adaptDesign_seamless: Adaptive Phase 2/3 Seamless Design

In lrstat: Power and Sample Size Calculation for Non-Proportional Hazards and Beyond

Adaptive Phase 2/3 Seamless Design

Description

Calculates the conditional power for specified incremental information, given the interim results, parameter value, data-dependent changes in the error spending function, and the number and spacing of interim looks. Conversely, calculates the incremental information required to attain a specified conditional power, given the interim results, parameter value, data-dependent changes in the error spending function, and the number and spacing of interim looks.

Usage

adaptDesign_seamless(
  betaNew = NA_real_,
  INew = NA_real_,
  M = NA_integer_,
  r = 1,
  corr_known = TRUE,
  L = NA_integer_,
  zL = NA_real_,
  theta = NA_real_,
  IMax = NA_real_,
  K = NA_integer_,
  informationRates = NA_real_,
  efficacyStopping = NA_integer_,
  futilityStopping = NA_integer_,
  criticalValues = NULL,
  alpha = 0.025,
  typeAlphaSpending = "sfOF",
  parameterAlphaSpending = NA_real_,
  userAlphaSpending = NA_real_,
  futilityBounds = NULL,
  futilityCP = NULL,
  futilityTheta = NULL,
  spendingTime = NA_real_,
  MullerSchafer = FALSE,
  kNew = NA_integer_,
  informationRatesNew = NA_real_,
  efficacyStoppingNew = NA_integer_,
  futilityStoppingNew = NA_integer_,
  typeAlphaSpendingNew = "sfOF",
  parameterAlphaSpendingNew = NA_real_,
  futilityBoundsInt = NULL,
  futilityCPInt = NULL,
  futilityThetaInt = NULL,
  typeBetaSpendingNew = "none",
  parameterBetaSpendingNew = NA_real_,
  userBetaSpendingNew = NA_real_,
  spendingTimeNew = NA_real_
)

Arguments

betaNew	The type II error for the secondary trial.
INew	The maximum information for the active arm versus the common control in the secondary trial. Either betaNew or INew should be provided, while the other must be missing.
M	Number of active treatment arms in Phase 2.
r	Randomization ratio of each active arm to the common control in Phase 2.
corr_known	Logical. If TRUE, the correlation between Wald statistics in Phase 2 is derived from the randomization ratio r as r / (r + 1). If FALSE, a conservative correlation of 0 is used.
L	The interim adaptation look in Phase 3.
zL	The z-test statistic at the interim adaptation look of Phase 3.
theta	The assumed treatment effect for the selected arm versus the common control.
IMax	Maximum information for the active arm versus the common control for the original trial. Must be provided.
K	Number of sequential looks in Phase 3.
informationRates	A numeric vector of information rates fixed before the trial. If unspecified, defaults to (1:(K+1)) / (K+1).
efficacyStopping	Indicators of whether efficacy stopping is allowed at each stage of the primary trial. Defaults to TRUE if left unspecified.
futilityStopping	Indicators of whether futility stopping is allowed at each stage of the primary trial. Defaults to TRUE if left unspecified.
criticalValues	The upper boundaries on the max z-test statistic scale for Phase 2 and the z-test statistics for the selected arm in Phase 3 for the primary trial. If missing, boundaries will be computed based on the specified alpha spending function.
alpha	The significance level of the primary trial. Defaults to 0.025.
typeAlphaSpending	The type of alpha spending for the primary trial. One of the following: "OF" for O'Brien-Fleming boundaries, "P" for Pocock boundaries, "WT" for Wang & Tsiatis boundaries, "sfOF" for O'Brien-Fleming type spending function, "sfP" for Pocock type spending function, "sfKD" for Kim & DeMets spending function, "sfHSD" for Hwang, Shi & DeCani spending function, "user" for user defined spending, and "none" for no early efficacy stopping. Defaults to "sfOF".
parameterAlphaSpending	The parameter value of alpha spending for the primary trial. Corresponds to \Delta for "WT", \rho for "sfKD", and \gamma for "sfHSD".
userAlphaSpending	The user-defined alpha spending for the primary trial. Represents the cumulative alpha spent up to each stage.
futilityBounds	The lower boundaries on the max-z statistic scale at end of phase 2 and the z-test statistic scale in phase 3 for futility stopping for the primary trial. Defaults to rep(-8, kMax-1) if left unspecified.
futilityCP	The conditional power-based futility bounds for the primary trial.
futilityTheta	The parameter value-based futility bounds for the primary trial.
spendingTime	The error spending time of the primary trial. Defaults to missing, in which case it is assumed to be the same as informationRates.
MullerSchafer	Whether to use the Muller and Schafer (2001) method for trial adaptation.
kNew	The number of looks of the secondary trial.
informationRatesNew	The spacing of looks of the secondary trial.
efficacyStoppingNew	The indicators of whether efficacy stopping is allowed at each look of the secondary trial. Defaults to TRUE if left unspecified.
futilityStoppingNew	The indicators of whether futility stopping is allowed at each look of the secondary trial. Defaults to TRUE if left unspecified.
typeAlphaSpendingNew	The type of alpha spending for the secondary trial. One of the following: "OF" for O'Brien-Fleming boundaries, "P" for Pocock boundaries, "WT" for Wang & Tsiatis boundaries, "sfOF" for O'Brien-Fleming type spending function, "sfP" for Pocock type spending function, "sfKD" for Kim & DeMets spending function, "sfHSD" for Hwang, Shi & DeCani spending function, and "none" for no early efficacy stopping. Defaults to "sfOF".
parameterAlphaSpendingNew	The parameter value of alpha spending for the secondary trial. Corresponds to \Delta for "WT", \rho for "sfKD", and \gamma for "sfHSD".
futilityBoundsInt	The futility boundaries on the z statistic scale for new stages of the integrated trial.
futilityCPInt	The conditional power-based futility bounds for new stages of the integrated trial.
futilityThetaInt	The parameter value-based futility bounds for the new stages of the integrated trial.
typeBetaSpendingNew	The type of beta spending for the secondary trial. One of the following: "sfOF" for O'Brien-Fleming type spending function, "sfP" for Pocock type spending function, "sfKD" for Kim & DeMets spending function, "sfHSD" for Hwang, Shi & DeCani spending function, "user" for user defined spending, and "none" for no early futility stopping. Defaults to "none".
parameterBetaSpendingNew	The parameter value of beta spending for the secondary trial. Corresponds to \rho for "sfKD", and \gamma for "sfHSD".
userBetaSpendingNew	The user-defined cumulative beta spending. Represents the cumulative beta spent up to each stage of the secondary trial.
spendingTimeNew	The error spending time of the secondary trial. Defaults to missing, in which case it is assumed to be the same as informationRatesNew.

Value

An adaptDesign_seamless object with three list components:

• primaryTrial: A list of selected information for the primary trial, including M, r, corr_known, K, L, zL, theta, maxInformation, kMax, informationRates, efficacyBounds, futilityBounds, information, alpha, conditionalAlpha, conditionalPower, and MullerSchafer.

• secondaryTrial: A list of selected information for the seconary trial, including overallReject, alpha, kMax, maxInformation, informationRates, efficacyBounds, futilityBounds, cumulativeRejection, cumulativeFutility, cumulativeAlphaSpent, information, typeAlphaSpending, parameterAlphaSpending, typeBetaSpending, parameterBetaSpending, userBetaSpending, and spendingTime.

• integratedTrial: A list of selected information for the integrated trial, including M, r, corr_known, K, L, zL, theta, maxInformation, kMax, informationRates, efficacyBounds, futilityBounds, and information.

Author(s)

Kaifeng Lu, [e-mail]

References

Ping Gao, Yingqiu Li. Adaptive two-stage seamless sequential design for clinical trials. Journal of Biopharmaceutical Statistics, 2025, 35(4), 565-587.

See Also

getDesign_seamless

Examples

(des1 <- adaptDesign_seamless(
  betaNew = 0.1, M = 2, r = 1, corr_known = FALSE,
  L = 1, zL = -log(0.67) * sqrt(80 / 4), theta = -log(0.691),
  IMax = 120 / 4, K = 2, informationRates = c(1/3, 2/3, 1),
  alpha = 0.025, typeAlphaSpending = "OF", kNew = 1))

lrstat documentation built on May 13, 2026, 9:06 a.m.