Adding custom adverse event filters

{dv.clinlines} offers optional local filters for adverse event data which will be added to the bottom of the sidebar. The following filters are available:

• serious_ae_var: Offers the possibility to filter adverse events to show only serious/non-serious adverse events.
• soc_var: Offers the possibility to filter adverse events by System Organ Class.
• pref_term_var: Offers the possibility to filter adverse events by Preferred Term.
• drug_rel_ae_var: Offers the possibility to filter adverse events to show only drug related/non drug related adverse events.

Activate local filters by adding their names through a list to the filter parameter of the mod_clinical_timelines() call. Use NULL (the default) to turn all filters down. To specify one or multiple local adverse event filters, you need to provide a list with the following elements:

• dataset_name: Character name of the adverse events dataset of your loaded data list. Must be a single value. (Mandatory.)
• label: Character value which is exactly the same as the name for the adverse events event defined in the mapping parameter of mod_clinical_timelines().
• serious_ae_var: Character name of the variable that holds Y/N flags for serious adverse events. Must be a single value.
• soc_var: Character name of the variable that holds system organ classes. Must be a single value.
• pref_term_var: Character name of the variable that holds preferred terms. Must be a single value.
• drug_rel_ae_var: Character name of the variable that holds Y/N flags for causality. Must be a single value.

Wrap this list with another list. The inner list must be named ae_filter. The outer list should be assigned to the filter parameter of mod_clinical_timelines().

Find an example of the code structure below:

# To deactivate local filters
filter <- NULL

# To activate all local adverse event filters
filter <- list(
  ae_filter = list(
    dataset_name = "adae", # mandatory - as defined in the data list
    label = "Adverse Events", # mandatory - as defined in the mapping parameter
    soc_var = "AESOC",
    serious_ae_var = "AESER",
    pref_term_var = "AEDECOD",
    drug_rel_ae_var = "AEREL"
  )
)

For multiple filters, filtering will be performed using AND condition.

The code below shows a module list containing a Clinical Timelines module with only three local adverse event filters:

module_list <- list(
  "Clinical Timelines" = mod_clinical_timelines(
    module_id = "mod1",
    basic_info = list(
      subject_level_dataset_name = "adsl",
      trt_start_var = "TRTSDT",
      trt_end_var = "TRTEDT",
      icf_date_var = "RFICDT"
    ),
    mapping = list(
      adsl = list(
        "Treatment Start" = list(
          start_dt_var = "TRTSDT",
          end_dt_var = NULL,
          start_dy_var = NULL,
          end_dy_var = NULL,
          detail_var = NULL
        ),
        "Treatment End" = list(
          start_dt_var = "TRTEDT",
          end_dt_var = NULL,
          start_dy_var = NULL,
          end_dy_var = NULL,
          detail_var = NULL
        )
      ),
      adae = list(
        "Adverse Events" = list(
          start_dt_var = "AESTDTC",
          end_dt_var = "AEENDTC",
          start_dy_var = NULL,
          end_dy_var = NULL,
          detail_var = "AEDECOD"
        )
      )
    ),
    drug_admin = list(
      dataset_name = "exp",
      start_var = "EXSTDTC",
      end_var = "EXENDTC",
      detail_var = "EXTRT",
      label = "Drug Administration",
      dose_var = "EXDOSE",
      dose_unit_var = "EXDOSU"
    ),
    filter = list(
      ae_filter = list(
        dataset_name = "adae",
        label = "Adverse Events",
        soc_var = "AESOC",
        serious_ae_var = "AESER",
        drug_rel_ae_var = "AEREL"
        # Note: The pref_term_var filter is not specified in this example.
      )
    )
  )
)