable that contains serious adverse events flags (Y/N).
soc_var: Character name of the adverse events variable that contains system organ classes.
pref_term_var: Character name of the adverse events variable that contains preferred terms.
drug_rel_ae_var: Character name of the adverse events variable that contains drug related (causality) flags (Y/N).

Usage

Arguments

Value

Details

See also