Package {trialfigs}

Efficacy and safety graphics for clinical review packages

Description

Simulated-data utilities and submission-style figures commonly used in clinical review packages. Not an FDA product. See ta_plot_catalog for the therapeutic-area map.

Author(s)

Shekhar

See Also

plot_km, plot_waterfall, plot_edish

Cox hazard ratio with the investigational arm in the numerator

Description

The reference level is the other arm, so a ratio below 1 favours the investigational arm. One row is returned, for binding into a forest.

Usage

cox_hr(data, time, event, arm, investigational = "Investigational",
  subgroup = "Overall")

Arguments

Value

A one-row data frame with subgroup, estimate, limits and n.

Examples

onc <- simulate_oncology(n_per_arm = 20)
cox_hr(onc$adsl, "os_months", "os_event", "arm")

Color palette for review figures

Description

Named colors for treatment arms and RECIST responses.

Usage

fda_palette()

Value

A named character vector of colors.

Examples

fda_palette()

Theme for review figures

Description

Classic theme with a left-aligned caption for population notes.

Usage

fda_theme(base_size = 11)

Arguments

Value

A ggplot2 theme object.

Examples

fda_theme()

Adverse-event incidence dot plot

Description

Percent of subjects with each term and a Wilson interval, ordered by the risk difference versus the reference arm.

Usage

plot_ae(data, term = "term", arm = "arm", denom = NULL, id = "usubjid",
  reference = "Placebo", title = "Subjects with an adverse event")

Arguments

Value

A ggplot object.

Examples

saf <- simulate_safety(n_per_arm = 25)
plot_ae(saf$adae, denom = saf$adsl, reference = "Placebo")

Mean change from baseline with a confidence interval

Description

The band is the normal approximation to the standard error of the mean. Replace it with the model named in the statistical analysis plan for a primary contrast.

Usage

plot_change(data, visit = "week", change = "chg", arm = "arm",
  title = "Mean change from baseline", xlab = "Week",
  ylab = "Mean change (95% CI)")

Arguments

Value

A ggplot object.

Examples

endo <- simulate_endocrinology(n_per_arm = 15)
plot_change(endo$adlb, title = "HbA1c")

eDISH plot of peak ALT versus peak bilirubin

Description

Log-scale multiples of the upper limit of normal. Reference lines are ALT 3x ULN and total bilirubin 2x ULN. A point in that quadrant needs narrative review; it is not by itself a Hy's law case.

Usage

plot_edish(data, alt = "alt_xuln", bili = "bili_xuln", arm = "arm",
  id = "usubjid", title = "eDISH: peak ALT vs peak total bilirubin")

Arguments

Value

A ggplot object.

Examples

saf <- simulate_safety(n_per_arm = 25)
plot_edish(saf$adlb)

Treatment duration by arm

Description

Box plot of exposure with the median in the caption.

Usage

plot_exposure(data, duration = "trtdur_days", arm = "arm",
  xlab = "Treatment duration (days)", title = "Exposure")

Arguments

Value

A ggplot object.

Examples

saf <- simulate_safety(n_per_arm = 20)
plot_exposure(saf$adsl)

Forest plot of a ratio or a difference

Description

Use null = 1 for hazard ratios and null = 0 for mean differences. Intervals that cross the null are drawn in grey.

Usage

plot_forest(data, label = "subgroup", estimate = "estimate", lcl = "lcl",
  ucl = "ucl", n = NULL, null = 1, xlab = "Hazard ratio (95% CI)",
  title = "Subgroup forest plot", subtitle = NULL,
  favour_left = "Favours investigational",
  favour_right = "Favours control")

Arguments

Value

A ggplot object.

Examples

onc <- simulate_oncology(n_per_arm = 20)
forest <- cox_hr(onc$adsl, "os_months", "os_event", "arm")
plot_forest(forest)

Kaplan-Meier curve with number at risk

Description

Event-free curve with censoring ticks, dashed confidence limits, a log-rank p-value and the number at risk. Competing risks are not modelled.

Usage

plot_km(data, time, event, arm, xlab = "Time (months)",
  ylab = "Event-free probability", title = "Kaplan-Meier estimate",
  subtitle = NULL, conf_int = TRUE, risk_times = NULL, palette = NULL,
  population = "Intent-to-treat population")

Arguments

Value

A ggplot object.

Examples

onc <- simulate_oncology(n_per_arm = 15)
plot_km(onc$adsl, time = "os_months", event = "os_event", arm = "arm")

Baseline versus post-baseline maximum

Description

Points above the identity line rose after baseline.

Usage

plot_lab_shift(data, baseline = "alt_base", post = "alt_max", arm = "arm",
  uln = NULL, title = "Baseline vs post-baseline maximum",
  xlab = "Baseline", ylab = "Post-baseline maximum")

Arguments

Value

A ggplot object.

Examples

saf <- simulate_safety(n_per_arm = 20)
plot_lab_shift(saf$adlb, uln = 1)

Binary responder rate with a Wilson interval

Description

Percent of responders by arm, with a Wilson score interval.

Usage

plot_responder(data, responder, arm, title = "Responder rate",
  ylab = "Responders, percent (Wilson 95% CI)")

Arguments

Value

A ggplot object.

Examples

onc <- simulate_oncology(n_per_arm = 15)
onc$adsl$responder <- onc$adsl$bor %in% c("CR", "PR")
plot_responder(onc$adsl, responder = "responder", arm = "arm")

Spider plot of percent change over time

Description

Individual tumor trajectories with the arm mean overlaid.

Usage

plot_spider(data, id = "usubjid", time = "week", pct = "pct_change",
  arm = "arm", title = "Percent change in sum of diameters")

Arguments

Value

A ggplot object.

Examples

onc <- simulate_oncology(n_per_arm = 8)
plot_spider(onc$adtr)

Swimmer plot of time on treatment

Description

One bar per subject, with points for objective response and progression. Limited to the longest durations so the figure stays readable.

Usage

plot_swimmer(data, id = "usubjid", arm = "arm",
  duration = "trtdur_months", response_time = "resp_months",
  progression_time = "pd_months", max_n = 30, xlab = "Months",
  title = "Time on treatment")

Arguments

Value

A ggplot object.

Examples

onc <- simulate_oncology(n_per_arm = 12)
plot_swimmer(onc$adsl, max_n = 10)

RECIST waterfall of best percent change

Description

Bars of best percent change in the sum of diameters. Reference lines at -30 and +20 follow RECIST 1.1. Subjects with no post-baseline value are omitted.

Usage

plot_waterfall(data, pct = "pct_change", response = "bor", arm = "arm",
  id = "usubjid", title = "Best percent change in sum of diameters",
  subtitle = "RECIST 1.1 reference lines at -30% and +20%",
  palette = NULL)

Arguments

Value

A ggplot object.

Examples

onc <- simulate_oncology(n_per_arm = 15)
plot_waterfall(onc$adsl)

Simulate a cardiovascular outcomes set

Description

Time to first MACE and systolic blood pressure. Synthetic data.

Usage

simulate_cardiovascular(n_per_arm = 220, seed = 20260316)

Arguments

Value

A list with adsl and advs.

Examples

cv <- simulate_cardiovascular(n_per_arm = 20)
plot_km(cv$adsl, time = "mace_months", event = "mace_event", arm = "arm")

Simulate a type 2 diabetes HbA1c set

Description

Longitudinal HbA1c. Synthetic data.

Usage

simulate_endocrinology(n_per_arm = 150, seed = 20260317)

Arguments

Value

A list with adsl and adlb.

Examples

endo <- simulate_endocrinology(n_per_arm = 15)
plot_change(endo$adlb)

Simulate a rheumatoid-arthritis DAS28 set

Description

Longitudinal DAS28. Synthetic data.

Usage

simulate_immunology(n_per_arm = 120, seed = 20260318)

Arguments

Value

A list with adsl and adeff.

Examples

imm <- simulate_immunology(n_per_arm = 15)
plot_change(imm$adeff, title = "DAS28")

Simulate an antiviral viral-load set

Description

Log10 viral load and time to clearance. Synthetic data.

Usage

simulate_infectious(n_per_arm = 100, seed = 20260319)

Arguments

Value

A list with adsl and adlb.

Examples

id <- simulate_infectious(n_per_arm = 15)
plot_change(id$adlb, visit = "day", xlab = "Day")

Simulate a depression MADRS set

Description

Longitudinal MADRS. Synthetic data.

Usage

simulate_neuroscience(n_per_arm = 140, seed = 20260320)

Arguments

Value

A list with adsl and adeff.

Examples

cns <- simulate_neuroscience(n_per_arm = 15)
plot_change(cns$adeff, title = "MADRS")

Simulate a two-arm oncology efficacy set

Description

Subject-level survival, RECIST response, and longitudinal tumor measurements. Data are synthetic. The random-number stream is restored on exit.

Usage

simulate_oncology(n_per_arm = 80, seed = 20260315)

Arguments

Value

A list with adsl and adtr.

Examples

onc <- simulate_oncology(n_per_arm = 10)
plot_waterfall(onc$adsl)

Simulate core safety data

Description

Adverse events and peak liver tests in multiples of the upper limit of normal. Synthetic data.

Usage

simulate_safety(n_per_arm = 160, seed = 20260321)

Arguments

Value

A list with adsl, adae and adlb.

Examples

saf <- simulate_safety(n_per_arm = 20)
plot_edish(saf$adlb)

Recommended displays by therapeutic area

Description

Working catalog of figures commonly discussed in a clinical review. Not a regulatory requirement.

Usage

ta_plot_catalog()

Value

A data frame with therapeutic area, display, function name and anchor.

Examples

head(ta_plot_catalog())