FDA Table 16

Patients With Adverse Events by Male-Specific FDA Medical Query (Broad) and Preferred Term, Male Safety Population, Pooled Analyses

FMQ (Broad)            A: Drug X   B: Placebo   C: Combination   Risk Difference (%) (95% CI)
  Preferred Term        (N=134)     (N=134)        (N=132)                 (N=268)           
—————————————————————————————————————————————————————————————————————————————————————————————
Erectile Dysfunction                                                                         
  dcd B.2.2.3.1        11 (8.2%)   12 (9.0%)      14 (10.6%)           0.7 (-6.0 - 7.5)      
  dcd C.1.1.1.3        7 (5.2%)     5 (3.7%)       7 (5.3%)           -1.5 (-6.4 - 3.5)      
Gynecomastia                                                                                 
  dcd B.2.2.3.1        10 (7.5%)   16 (11.9%)     15 (11.4%)          4.5 (-2.6 - 11.5)      
  dcd C.1.1.1.3        7 (5.2%)     6 (4.5%)      10 (7.6%)           -0.7 (-5.9 - 4.4)      
# Load Libraries & Data
library(cardinal)

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

# Pre-Processing - Ensure required variables FMQ01SC and FMQ01NAM exist in adae
set.seed(1)
adae <- dplyr::rename(adae, FMQ01SC = SMQ01SC, FMQ01NAM = SMQ01NAM)
levels(adae$FMQ01SC) <- c("BROAD", "NARROW")
adae$FMQ01SC[is.na(adae$FMQ01SC)] <- "NARROW"
adae$FMQ01NAM <- factor(adae$FMQ01NAM, levels = c(unique(adae$FMQ01NAM), "Erectile Dysfunction", "Gynecomastia"))
adae$FMQ01NAM[adae$SEX == "M"] <- as.factor(
  sample(c("Erectile Dysfunction", "Gynecomastia"), sum(adae$SEX == "M"), replace = TRUE)
)

# Output Table
risk_diff <- list(arm_x = "B: Placebo", arm_y = "A: Drug X")
make_table_16(adae = adae, alt_counts_df = adsl, risk_diff = risk_diff)

make_table_16()

Required variables:

  • adae: adae must contain USUBJID, SEX, and the variables specified by arm_var, saffl_var, pref_var, fmqsc_var and fmqnam_var.
  • alt_counts_df (if specified): USUBJID and the variables specified by arm_var and saffl_var.
Argument Description Default
adae (data.frame) Dataset (typically ADAE) required to build table. No default
alt_counts_df (character) Alternative dataset used only to calculate column counts. NULL
show_colcounts (flag) Whether column counts should be printed. TRUE
arm_var (character) Arm variable used to split table into columns. "ARM"
saffl_var (character) Flag variable used to indicate inclusion in safety population. "SAFFL"
pref_var (character) Preferred term variable to use in table. "AEDECOD"
sex_scope (character) Level of SEX to output in table. "M"
fmq_scope (character) FMQ scope value to use in table. "BROAD"
fmqsc_var (character) FMQ scope variable to use in table. "FMQ01SC"
fmqnam_var (character) FMQ reference name variable to use in table. "FMQ01NAM"
lbl_overall (character) If specified, an overall column will be added to the table with the given value as the column label. NULL
risk_diff

(named list) List of settings to apply to add a risk difference column to the table. See tern::add_riskdiff() for more details. List should contain the following elements:

  • arm_x: (required) the name of reference arm.

  • arm_y: (required) the name of the arm to compare to the reference arm.

  • col_label: (optional) label to use for the risk difference column. Defaults to "Risk Difference (%) (95% CI)".

  • pct: (optional) whether the output should be returned as percentages. Defaults to TRUE.

 NULL
prune_0 (flag) Whether all-zero rows should be removed from the table. FALSE
na_level (character) String to represent missing values. "<Missing>"
annotations (named list of character) List of annotations to add to the table. Valid annotation types are title, subtitles, main_footer, and prov_footer. Each name-value pair should use the annotation type as name and the desired string as value. NULL

Source code for this function is available here.