Package 'phase12designs' reference manual

Title:	Comprehensive Tools for Running Model-Assisted Phase I/II Trial Simulations
Description:	Provides a comprehensive set of tools to simulate, evaluate, and compare model-assisted designs for early-phase (Phase I/II) clinical trials, including: - BOIN12 (Bayesian optimal interval phase 1/11 trial design; Lin et al. (2020) <doi:10.1200/PO.20.00257>), - BOIN-ET (Takeda, K., Taguri, M., & Morita, S. (2018) <doi:10.1002/pst.1864>), - EffTox (Thall, P. F., & Cook, J. D. (2004) <doi:10.1111/j.0006-341X.2004.00218.x>), - Ji3+3 (Joint i3+3 design; Lin, X., & Ji, Y. (2020) <doi:10.1080/10543406.2020.1818250>), - PRINTE (probability intervals of toxicity and efficacy design; Lin, X., & Ji, Y. (2021) <doi:10.1177/0962280220977009>), - STEIN (simple toxicity and efficacy interval design; Lin, R., & Yin, G. (2017) <doi:10.1002/sim.7428>), - TEPI (toxicity and efficacy probability interval design; Li, D. H., Whitmore, J. B., Guo, W., & Ji, Y. (2017) <doi:10.1158/1078-0432.CCR-16-1125>), - uTPI (utility-based toxicity Probability interval design; Shi, H., Lin, R., & Lin, X. (2024) <doi:10.1002/sim.8922>). Includes flexible simulation parameters that allow researchers to efficiently compute operating characteristics under various fixed and random trial scenarios and export the results.
Authors:	Angela Cao [aut, cre], Haolun Shi [ctb]
Maintainer:	Angela Cao <[email protected]>
License:	MIT + file LICENSE
Version:	0.3.1
Built:	2026-05-31 07:20:05 UTC
Source:	https://github.com/cran/phase12designs

Decision map plot

Description

This function creates a decision plot containing customizable decision zones.

Usage

decision_plot(
  filename,
  filetype = c("png", "pdf", "svg"),
  xlab = "Toxicity Probability",
  ylab = "Efficacy Probability",
  x_breaks = c(0, 1),
  y_breaks = c(0, 1),
  x_labels = c(0, 1),
  y_labels = c(0, 1),
  zones = list(),
  legend_info = list(labels = NULL, colors = NULL),
  title = NULL,
  title_pos = c(0.05, 1.1),
  legend_pos = c(0.3, 1.2),
  grid_lines = TRUE,
  plot_size = c(7, 7)
)
decision_plot(
  filename,
  filetype = c("png", "pdf", "svg"),
  xlab = "Toxicity Probability",
  ylab = "Efficacy Probability",
  x_breaks = c(0, 1),
  y_breaks = c(0, 1),
  x_labels = c(0, 1),
  y_labels = c(0, 1),
  zones = list(),
  legend_info = list(labels = NULL, colors = NULL),
  title = NULL,
  title_pos = c(0.05, 1.1),
  legend_pos = c(0.3, 1.2),
  grid_lines = TRUE,
  plot_size = c(7, 7)
)

Arguments

filename

File path.

filetype

File type.

xlab

x-axis label. (Default is "Toxicity Probability")

ylab

y-axis label. (Default is "Efficacy Probability")

x_breaks

Numeric vector for x-axis major ticks. (Default is 'c(0, 1')

y_breaks

Numeric vector for y-axis major ticks. (Default is 'c(0, 1')

x_labels

Labels corresponding to x_breaks. (Default is 'c(0, 1')

y_labels

Labels corresponding to y_breaks. (Default is 'c(0, 1')

zones

A list of rectangular zones to draw, where each rectangle is a list with elements xmin, xmax, ymin, ymax, and color.

legend_info

A list with two elements: labels (character vector) and colors (character vector) for the legend.

title

Title of plot. (Default is 'NULL')

title_pos

A numeric vector (x, y) indicating the position of the title text.

legend_pos

A numeric vector (x, y) indicating the position of the legend.

grid_lines

Whether to include background grid lines. (Default is TRUE.)

plot_size

A numeric vector indicating width and height. (Default is c(7, 7)).

Value

No return value, called for side effects.

Examples

zones <- list(list(xmin = 0.0, xmax = 0.2, ymin = 0, ymax = 1.0, color = "#a8eea8"),
              list(xmin = .2, xmax = .3, ymin = 0, ymax = 0.6, color = "#a8eea8"),
              list(xmin = .2, xmax = .3, ymin = .6, ymax = 1, color = "#a8d5ee"))
tmpfile <- tempfile(fileext = ".png")
decision_plot(tmpfile, filetype = "png", zones = zones, title = "Decision Zones")

zones <- list(list(xmin = 0.0, xmax = 0.2, ymin = 0, ymax = 1.0, color = "#a8eea8"),
              list(xmin = .2, xmax = .3, ymin = 0, ymax = 0.6, color = "#a8eea8"),
              list(xmin = .2, xmax = .3, ymin = .6, ymax = 1, color = "#a8d5ee"))
tmpfile <- tempfile(fileext = ".png")
decision_plot(tmpfile, filetype = "png", zones = zones, title = "Decision Zones")

Compute operating characteristics using BOIN12

Description

oc_boin12() uses the BOIN12 design to compute operating charateristics of a user-specificed trial scenario. This design places significance on optimizing utility and the toxicity–efficacy trade-off.

Usage

oc_boin12(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  psafe = 0.95,
  pfutility = 0.95,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)
oc_boin12(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  psafe = 0.95,
  pfutility = 0.95,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)

Arguments

ndose

Integer. Number of dose levels. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

ncohort

Integer. Number of cohorts. (Default is 10)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

OBD

Integer. True index of the Optimal Biological Dose (OBD) for the trial scenario. (Default is 0)

If set to 0: Random OBD will be selected.
Other: Treat this argument as the true OBD.

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.95)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list of the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

Value

A list containing operating characteristics such as:

bd.sel: OBD selection percentage
od.sel: Favorable dose selection percentage
bd.pts: Average percentage of patients at the OBD
od.pts: Average percentage of patients at the favorable doses
earlystop: Percentage of early stopped trials
overdose: Overdose patients percentage
poorall: Poor allocation percentage
ov.sel: Overdose selection percentage

Examples

oc_boin12(
  ndose = 5,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)

oc_boin12(
  ndose = 5,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)

Compute operating characteristics using BOINET

Description

oc_boinet() uses the BOINET design to compute operating charateristics of a user-specificed trial scenario. This design uses target toxicity and efficacy rates jointly to form the cutoff intervals within a decision map.

Usage

oc_boinet(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  psafe = 0.95,
  pfutility = 0.95,
  ntrial = 10000,
  utilitytype = 1,
  prob = NULL
)
oc_boinet(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  psafe = 0.95,
  pfutility = 0.95,
  ntrial = 10000,
  utilitytype = 1,
  prob = NULL
)

Arguments

ndose

Integer. Number of dose levels. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

ncohort

Integer. Number of cohorts. (Default is 10)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

OBD

Integer. True index of the Optimal Biological Dose (OBD) for the trial scenario. (Default is 0)

If set to 0: Random OBD will be selected.
Other: Treat this argument as the true OBD.

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.95)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list with the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

Value

A list containing operating characteristics such as:

bd.sel: OBD selection percentage
od.sel: Favorable dose selection percentage
bd.pts: Average percentage of patients at the OBD
od.pts: Average percentage of patients at the favorable doses
earlystop: Percentage of early stopped trials
overdose: Overdose patients percentage
poorall: Poor allocation percentage
ov.sel: Overdose selection percentage

Examples

oc_boinet(
  ndose = 5,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)
oc_boinet(
  ndose = 5,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)

Compute operating characteristics using EffTox

Description

oc_efftox() uses the EffTox design to compute operating charateristics of a user-specificed trial scenario. This design uses toxicity–efficacy trade-off contours.

Usage

oc_efftox(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  startdose = 1,
  OBD = 0,
  ntrial = 10000,
  utilitytype = 1,
  prob = NULL
)
oc_efftox(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  startdose = 1,
  OBD = 0,
  ntrial = 10000,
  utilitytype = 1,
  prob = NULL
)

Arguments

ndose

Integer. Number of dose levels. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

ncohort

Integer. Number of cohorts. (Default is 10)

startdose

Integer. Starting dose level. (Default is 1)

OBD

Integer. True index of the Optimal Biological Dose (OBD) for the trial scenario. (Default is 0)

If set to 0: Random OBD will be selected.
Other: Treat this argument as the true OBD.

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list of the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

Value

A list containing operating characteristics such as:

bd.sel: OBD selection percentage
od.sel: Favorable dose selection percentage
bd.pts: Average percentage of patients at the OBD
od.pts: Average percentage of patients at the favorable doses
earlystop: Percentage of early stopped trials
overdose: Overdose patients percentage
poorall: Poor allocation percentage
ov.sel: Overdose selection percentage

Examples

oc_efftox(
  ndose = 2,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 1,
)
oc_efftox(
  ndose = 2,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 1,
)

Compute operating characteristics using Ji3+3

Description

oc_ji3p3() uses the Ji3+3 design to compute operating charateristics of a user-specificed trial scenario. This design compares observed efficacy and toxicity with predefined target rates.

Usage

oc_ji3p3(
  ndose,
  target_t,
  target_e,
  lower_e = 0.2,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  eps1 = 0.05,
  eps2 = 0.05,
  psafe = 0.95,
  pfutility = 0.95,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)
oc_ji3p3(
  ndose,
  target_t,
  target_e,
  lower_e = 0.2,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  eps1 = 0.05,
  eps2 = 0.05,
  psafe = 0.95,
  pfutility = 0.95,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)

Arguments

ndose

Integer. Number of dose levels. (Required)

target_t

Numeric. Target toxicity probability. (Required)

target_e

Numeric. Target efficacy probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

ncohort

Integer. Number of cohorts. (Default is 10)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

OBD

Integer. True index of the Optimal Biological Dose (OBD) for the trial scenario. (Default is 0)

If set to 0: Random OBD will be selected.
Other: Treat this argument as the true OBD.

eps1

Numerical. Width of the subrectangle.

eps2

Numerical. Width of the subreactangle.

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.95)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list of the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

Value

A list containing operating characteristics such as:

bd.sel: OBD selection percentage
od.sel: Favorable dose selection percentage
bd.pts: Average percentage of patients at the OBD
od.pts: Average percentage of patients at the favorable doses
earlystop: Percentage of early stopped trials
overdose: Overdose patients percentage
poorall: Poor allocation percentage
ov.sel: Overdose selection percentage

Examples

oc_ji3p3(
  ndose = 5,
  target_t = 0.3,
  target_e = 0.35,
  lower_e = 0.4,
  ntrial = 10,
)
oc_ji3p3(
  ndose = 5,
  target_t = 0.3,
  target_e = 0.35,
  lower_e = 0.4,
  ntrial = 10,
)

Compute operating characteristics using PRINTE

Description

oc_pite() uses the PRINTE design to compute operating charateristics of a user-specificed trial scenario. This design maps toxicity and efficacy intervals onto a decision table, forming 16 equal-area regions.

Usage

oc_pite(
  ndose,
  target_t,
  target_e,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  eps1 = 0.05,
  eps2 = 0.05,
  psafe = 0.95,
  pfutility = 0.95,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)
oc_pite(
  ndose,
  target_t,
  target_e,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  eps1 = 0.05,
  eps2 = 0.05,
  psafe = 0.95,
  pfutility = 0.95,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)

Arguments

ndose

Integer. Number of dose levels. (Required)

target_t

Numeric. Target toxicity probability. (Required)

target_e

Numeric. Target efficacy probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

ncohort

Integer. Number of cohorts. (Default is 10)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

OBD

Integer. True index of the Optimal Biological Dose (OBD) for the trial scenario. (Default is 0)

If set to 0: Random OBD will be selected.
Other: Treat this argument as the true OBD.

eps1

Numerical. Width of the subrectangle. (Default is '0.05')

eps2

Numerical. Width of the subreactangle. (Default is '0.05')

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.95)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list with the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

Value

A list containing operating characteristics such as:

bd.sel: OBD selection percentage
od.sel: Favorable dose selection percentage
bd.pts: Average percentage of patients at the OBD
od.pts: Average percentage of patients at the favorable doses
earlystop: Percentage of early stopped trials
overdose: Overdose patients percentage
poorall: Poor allocation percentage
ov.sel: Overdose selection percentage

Examples

oc_pite(
  ndose = 5,
  target_t = 0.3,
  target_e = 0.35,
  lower_e = 0.4,
  ntrial = 10,
)
oc_pite(
  ndose = 5,
  target_t = 0.3,
  target_e = 0.35,
  lower_e = 0.4,
  ntrial = 10,
)

Compute operating characteristics using STEIN

Description

oc_stein() uses the STEIN design to compute operating charateristics of a user-specificed trial scenario. This design uses target toxicity and efficacy rates separately to form the cutoff intervals within a decision map.

Usage

oc_stein(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  psi1 = 0.2,
  psi2 = 0.6,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)
oc_stein(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  psi1 = 0.2,
  psi2 = 0.6,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)

Arguments

ndose

Integer. Number of dose levels. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

ncohort

Integer. Number of cohorts. (Default is 10)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

OBD

Integer. True index of the Optimal Biological Dose (OBD) for the trial scenario. (Default is 0)

If set to 0: Random OBD will be selected.
Other: Treat this argument as the true OBD.

psi1

Numerical. Highest inefficacious efficacy probability.

psi2

Numerical. Lowest highly-promising efficacy probability.

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.95)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list of the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

Value

A list containing operating characteristics such as:

bd.sel: OBD selection percentage
od.sel: Favorable dose selection percentage
bd.pts: Average percentage of patients at the OBD
od.pts: Average percentage of patients at the favorable doses
earlystop: Percentage of early stopped trials
overdose: Overdose patients percentage
poorall: Poor allocation percentage
ov.sel: Overdose selection percentage

Examples

oc_stein(
  ndose = 5,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)
oc_stein(
  ndose = 5,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)

Compute operating characteristics using TEPI

Description

oc_tepi() uses the TEPI design to compute operating charateristics of a user-specificed trial scenario. This design maps toxicity and efficacy intervals onto a decision table, forming 16 regions.

Usage

oc_tepi(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  effint_l = c(0, lower_e, lower_e + 0.2, lower_e + 0.4),
  effint_u = c(lower_e, lower_e + 0.2, lower_e + 0.4, 1),
  toxint_l = c(0, 0.15, target_t, target_t + 0.05),
  toxint_u = c(0.15, target_t, target_t + 0.05, 1),
  psafe = 0.95,
  pfutility = 0.95,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)
oc_tepi(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  effint_l = c(0, lower_e, lower_e + 0.2, lower_e + 0.4),
  effint_u = c(lower_e, lower_e + 0.2, lower_e + 0.4, 1),
  toxint_l = c(0, 0.15, target_t, target_t + 0.05),
  toxint_u = c(0.15, target_t, target_t + 0.05, 1),
  psafe = 0.95,
  pfutility = 0.95,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)

Arguments

ndose

Integer. Number of dose levels. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

ncohort

Integer. Number of cohorts. (Default is 10)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

OBD

Integer. True index of the Optimal Biological Dose (OBD) for the trial scenario. (Default is 0)

If set to 0: Random OBD will be selected.
Other: Treat this argument as the true OBD.

effint_l

Lower efficacy bounds for dose assignment decision table. (Default is c(0,lower_e,lower_e+0.2,lower_e+0.4))

effint_u

Lower efficacy bounds for dose assignment decision table. (Default is c(lower_e,lower_e+0.2,lower_e+0.4,1))

toxint_l

Lower toxicity bounds for dose assignment decision table. (Default is c(0,0.15,target_t,target_t+0.05))

toxint_u

Lower toxicity bounds for dose assignment decision table. (Default is c(0.15,target_t,target_t+0.05,1))

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.95)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list of the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

Value

A list containing operating characteristics such as:

bd.sel: OBD selection percentage
od.sel: Favorable dose selection percentage
bd.pts: Average percentage of patients at the OBD
od.pts: Average percentage of patients at the favorable doses
earlystop: Percentage of early stopped trials
overdose: Overdose patients percentage
poorall: Poor allocation percentage
ov.sel: Overdose selection percentage

Examples

oc_tepi(
  ndose = 5,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)
oc_tepi(
  ndose = 5,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)

Compute operating characteristics using uTPI

Description

oc_utpi() uses the uTPI design to compute operating charateristics of a user-specificed trial scenario. This design places significance on optimizing utility using a quasi-binomial likelihood approach.

Usage

oc_utpi(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)
oc_utpi(
  ndose,
  target_t,
  lower_e,
  ncohort = 10,
  cohortsize = 3,
  startdose = 1,
  OBD = 0,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL
)

Arguments

ndose

Integer. Number of dose levels. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

ncohort

Integer. Number of cohorts. (Default is 10)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

OBD

Integer. True index of the Optimal Biological Dose (OBD) for the trial scenario. (Default is 0)

If set to 0: Random OBD will be selected.
Other: Treat this argument as the true OBD.

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.95)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list with the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

Value

A list containing operating characteristics such as:

bd.sel: OBD selection percentage
od.sel: Favorable dose selection percentage
bd.pts: Average percentage of patients at the OBD
od.pts: Average percentage of patients at the favorable doses
earlystop: Percentage of early stopped trials
overdose: Overdose patients percentage
poorall: Poor allocation percentage
ov.sel: Overdose selection percentage

Examples

oc_utpi(
  ndose = 5,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)
oc_utpi(
  ndose = 5,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)

Simulate operating characteristics using BOIN12.

Description

This function runs simulations of the BOIN12 design by evaluating operating characteristics over a range of cohort sizes. For each dose level within the user-specified range, it performs multiple trials and saves the results to a corresponding file.

Usage

simulate_boin12(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "boin12_simulations",
  save_file = "boin12_simulation.csv"
)
simulate_boin12(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "boin12_simulations",
  save_file = "boin12_simulation.csv"
)

Arguments

ndose

Integer. Number of dose levels. (Required)

ssizerange

Integer vector. Range of number of cohorts to simulate. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.90)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list with the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

save_dir

Directory to save output folders. Default is tempdir().

save_folder

Folder name. (Default is "boin12_simulations")

save_file

File name. (Default is "boin12_simulation.csv")

Value

No return value, called for side effects

Examples

prob <- list(
  pE = c(0.4, 0.5, 0.6),
  pT = c(0.1, 0.2, 0.3),
  obd = 2,
  mtd = 2
)
simulate_boin12(
  ndose = 3,
  ssizerange = c(3, 5),
  target_t = 0.3,
  lower_e = 0.2,
  ntrial = 10,
  prob = prob,
)
prob <- list(
  pE = c(0.4, 0.5, 0.6),
  pT = c(0.1, 0.2, 0.3),
  obd = 2,
  mtd = 2
)
simulate_boin12(
  ndose = 3,
  ssizerange = c(3, 5),
  target_t = 0.3,
  lower_e = 0.2,
  ntrial = 10,
  prob = prob,
)

Simulate operating characteristics using BOINET

Description

This function runs simulations of the BOINET design by evaluating operating characteristics over a range of cohort sizes. For each dose level within the user-specified range, it performs multiple trials and saves the results to a corresponding file.

Usage

simulate_boinet(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "boinet_simulations",
  save_file = "boinet_simulation.csv"
)
simulate_boinet(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "boinet_simulations",
  save_file = "boinet_simulation.csv"
)

Arguments

ndose

Integer. Number of dose levels. (Required)

ssizerange

Integer vector. Range of number of cohorts to simulate. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.90)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list of the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

save_dir

Directory to save output folders. Default is tempdir().

save_folder

Folder name. (Default is "boin12_simulations")

save_file

File name. (Default is "boin12_simulation.csv")

Value

No return value, called for side effects

Examples

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)
simulate_boinet(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
  prob = prob,
)
prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)
simulate_boinet(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
  prob = prob,
)

Simulate operating characteristics using EffTox

Description

This function runs simulations of the EffTox design by evaluating operating characteristics over a range of cohort sizes. For each dose level within the user-specified range, it performs multiple trials and saves the results to a corresponding file.

Usage

simulate_efftox(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  startdose = 1,
  ntrial = 10000,
  utilitytype = 1,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "efftox_simulations",
  save_file = "efftox_simulation.csv"
)
simulate_efftox(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  startdose = 1,
  ntrial = 10000,
  utilitytype = 1,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "efftox_simulations",
  save_file = "efftox_simulation.csv"
)

Arguments

ndose

Integer. Number of dose levels. (Required)

ssizerange

Integer vector. Range of number of cohorts to simulate. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

startdose

Integer. Starting dose level. (Default is 1)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list of the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

save_dir

Directory to save output folders. Default is tempdir().

save_folder

Folder name. (Default is "boin12_simulations")

save_file

File name. (Default is "boin12_simulation.csv")

Value

No return value, called for side effects

Examples

prob <- list(
  pE = c(0.4, 0.5),
  pT = c(0.1, 0.2),
  obd = 2,
  mtd = 2
)
simulate_efftox(
  ndose = 2,
  ssizerange = 1,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 2,
  prob = prob,
)
prob <- list(
  pE = c(0.4, 0.5),
  pT = c(0.1, 0.2),
  obd = 2,
  mtd = 2
)
simulate_efftox(
  ndose = 2,
  ssizerange = 1,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 2,
  prob = prob,
)

Simulate operating characteristics using Ji3+3

Description

This function runs simulations of the Ji3+3 design by evaluating operating characteristics over a range of cohort sizes. For each dose level within the user-specified range, it performs multiple trials and saves the results to a corresponding file.

Usage

simulate_ji3p3(
  ndose,
  ssizerange,
  target_t,
  target_e,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  eps1 = 0.05,
  eps2 = 0.05,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "ji3p3_simulations",
  save_file = "ji3p3_simulation.csv"
)
simulate_ji3p3(
  ndose,
  ssizerange,
  target_t,
  target_e,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  eps1 = 0.05,
  eps2 = 0.05,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "ji3p3_simulations",
  save_file = "ji3p3_simulation.csv"
)

Arguments

ndose

Integer. Number of dose levels. (Required)

ssizerange

Integer vector. Range of number of cohorts to simulate. (Required)

target_t

Numeric. Target toxicity probability. (Required)

target_e

Numeric. Target efficacy probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

eps1

Numerical. Width of the subrectangle. (Default is '0.05')

eps2

Numerical. Width of the subreactangle. (Default is '0.05')

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.90)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list of the following named elements: Use this parameter to provide fixed probability vectors as a list with the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

save_dir

Directory to save output folders. Default is tempdir().

save_folder

Folder name. (Default is "boin12_simulations")

save_file

File name. (Default is "boin12_simulation.csv")

Value

No return value, called for side effects

Examples

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)
simulate_ji3p3(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  target_e = 0.5,
  lower_e = 0.4,
  ntrial = 10,
  prob = prob,
)
prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)
simulate_ji3p3(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  target_e = 0.5,
  lower_e = 0.4,
  ntrial = 10,
  prob = prob,
)

Simulate operating characteristics using PRINTE

Description

This function runs simulations of the PRINTE design by evaluating operating characteristics over a range of cohort sizes. For each dose level within the user-specified range, it performs multiple trials and saves the results to a corresponding file.

Usage

simulate_pite(
  ndose,
  ssizerange,
  target_t,
  target_e,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  eps1 = 0.05,
  eps2 = 0.05,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "pite_simulations",
  save_file = "pite_simulation.csv"
)
simulate_pite(
  ndose,
  ssizerange,
  target_t,
  target_e,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  eps1 = 0.05,
  eps2 = 0.05,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "pite_simulations",
  save_file = "pite_simulation.csv"
)

Arguments

ndose

Integer. Number of dose levels. (Required)

ssizerange

Integer vector. Range of number of cohorts to simulate. (Required)

target_t

Numeric. Target toxicity probability. (Required)

target_e

Numeric. Target efficacy probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

eps1

Numerical. Width of the subrectangle.

eps2

Numerical. Width of the subreactangle.

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.90)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list with the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

save_dir

Directory to save output folders. Default is tempdir().

save_folder

Folder name. (Default is "boin12_simulations")

save_file

File name. (Default is "boin12_simulation.csv")

Value

No return value, called for side effects

Examples

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)
simulate_pite(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  target_e = 0.5,
  lower_e = 0.4,
  ntrial = 10,
  prob = prob,
)
prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)
simulate_pite(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  target_e = 0.5,
  lower_e = 0.4,
  ntrial = 10,
  prob = prob,
)

Simulate operating characteristics using STEIN

Description

This function runs simulations of the STEIN design by evaluating operating characteristics over a range of cohort sizes. For each dose level within the user-specified range, it performs multiple trials and saves the results to a corresponding file.

Usage

simulate_stein(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  psi1 = 0.2,
  psi2 = 0.6,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "stein_simulations",
  save_file = "stein_simulation.csv"
)
simulate_stein(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  psi1 = 0.2,
  psi2 = 0.6,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "stein_simulations",
  save_file = "stein_simulation.csv"
)

Arguments

ndose

Integer. Number of dose levels. (Required)

ssizerange

Integer vector. Range of number of cohorts to simulate. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

psi1

Numerical. Highest inefficacious efficacy probability.

psi2

Numerical. Lowest highly-promising efficacy probability.

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.90)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list with the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

save_dir

Directory to save output folders. Default is tempdir().

save_folder

Folder name. (Default is "boin12_simulations")

save_file

File name. (Default is "boin12_simulation.csv")

Value

No return value, called for side effects

Examples

simulate_stein(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)
simulate_stein(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)

Simulate operating characteristics using TEPI

Description

This function runs simulations of the TEPI design by evaluating operating characteristics over a range of cohort sizes. For each dose level within the user-specified range, it performs multiple trials and saves the results to a corresponding file.

Usage

simulate_tepi(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  effint_l = c(0, lower_e, lower_e + 0.2, lower_e + 0.4),
  effint_u = c(lower_e, lower_e + 0.2, lower_e + 0.4, 1),
  toxint_l = c(0, 0.15, target_t, target_t + 0.05),
  toxint_u = c(0.15, target_t, target_t + 0.05, 1),
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "tepi_simulations",
  save_file = "tepi2_simulation.csv"
)
simulate_tepi(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  effint_l = c(0, lower_e, lower_e + 0.2, lower_e + 0.4),
  effint_u = c(lower_e, lower_e + 0.2, lower_e + 0.4, 1),
  toxint_l = c(0, 0.15, target_t, target_t + 0.05),
  toxint_u = c(0.15, target_t, target_t + 0.05, 1),
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "tepi_simulations",
  save_file = "tepi2_simulation.csv"
)

Arguments

ndose

Integer. Number of dose levels. (Required)

ssizerange

Integer vector. Range of number of cohorts to simulate. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

effint_l

Lower efficacy bounds for dose assignment decision table. (Default is c(0,lower_e,lower_e+0.2,lower_e+0.4))

effint_u

Lower efficacy bounds for dose assignment decision table. (Default is c(lower_e,lower_e+0.2,lower_e+0.4,1))

toxint_l

Lower toxicity bounds for dose assignment decision table. (Default is c(0,0.15,target_t,target_t+0.05))

toxint_u

Lower toxicity bounds for dose assignment decision table. (Default is c(0.15,target_t,target_t+0.05,1))

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.90)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list with the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

save_dir

Directory to save output folders. Default is tempdir().

save_folder

Folder name. (Default is "boin12_simulations")

save_file

File name. (Default is "boin12_simulation.csv")

Value

No return value, called for side effects

Examples

simulate_tepi(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)
simulate_tepi(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)

Simulate operating characteristics using uTPI

Description

This function runs simulations of the uTPI design by evaluating operating characteristics over a range of cohort sizes. For each dose level within the user-specified range, it performs multiple trials and saves the results to a corresponding file.

Usage

simulate_utpi(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "utpi_simulations",
  save_file = "utpi_simulation.csv"
)
simulate_utpi(
  ndose,
  ssizerange,
  target_t,
  lower_e,
  cohortsize = 3,
  startdose = 1,
  psafe = 0.95,
  pfutility = 0.9,
  ntrial = 10000,
  utilitytype = 1,
  u1,
  u2,
  prob = NULL,
  save_dir = tempdir(),
  save_folder = "utpi_simulations",
  save_file = "utpi_simulation.csv"
)

Arguments

ndose

Integer. Number of dose levels. (Required)

ssizerange

Integer vector. Range of number of cohorts to simulate. (Required)

target_t

Numeric. Target toxicity probability. (Required)

lower_e

Numeric. Minimum acceptable efficacy probability. (Required)

cohortsize

Integer. Size of a cohort. (Default is 3)

startdose

Integer. Starting dose level. (Default is 1)

psafe

Numeric. Early stopping cutoff for toxicity. (Default is 0.95)

pfutility

Numeric. Early stopping cutoff for efficacy. (Default is 0.90)

ntrial

Integer. Number of random trial replications. (Default is 10000)

utilitytype

Integer. Type of utility structure. (Default is 1)

If set to 1: Use preset weights (w11 = 0.6, w00 = 0.4)
If set to 2: Use (w11 = 1, w00 = 0)
Other: Use user-specified values from u1 and u2.

u1

Numeric. Utility parameter w_11. (0-100)

u2

Numeric. Utility parameter w_00. (0-100)

prob

Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list with the following named elements:

pE: Numeric vector of efficacy probabilities for each dose level.
pT: Numeric vector of toxicity probabilities for each dose level.
obd: Integer indicating the index of the true Optimal Biological Dose (OBD).
mtd: Integer indicating the index of the true Maximum Tolerated Dose (MTD).

For example:

prob <- list(
  pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
  pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
  obd = 3,
  mtd = 2
)

save_dir

Directory to save output folders. Default is tempdir().

save_folder

Folder name. (Default is "boin12_simulations")

save_file

File name. (Default is "boin12_simulation.csv")

Value

No return value, called for side effects

Examples

simulate_utpi(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)
simulate_utpi(
  ndose = 5,
  ssizerange = 1:2,
  target_t = 0.3,
  lower_e = 0.4,
  ntrial = 10,
)

Package 'phase12designs'

Help Index

Decision map plot

Description

Usage

Arguments

Value

Examples

Compute operating characteristics using BOIN12

Description

Usage

Arguments

Value

Examples

Compute operating characteristics using BOINET

Description

Usage

Arguments

Value

Examples

Compute operating characteristics using EffTox

Description

Usage

Arguments

Value

Examples

Compute operating characteristics using Ji3+3

Description

Usage

Arguments

Value

Examples

Compute operating characteristics using PRINTE

Description

Usage

Arguments

Value

Examples

Compute operating characteristics using STEIN

Description

Usage

Arguments

Value

Examples

Compute operating characteristics using TEPI

Description

Usage

Arguments

Value

Examples

Compute operating characteristics using uTPI

Description

Usage

Arguments

Value

Examples

Simulate operating characteristics using BOIN12.

Description

Usage

Arguments

Value

Examples

Simulate operating characteristics using BOINET

Description

Usage

Arguments

Value

Examples

Simulate operating characteristics using EffTox

Description

Usage

Arguments

Value

Examples

Simulate operating characteristics using Ji3+3

Description

Usage

Arguments

Value

Examples