uTPI: A utility‐based toxicity probability interval design for phase I/II dose‐finding trials

2021 ◽  
Author(s):  
Haolun Shi ◽  
Jiguo Cao ◽  
Ying Yuan ◽  
Ruitao Lin
2021 ◽  
pp. 096228022110527
Author(s):  
Zichun Xu ◽  
Xiaolei Lin

Late-onset toxicities often occur in phase I trials investigating novel immunotherapy and molecular targeted therapies. For trials with cohort based designs (such as modified toxicity probability interval, Bayesian optimal interval, and i3+3), patients are often turned away since the current cohort are still being followed without definite dose-limiting toxicities, which results in prolonged trial duration and waste of patient resources. In this paper, we incorporate a probability-of-decision framework into the i3+3 design and allow real-time dosing inference when the next patient becomes available. Both follow-up time for the pending patients and time to dose-limiting toxicities for the observed patients are used in calculating the posterior probability of each possible dosing decision. An intensive simulation study is conducted to evaluate the operating characteristics of the newly proposed probability-of-decision-i3+3 design under various dosing scenarios and patient accrual settings. Results show that the probability-of-decision-i3+3 design achieves comparable safety and reliability performances but much shorter trial duration compared to the complete designs.


2021 ◽  
pp. 174077452110015
Author(s):  
Matthew J Schipper ◽  
Ying Yuan ◽  
Jeremy MG Taylor ◽  
Randall K Ten Haken ◽  
Christina Tsien ◽  
...  

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.


Author(s):  
Georgios E. Christakopoulos ◽  
Todd E. DeFor ◽  
Stefanie Hage ◽  
John E. Wagner ◽  
Michael A. Linden ◽  
...  

2014 ◽  
Vol 20 (14) ◽  
pp. 3683-3691 ◽  
Author(s):  
Donald W. Northfelt ◽  
Ramesh K. Ramanathan ◽  
Peter A. Cohen ◽  
Daniel D. Von Hoff ◽  
Glen J. Weiss ◽  
...  

2003 ◽  
Vol 1 (5) ◽  
pp. S174-S175
Author(s):  
D. Zingel ◽  
C. Bolling ◽  
T. Graefe ◽  
D. Radtke ◽  
J. Latz ◽  
...  

2015 ◽  
Vol 34 (24) ◽  
pp. 3194-3213 ◽  
Author(s):  
Akihiro Hirakawa ◽  
Nolan A. Wages ◽  
Hiroyuki Sato ◽  
Shigeyuki Matsui

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