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Dose-Finding and Phase I/II Designs

Bayesian Dose-Escalation with Overdose Control (EWOC)

A classical single-agent Bayesian EWOC calculator. Given dose/DLT observations, it updates the posterior distribution of the maximum tolerated dose (MTD) and recommends the posterior α-quantile, explicitly controlling the posterior probability of assigning a dose above the MTD.

EWOC Design Parameters

Classical Kadane parameterization with uniform priors for the MTD and the DLT probability at the minimum dose.
Patients (dose, DLT status)

Recommended Dose

The continuous EWOC dose is the posterior α-quantile of the MTD. If a minimum dose increment is supplied, the dose is rounded down as in the EWOC software documentation.
Enter patient data and click Calculate EWOC Dose.

Methodology

EWOC (Escalation With Overdose Control) is a Bayesian adaptive dose-finding design introduced by Babb, Rogatko, and Zacks (1998). Its defining rule is to choose the next dose so that the posterior probability that the dose exceeds the MTD is the feasibility bound α. Thus, if the posterior MTD is Γ, the continuous recommendation xEWOC satisfies:

P(Γ ≤ xEWOC | data) = α
equivalently,   P(Γ > xEWOC | data) = 1 − α

Dose-toxicity model

The calculator uses the classical logistic model parameterized by ρ0, the DLT probability at Xmin, and Γ, the dose at which the DLT probability equals the target θ:

logit[p(x)] = β0 + β1x
β1 = {logit(θ) − logit(ρ0)} / (Γ − Xmin)
β0 = {\Gamma;·logit(ρ0) − Xmin·logit(θ)} / (Γ − Xmin)

The default priors follow the classical EWOC specification: Γ is uniform on [Xmin, Xmax] and ρ0 is uniform on (0, θ). The posterior is proportional to the Bernoulli likelihood times these priors. The calculator evaluates that posterior numerically on a two-dimensional grid and integrates over ρ0 to obtain the marginal posterior distribution of Γ.

Continuous and discrete doses

For a continuous dose, the displayed EWOC dose is the posterior α-quantile directly. When a positive minimum dose increment is entered, the continuous recommendation is rounded down to the nearest permitted increment, matching the documented EWOC treatment of discrete dose levels.

Important interpretation

Design scope: This page implements the classical single-agent EWOC model, not every EWOC variant. It does not replace the full MCMC implementation used by dedicated EWOC software for complex priors, covariates, time-to-event toxicity, drug combinations, or other extensions. The numerical grid is deterministic and browser-based, so results can differ slightly in the last decimal from an MCMC implementation.

References

Babb, J., Rogatko, A., & Zacks, S. (1998). Cancer phase I clinical trials: efficient dose escalation with overdose control. Statistics in Medicine, 17(10), 1103–1120. doi:10.1002/(SICI)1097-0258(19980530)17:10<1103::AID-SIM793>3.0.CO;2-9.

Zacks, S., Rogatko, A., & Babb, J. (1998). Optimal Bayesian-feasible dose escalation for cancer phase I trials. Statistics & Probability Letters, 38(3), 215–220.

Rogatko, A., Tighiouart, M., Cook-Wiens, G., & Li, Q. (2012). EWOC User Guide, Version 3.1. Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center.