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Update safety table templates with modifications from chevron #67

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merged 10 commits into from
Aug 3, 2023
Merged

Update safety table templates with modifications from chevron #67

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ea6955e
Update safety tables
edelarua Jul 5, 2023
0681d40
Minor changes
edelarua Jul 6, 2023
bc53770
Merge branch 'main' into 61_safety_chevron_changes@main
edelarua Jul 6, 2023
becdb66
Merge bc5377056ce35ab700fcb6eaee7b3e3ece35da52 into 3e01775a80033639b…
edelarua Jul 6, 2023
d7560d3
[skip actions] Restyle files
github-actions[bot] Jul 6, 2023
c2e9e8e
Empty commit
edelarua Jul 6, 2023
041bdf2
Switch to new format
edelarua Jul 31, 2023
30d288d
Merge branch 'main' into 61_safety_chevron_changes@main
edelarua Jul 31, 2023
ef4ca2d
Fix egt02
edelarua Jul 31, 2023
6ab0164
Update snapshots
edelarua Aug 2, 2023
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36 changes: 10 additions & 26 deletions book/tables/safety/cmt01a.qmd
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,8 @@ adsl <- adsl %>%
filter(SAFFL == "Y")

adcm <- adcm %>%
filter(SAFFL == "Y" & ATIREL == "CONCOMITANT")
filter(SAFFL == "Y" & ATIREL == "CONCOMITANT") %>%
var_relabel(CMDECOD = "Other Treatment")
```

## Standard Table, <br/> Safety-Evaluable Patients
Expand All @@ -43,7 +44,7 @@ adcm <- adcm %>%
split_fun <- drop_split_levels

lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by("ARM") %>%
split_cols_by("ACTARM") %>%
analyze_num_patients(
vars = "USUBJID",
count_by = "CMSEQ",
Expand Down Expand Up @@ -73,11 +74,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
count_occurrences(vars = "CMDECOD", .indent_mods = -1L) %>%
append_varlabels(adcm, "CMDECOD", indent = 1L)

result <- build_table(
lyt = lyt,
df = adcm,
alt_counts_df = adsl
) %>%
result <- build_table(lyt = lyt, df = adcm, alt_counts_df = adsl) %>%
prune_table() %>%
# Sort lowest level terms by descending frequency.
sort_at_path(
Expand All @@ -94,7 +91,7 @@ result
split_fun <- drop_split_levels

lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by("ARM") %>%
split_cols_by("ACTARM") %>%
analyze_num_patients(
vars = "USUBJID",
count_by = "CMSEQ",
Expand Down Expand Up @@ -124,11 +121,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
count_occurrences(vars = "CMDECOD", .indent_mods = -1L) %>%
append_varlabels(adcm, "CMDECOD", indent = 1L)

result <- build_table(
lyt = lyt,
df = adcm,
alt_counts_df = adsl
) %>%
result <- build_table(lyt = lyt, df = adcm, alt_counts_df = adsl) %>%
prune_table() %>%
# Sort lowest level terms by descending frequency.
sort_at_path(
Expand All @@ -145,7 +138,7 @@ result
split_fun <- drop_split_levels

lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by("ARM") %>%
split_cols_by("ACTARM") %>%
analyze_num_patients(
vars = "USUBJID",
count_by = "CMSEQ",
Expand Down Expand Up @@ -175,11 +168,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
count_occurrences(vars = "CMDECOD", .indent_mods = -1L) %>%
append_varlabels(adcm, "CMDECOD", indent = 1L)

result <- build_table(
lyt = lyt,
df = adcm,
alt_counts_df = adsl
) %>%
result <- build_table(lyt = lyt, df = adcm, alt_counts_df = adsl) %>%
prune_table() %>%
sort_at_path(path = c("ATC2"), scorefun = cont_n_allcols) %>%
sort_at_path(path = c("ATC2", "*", "CMDECOD"), scorefun = score_occurrences)
Expand All @@ -193,7 +182,7 @@ result
split_fun <- drop_split_levels

lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by("ARM") %>%
split_cols_by("ACTARM") %>%
analyze_num_patients(
vars = "USUBJID",
count_by = "CMSEQ",
Expand Down Expand Up @@ -222,11 +211,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
count_occurrences(vars = "CMDECOD", .indent_mods = -1L) %>%
append_varlabels(adcm, "CMDECOD", indent = 1L)

result <- build_table(
lyt = lyt,
df = adcm,
alt_counts_df = adsl
) %>%
result <- build_table(lyt = lyt, df = adcm, alt_counts_df = adsl) %>%
prune_table() %>%
# Sort lowest level terms by descending frequency.
sort_at_path(
Expand Down Expand Up @@ -305,5 +290,4 @@ shinyApp(app$ui, app$server)
```

{{< include ../../si.qmd >}}

:::
16 changes: 5 additions & 11 deletions book/tables/safety/cmt02_pt.qmd
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -24,10 +24,8 @@ adcm$CMSEQ <- as.factor(adcm$CMSEQ)

# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.
# If you want your missing levels to show as "No Coding Available", please use
# adsl <- df_explicit_na(adsl, na_level = "No Coding Available")
# adcm <- df_explicit_na(adcm, na_level = "No Coding Available")
adsl <- df_explicit_na(adsl)
adcm <- df_explicit_na(adcm)
adsl <- df_explicit_na(adsl, na_level = "No Coding Available")
adcm <- df_explicit_na(adcm, na_level = "No Coding Available")

# Keep only safety-evaluable patients and concomitant medications
adsl <- adsl %>%
Expand All @@ -43,7 +41,7 @@ adcm <- adcm %>% filter(ATIREL == "CONCOMITANT")
split_fun <- drop_split_levels

lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by("ARM") %>%
split_cols_by("ACTARM") %>%
add_overall_col("All Patients") %>%
analyze_num_patients(
vars = "USUBJID",
Expand All @@ -56,13 +54,9 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
show_labels = "hidden"
) %>%
count_occurrences(vars = "CMDECOD") %>%
append_varlabels(adcm, "CMDECOD", indent = 0)
append_topleft(paste("\nOther Treatment"))

result <- build_table(
lyt = lyt,
df = adcm,
alt_counts_df = adsl
) %>%
result <- build_table(lyt = lyt, df = adcm, alt_counts_df = adsl) %>%
sort_at_path(
path = c("CMDECOD"),
scorefun = score_occurrences
Expand Down
34 changes: 21 additions & 13 deletions book/tables/safety/dmt01.qmd
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@ adsl <- adsl %>%
SEX == "U" ~ "Unknown",
SEX == "UNDIFFERENTIATED" ~ "Undifferentiated"
)),
AGEGRP = factor(
AGEGR1 = factor(
case_when(
between(AGE, 18, 40) ~ "18-40",
between(AGE, 41, 64) ~ "41-64",
Expand Down Expand Up @@ -79,52 +79,58 @@ get_param_adsub <- function(pname, plabel) {
ds
}
adsl <- adsl %>%
left_join(get_param_advs("SBP", "Systolic Blood Pressure")) %>%
left_join(get_param_advs("DBP", "Diastolic Blood Pressure")) %>%
left_join(get_param_advs("WGT", "Weight")) %>%
left_join(get_param_adsub("BBMISI", "Baseline BMI"))
left_join(get_param_advs("SBP", "Systolic Blood Pressure"), by = "USUBJID") %>%
left_join(get_param_advs("DBP", "Diastolic Blood Pressure"), by = "USUBJID") %>%
left_join(get_param_advs("WGT", "Weight"), by = "USUBJID") %>%
left_join(get_param_adsub("BBMISI", "Baseline BMI"), by = "USUBJID")
```

## Table with an Additional <br/> Study-Specific Continuous Variable

```{r variant1, test = list(result_v1 = "result")}
vars <- c("AGE", "SEX", "RACE", "BMRKR1")
vars <- c("AGE", "AGEGR1", "SEX", "ETHNIC", "RACE", "BMRKR1")
var_labels <- c(
"Age (yr)",
"Age Group",
"Sex",
"Ethnicity",
"Race",
"Continous Level Biomarker 1"
)

result <- basic_table(show_colcounts = TRUE) %>%
split_cols_by(var = "ARM") %>%
split_cols_by(var = "ACTARM") %>%
add_overall_col("All Patients") %>%
summarize_vars(
vars = vars,
var_labels = var_labels
) %>%
build_table(adsl)

result
```

## Table with an Additional <br/> Study-Specific Categorical Variable

```{r variant2, test = list(result_v2 = "result")}
vars <- c("AGE", "SEX", "RACE", "BMRKR1_CAT")
vars <- c("AGE", "AGEGR1", "SEX", "ETHNIC", "RACE", "BMRKR1_CAT")
var_labels <- c(
"Age (yr)",
"Age Group",
"Sex",
"Ethnicity",
"Race",
"Biomarker 1 Categories"
)

result <- basic_table(show_colcounts = TRUE) %>%
split_cols_by(var = "ARM") %>%
split_cols_by(var = "ACTARM") %>%
summarize_vars(
vars = vars,
var_labels = var_labels
) %>%
build_table(adsl)

result
```

Expand All @@ -134,7 +140,7 @@ result
split_fun <- drop_split_levels

result <- basic_table(show_colcounts = TRUE) %>%
split_cols_by(var = "ARM") %>%
split_cols_by(var = "ACTARM") %>%
summarize_vars(
vars = c("AGE", "SEX", "RACE"),
var_labels = c("Age", "Sex", "Race")
Expand All @@ -144,14 +150,15 @@ result <- basic_table(show_colcounts = TRUE) %>%
) %>%
summarize_vars("BMRKR1") %>%
build_table(adsl)

result
```

## Table with Additional Vital <br/> Signs Baseline Values

```{r variant4, test = list(result_v4 = "result")}
result <- basic_table(show_colcounts = TRUE) %>%
split_cols_by(var = "ARM") %>%
split_cols_by(var = "ACTARM") %>%
summarize_vars(
vars = c("AGE", "SEX", "RACE", "DBP", "SBP"),
var_labels = c(
Expand All @@ -163,14 +170,15 @@ result <- basic_table(show_colcounts = TRUE) %>%
)
) %>%
build_table(adsl)

result
```

## Table with Additional <br/> Values from ADSUB

```{r variant5, test = list(result_v5 = "result")}
result <- basic_table(show_colcounts = TRUE) %>%
split_cols_by(var = "ARM") %>%
split_cols_by(var = "ACTARM") %>%
summarize_vars(
vars = c("AGE", "SEX", "RACE", "BBMISI"),
var_labels = c(
Expand All @@ -181,6 +189,7 @@ result <- basic_table(show_colcounts = TRUE) %>%
)
) %>%
build_table(adsl)

result
```

Expand Down Expand Up @@ -226,5 +235,4 @@ shinyApp(app$ui, app$server)
```

{{< include ../../si.qmd >}}

:::
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