A product of independent beta probabilities dose escalation design for dual‐agent phase I trials

Mander, Adrian P.; Sweeting, Michael

doi:10.1002/sim.6434

Cited by 70 publications

(111 citation statements)

References 22 publications

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“…Hence, many strategies for exploring the space of dose combinations safely are possible and not one algorithm described in the literature seems to perform uniformly better than the others in estimating the maximum tolerated dose. In general, parametric model based designs that link the dose combination-toxicity relationship described in [4–13], the partial ordering approach [14,15], and nonparameteric method [16] all proceed by treating successive cohorts of patients with dose escalation starting from the lowest dose combination and the model parameters and estimated probabilities of toxicities sequentially updated. Dose allocation to the next cohort proceeds by using variations of the continual reassessment method (CRM) ([17–21]) or escalation with overdose control (EWOC)([22–30]).…”

Section: Introductionmentioning

confidence: 99%

Dose Finding for Drug Combination in Early Cancer Phase I Trials Using Conditional Continual Reassessment Method

2017

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We describe a dose escalation algorithm for drug combinations in cancer phase I clinical trials. Parametric models for describing the association between the doses and the probability of dose limiting toxicity are used assuming univariate monotonicity of the dose-toxicity relationship. Trial design proceeds using the continual reassessment method, where at each stage of the trial, we seek the dose of one agent with estimated probability of toxicity closest to a target probability of toxicity given the current dose of the other agent. A Bayes estimate of the maximum tolerated dose (MTD) curve is proposed at the conclusion of the trial for continuous doses or a set of MTDs is determined in the case of discrete dose levels. We evaluate design operating characteristics in terms of safety of the trial and percent of dose recommendation at dose combination neighborhoods around the true MTD under various model generated scenarios and misspecification. The method is further assessed for varying algorithms enrolling cohorts of two and three patients receiving different doses and compared to previous approaches such as escalation with overdose control and two-dimensional design.

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Section: Introductionmentioning

confidence: 99%

Dose Finding for Drug Combination in Early Cancer Phase I Trials Using Conditional Continual Reassessment Method

2017

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“…In the case where multiple dose combinations are equally close to the TTL on the probability scale (call this set

scriptC

), one may use weighted randomization to choose a dose combination , where each dose combination selection probability is weighted by

n_{c}^{- 1}

, the inverse of the number of patients treated at each candidate combination

c \in scriptC

, that is,

double-struckP ((), Next cohort given ((), a_{j}, b_{k}) | ((), a_{j}, b_{k}) \in scriptC) = \frac{n_{jk}^{- 1}}{\sum_{c \in scriptC} n_{c}^{- 1}} .

…”

Section: Methodsmentioning

confidence: 99%

Modelling semi‐attributable toxicity in dual‐agent phase I trials with non‐concurrent drug administration

Wheeler

Sweeting

Mander

et al. 2016

Statistics in Medicine

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In oncology, combinations of drugs are often used to improve treatment efficacy and/or reduce harmful side effects. Dual‐agent phase I clinical trials assess drug safety and aim to discover a maximum tolerated dose combination via dose‐escalation; cohorts of patients are given set doses of both drugs and monitored to see if toxic reactions occur. Dose‐escalation decisions for subsequent cohorts are based on the number and severity of observed toxic reactions, and an escalation rule. In a combination trial, drugs may be administered concurrently or non‐concurrently over a treatment cycle. For two drugs given non‐concurrently with overlapping toxicities, toxicities occurring after administration of the first drug yet before administration of the second may be attributed directly to the first drug, whereas toxicities occurring after both drugs have been given some present ambiguity; toxicities may be attributable to the first drug only, the second drug only or the synergistic combination of both. We call this mixture of attributable and non‐attributable toxicity semi‐attributable toxicity. Most published methods assume drugs are given concurrently, which may not be reflective of trials with non‐concurrent drug administration. We incorporate semi‐attributable toxicity into Bayesian modelling for dual‐agent phase I trials with non‐concurrent drug administration and compare the operating characteristics to an approach where this detail is not considered. Simulations based on a trial for non‐concurrent administration of intravesical Cabazitaxel and Cisplatin in early‐stage bladder cancer patients are presented for several scenarios and show that including semi‐attributable toxicity data reduces the number of patients given overly toxic combinations. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

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“…Multidimensional approaches, such as the proposed Product of Independent beta Probabilities dose Escalation (PIPE) design, could be used to identify the most promising combinations to take forward to phase II trials 67 . PIPE is an example of a non-parametric design for a dual agent clinical trial, in which the model parameters are the probabilities of toxicity for each of the dose combinations.…”

Section: Box 4 | Immuno-radio-oncologymentioning

confidence: 99%

Clinical development of new drug–radiotherapy combinations

et al. 2016

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A product of independent beta probabilities dose escalation design for dual‐agent phase I trials

Cited by 70 publications

References 22 publications

Dose Finding for Drug Combination in Early Cancer Phase I Trials Using Conditional Continual Reassessment Method

Dose Finding for Drug Combination in Early Cancer Phase I Trials Using Conditional Continual Reassessment Method

Modelling semi‐attributable toxicity in dual‐agent phase I trials with non‐concurrent drug administration

Clinical development of new drug–radiotherapy combinations

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