Create or adapt an analysis function for injection rate

[edelarua]

Create a new analysis function or adapt estimate_incidence_rate() if possible to calculate rate per injection, with rows as follows:

• "Total number of injections" - default format "xx"
• "Total number of adverse events (Rate per injection)" - default format "xx (xx.x)"

[edelarua]

Hi @barnett11,

This issue relates to AET10ALL_INJ. Are you able to provide some details on how injection data appears in a dataset (or, ideally, dummy data)? Is this data usually part of ADAETTE?

Thanks!!

[barnett11]

Hi @barnett11,

This issue relates to AET10ALL_INJ. Are you able to provide some details on how injection data appears in a dataset (or, ideally, dummy data)? Is this data usually part of ADAETTE?

Thanks!!

Hi @edelarua - it would come from ADEX where PARAMCD="TNDOSE"

[edelarua]

Tentative solution:

library(tern) 

adsl <- random.cdisc.data::cadsl
adex <- random.cdisc.data::cadex
adae <- random.cdisc.data::cadae

# filter injection data so PARAMCD == "TNDOSE"
anl <- dplyr::left_join(
  adae,
  adex %>% 
    dplyr::filter(PARAMCD == "TNDOSE") %>%
    dplyr::select(USUBJID, AVAL),
  by = "USUBJID"
)

a_ae_dose_rate <- function(df,
                           .var,
                           aval_var = "AVAL",
                           id_var = "USUBJID",
                           per_n_dose = NULL,
                           tot_inj_row = TRUE,
                           tot_ae_row = TRUE,
                           .df_row,
                           .N_col,
                           .labels = list(
                             tot_inj = "Total number of injections",
                             tot_ae = "Total number of adverse events (rate per injection)"
                           ),
                           .formats = list(tot_inj = "xx", tot_ae = "xx (xx.xx)", ae_rows = "xx (xx.xx)"),
                           .indent_mods = list(tot_inj = 0L, tot_ae = 0L, ae_rows = 1L),
                           na_str = default_na_str()) {
  # process data
  df_dose <- df %>% dplyr::distinct(.data[[id_var]], .keep_all = TRUE)
  if (is.null(per_n_dose)) per_n_dose <- 1
  
  # calculate statistics
  tot_dose <- sum(df_dose[[aval_var]])
  ae_cts <- s_count_occurrences(df = df, .var = .var, .N_col = .N_col, .df_row = .df_row)$count
  ae_cts_rates <- lapply(ae_cts, function(x, per_n) c(x, x / tot_dose * per_n), per_n = per_n_dose)

  # apply formatting
  .formats <- c(
    if (tot_inj_row) .formats$tot_inj, 
    if (tot_ae_row) .formats$tot_ae, 
    rep(.formats$ae_rows, length(ae_cts))
  )
  .indent_mods <- c(
    if (tot_inj_row) .indent_mods$tot_inj, 
    if (tot_ae_row) .indent_mods$tot_ae, 
    rep(.indent_mods$ae_rows, length(ae_cts))
  )
  
  # add total AEs row
  if (tot_ae_row) {
    overall_aes <- sum(unlist(ae_cts))
    overall <- list(c(overall_aes, overall_aes / tot_dose * per_n_dose))
    names(overall) <- .labels$tot_ae
    ae_cts_rates <- c(overall, ae_cts_rates)
  }

  # add total injections row
  if (tot_inj_row) {
    overall <- list(tot_dose)
    names(overall) <- .labels$tot_inj
    ae_cts_rates <- c(overall, ae_cts_rates)
  }
  
  in_rows(
    .list = ae_cts_rates,
    .formats = .formats,
    .indent_mods = .indent_mods,
    .format_na_strs = na_str
  )
}

basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ARM") %>%
  analyze(
    vars = "AETERM",
    afun = a_ae_dose_rate,
    extra_args = list(
      tot_inj_row = TRUE, tot_ae_row = TRUE, 
      per_n_dose = 100,
      .labels = list(
        tot_inj = "Total number of injections",
        tot_ae = "Total number of adverse events (rate per 100 injections)"
      )
    )
  ) %>%
  append_topleft("MedDRA Preferred Term") %>%
  build_table(anl, alt_counts_df = adsl)
#>                                                             A: Drug X    B: Placebo    C: Combination
#> MedDRA Preferred Term                                        (N=134)       (N=134)        (N=132)    
#> —————————————————————————————————————————————————————————————————————————————————————————————————————
#> Total number of injections                                     854           861            840      
#> Total number of adverse events (rate per 100 injections)   465 (54.45)   476 (55.28)    515 (61.31)  
#>   trm A.1.1.1.1                                             50 (5.85)     45 (5.23)      63 (7.50)   
#>   trm A.1.1.1.2                                             48 (5.62)     48 (5.57)      50 (5.95)   
#>   trm B.1.1.1.1                                             47 (5.50)     49 (5.69)      43 (5.12)   
#>   trm B.2.1.2.1                                             49 (5.74)     44 (5.11)      52 (6.19)   
#>   trm B.2.2.3.1                                             48 (5.62)     54 (6.27)      51 (6.07)   
#>   trm C.1.1.1.3                                             43 (5.04)     46 (5.34)      43 (5.12)   
#>   trm C.2.1.2.1                                             35 (4.10)     48 (5.57)      55 (6.55)   
#>   trm D.1.1.1.1                                             50 (5.85)     42 (4.88)      51 (6.07)   
#>   trm D.1.1.4.2                                             48 (5.62)     42 (4.88)      50 (5.95)   
#>   trm D.2.1.5.3                                             47 (5.50)     58 (6.74)      57 (6.79)

^{Created on 2024-09-09 with reprex v2.1.1}