An R Package Unified Dose Finding for Continuous and Ordinal Outcomes in Phase I Dose-Finding Trials

Traditional dose-finding designs are substantially inefficient for targeted agents and cancer immunotherapies by failing to incorporate efficacy signals, mild and moderate adverse events, and late, cumulative toxicities. However, the lack of user-friendly software is a barrier to the practical use of the novel phase I designs, despite their demonstrated superiority of traditional 3+3 designs. To overcome these barriers, we present an R package, phase1RMD, which provides a comprehensive implementation of novel designs with repeated toxicity measures and early efficacy. A novel phase I repeated measures design that used a continuous toxicity score from multiple treatment cycles was implemented. Furthermore, in studies where preliminary efficacy is evaluated, an adaptive, multi-stage design to identify the most efficacious dose with acceptable toxicity was demonstrated. Functions are provided to recommend the next dose based on the data collected in a phase I trial, as well as to assess trial characteristics given design parameters via simulations. The repeated measure designs accurately estimated both the magnitude and direction of toxicity trends in late treatment cycles, and allocated more patients at therapeutic doses. The R package for implementing these designs is available from the Comprehensive R Archive Network. To our best knowledge, this is the first software that implement novel phase I dose-finding designs that simultaneously accounts for the multiple-grade toxicity events over multiple treatment cycles and a continuous early efficacy outcome. With the software published on CRAN, we will pursue the implementation of these designs in phase I trials in real-life settings.

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Keyboard: An R Package Suite for Early Phase Dose-finding Designs

10.21203/rs.3.rs-400107/v1 ◽

2021 ◽

Author(s):

Hongying Sun ◽

Chen Li ◽

Cheng Cheng ◽

Tang Li ◽

Haitao Pan

Keyword(s):

Phase I ◽

Drug Combination ◽

Single Agent ◽

Optimal Dose ◽

R Package ◽

Maximum Tolerated Dose ◽

Cytotoxic Agents ◽

Dose Finding ◽

Operating Characteristics ◽

Background Phase

Abstract Background: Phase I and/or I/II oncology trials are conducted to find the maximum tolerated dose (MTD) and/or optimal biological dose (OBD) of a new drug or treatment. In these trials, for cytotoxic agents, the primary aim of the single-agent or drug-combination is to find the MTD with a certain target toxicity rate, while for the cytostatic agents, a more appropriate target is the OBD, which is often defined by consideration of toxicity and efficacy simultaneously. However, there still lacks accessible software packages to achieve both yet. Results: Objective of this work is to develop a software package that can provide tools for both MTD- and OBD-finding trials, which implements the Keyboard design for single-agent MTD-finding trials by Yan et al., the Keyboard design for drug-combination MTD-finding trials by Pan et al., and phase I/II OBD-finding method by Li et al., in a single R package, called Keyboard. For each of the designs, the Keyboard package provides corresponding functions that begins with get.boundary( . . . ) to determine the optimal dose escalation and de-escalation boundaries, that begins with select.mtd( . . . ) to select the MTD when the trial is completed, that begins with select.obd( . . . ) to select the OBD at the end of a trial, and that begins with get.oc( . . . ) to generate the operating characteristics. Conclusions: The developed Keyboard R package provides convenient tools for designing, conducting and analyzing single-agent, drug-combination and phase I/II dose-finding trials, which supports Bayesian designs of innovative dose-finding studies.

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42P Using patient-reported outcomes (PROs) in phase I/II dose-finding oncology trials (DPOT): A global survey

Annals of Oncology ◽

10.1016/j.annonc.2021.01.057 ◽

2021 ◽

Vol 32 ◽

pp. S17

Author(s):

J.E. Lai-Kwon ◽

A. Vanderbeek ◽

A. Minchom ◽

C. Yap

Keyword(s):

Phase I ◽

Patient Reported Outcomes ◽

Dose Finding ◽

Global Survey ◽

Patient Reported

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A Bayesian dose-finding design for outcomes evaluated with uncertainty

Clinical Trials ◽

10.1177/17407745211001521 ◽

2021 ◽

pp. 174077452110015

Author(s):

Matthew J Schipper ◽

Ying Yuan ◽

Jeremy MG Taylor ◽

Randall K Ten Haken ◽

Christina Tsien ◽

...

Keyword(s):

Phase I ◽

Phase I Trial ◽

Data Augmentation ◽

Maximum Tolerated Dose ◽

Dose Finding ◽

Continual Reassessment Method ◽

Number Of Patients ◽

Continual Reassessment ◽

Partially Observed ◽

Dose Limiting Toxicity

Introduction: In some phase I trial settings, there is uncertainty in assessing whether a given patient meets the criteria for dose-limiting toxicity. Methods: We present a design which accommodates dose-limiting toxicity outcomes that are assessed with uncertainty for some patients. Our approach could be utilized in many available phase I trial designs, but we focus on the continual reassessment method due to its popularity. We assume that for some patients, instead of the usual binary dose-limiting toxicity outcome, we observe a physician-assessed probability of dose-limiting toxicity specific to a given patient. Data augmentation is used to estimate the posterior probabilities of dose-limiting toxicity at each dose level based on both the fully observed and partially observed patient outcomes. A simulation study is used to assess the performance of the design relative to using the continual reassessment method on the true dose-limiting toxicity outcomes (available in simulation setting only) and relative to simple thresholding approaches. Results: Among the designs utilizing the partially observed outcomes, our proposed design has the best overall performance in terms of probability of selecting correct maximum tolerated dose and number of patients treated at the maximum tolerated dose. Conclusion: Incorporating uncertainty in dose-limiting toxicity assessment can improve the performance of the continual reassessment method design.

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