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1.
Clin Trials ; 21(3): 267-272, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38570906

RESUMO

With the advent of targeted agents and immunological therapies, the medical research community has become increasingly aware that conventional methods for determining the best dose or schedule of a new agent are inadequate. It has been well established that conventional phase I designs cannot reliably identify safe and effective doses. This problem applies, generally, for cytotoxic agents, radiation therapy, targeted agents, and immunotherapies. To address this, the US Food and Drug Administration's Oncology Center of Excellence initiated Project Optimus, with the goal "to reform the dose optimization and dose selection paradigm in oncology drug development." As a response to Project Optimus, the articles in this special issue of Clinical Trials review recent advances in methods for choosing the dose or schedule of a new agent with an overall objective of informing clinical trialists of these innovative designs. This introductory article briefly reviews problems with conventional methods, the regulatory changes that encourage better dose optimization designs, and provides brief summaries of the articles that follow in this special issue.


Assuntos
Antineoplásicos , Relação Dose-Resposta a Droga , Projetos de Pesquisa , United States Food and Drug Administration , Humanos , Estados Unidos , Antineoplásicos/administração & dosagem , Neoplasias/tratamento farmacológico , Oncologia/métodos , Dose Máxima Tolerável , Ensaios Clínicos Fase I como Assunto/métodos , Desenvolvimento de Medicamentos/métodos
2.
Clin Trials ; 21(3): 331-339, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38554038

RESUMO

Combination therapy is increasingly being explored as a promising approach for improving cancer treatment outcomes. However, identifying effective dose combinations in early oncology drug development is challenging due to limited sample sizes in early-phase clinical trials. This task becomes even more complex when multiple agents are being escalated simultaneously, potentially leading to a loss of monotonic toxicity order with respect to the dose. Traditional single-agent trial designs are insufficient for this multi-dimensional problem, necessitating the development and implementation of dose-finding methods specifically designed for drug combinations. While, in practice, approaches to this problem have focused on preselecting combinations with a known toxicity order and applying single-agent designs, this limits the number of combinations considered and may miss promising dose combinations. In recent years, several novel designs have been proposed for exploring partially ordered drug combination spaces with the goal of identifying a maximum tolerated dose combination, based on safety, or an optimal dose combination, based on toxicity and efficacy. However, their implementation in clinical practice remains limited. In this article, we describe the application of the partial order continual reassessment method and its extensions for combination therapies in early-phase clinical trials. We present completed trials that use safety endpoints to identify maximum tolerated dose combinations and adaptively use both safety and efficacy endpoints to determine optimal treatment strategies. We discuss the effectiveness of the partial-order continual reassessment method and its extensions in identifying optimal treatment strategies and provide our experience with executing these novel adaptive designs in practice. By utilizing innovative dose-finding methods, researchers and clinicians can more effectively navigate the challenges of combination therapy development, ultimately improving patient outcomes in the treatment of cancer.


Assuntos
Protocolos de Quimioterapia Combinada Antineoplásica , Dose Máxima Tolerável , Neoplasias , Projetos de Pesquisa , Humanos , Neoplasias/tratamento farmacológico , Protocolos de Quimioterapia Combinada Antineoplásica/administração & dosagem , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Desenvolvimento de Medicamentos/métodos , Relação Dose-Resposta a Droga , Antineoplásicos/administração & dosagem , Antineoplásicos/uso terapêutico , Ensaios Clínicos como Assunto/métodos
3.
J Biopharm Stat ; 34(2): 151-163, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-36879525

RESUMO

Cell therapies comprise one of the most important advances in oncology. One of the biggest challenges in the early development of cell therapies is to recommend safe and feasible doses to carry forward to middle development. The treatment involves extracting cells from a patient, expanding the cells and infusing the cells back into the patient. Each dose level being studied is defined by the number of cells infused into the trial participant. The manufacturing process may not generate enough cells for a given patient to receive their assigned dose level, making it infeasible to administer their intended dose. The primary design challenge is to efficiently use accumulated data from participants treated away from their assigned dose to efficiently allocate future trial participants and recommend a feasible maximum tolerated dose (FMTD) at the study conclusion. Currently, there are few available options for designing and implementing Phase I trials of cell therapies that can incorporate a dose feasibility endpoint. Moreover, the application of these designs is limited to a traditional dose-finding framework, where the dose-limiting toxicity (DLT) endpoint is observed in early cycles of therapy. This paper presents a novel phase I trial design for adoptive cell therapy that simultaneously accounts for dose feasibility and late-onset toxicities. We apply our design to a phase I dose-escalation trial of Rituximab-based bispecific activated T-cells combined with a fixed dose of Nivolumab. Our simulation results demonstrate that our proposed method can reduce trial duration without significantly hindering trial accuracy.


Assuntos
Antineoplásicos , Neoplasias , Humanos , Antineoplásicos/toxicidade , Simulação por Computador , Relação Dose-Resposta a Droga , Estudos de Viabilidade , Imunoterapia Adotiva/efeitos adversos , Dose Máxima Tolerável , Oncologia , Neoplasias/tratamento farmacológico , Projetos de Pesquisa , Ensaios Clínicos como Assunto
4.
J Biopharm Stat ; 33(3): 357-370, 2023 05 04.
Artigo em Inglês | MEDLINE | ID: mdl-36606874

RESUMO

This article addresses the problem of identifying the maximum tolerated dose (MTD) in Phase I dose-finding clinical trials with late-onset toxicities. The main design challenge is how best to adaptively allocate study participants to tolerable doses when the evaluation window for the toxicity endpoint is long relative to the accrual rate of new participants. We propose a new design framework based on order-restricted statistical inference that addresses this challenge in sequential dose assignments. We illustrate the proposed method on real data from a Phase I trial of bortezomib in lymphoma patients and apply it to a Phase I trial of radiotherapy in prostate cancer patients. We conduct extensive simulation studies to compare our design's operating characteristics to existing published methods. Overall, our proposed design demonstrates good performance relative to existing methods in allocating participants at and around the MTD during the study and accurately recommending the MTD at the study conclusion.


Assuntos
Antineoplásicos , Neoplasias , Humanos , Antineoplásicos/efeitos adversos , Projetos de Pesquisa , Relação Dose-Resposta a Droga , Neoplasias/tratamento farmacológico , Neoplasias/induzido quimicamente , Bortezomib/efeitos adversos , Simulação por Computador , Dose Máxima Tolerável , Teorema de Bayes
5.
Stat Sin ; 32: 1983-2005, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36643072

RESUMO

We investigate a statistical framework for Phase I clinical trials that test the safety of two or more agents in combination. For such studies, the traditional assumption of a simple monotonic relation between dose and the probability of an adverse event no longer holds. Nonetheless, the dose toxicity (adverse event) relationship will obey an assumption of partial ordering in that there will be pairs of combinations for which the ordering of the toxicity probabilities is known. Some authors have considered how to best estimate the maximum tolerated dose (a dose providing a rate of toxicity as close as possible to some target rate) in this setting. A related, and equally interesting, problem is to partition the 2-dimensional dose space into two sub-regions: doses with probabilities of toxicity lower and greater than the target. We carry out a detailed investigation of this problem. The theoretical framework for this is the recently presented semiparametric dose finding method. This results in a number of proposals one of which can be viewed as an extension of the Product of Independent beta Priors Escalation method (PIPE). We derive useful asymptotic properties which also apply to the PIPE method when seen as a special case of the more general method given here. Simulation studies provide added confidence concerning the good behaviour of the operating characteristics.

6.
J Neurooncol ; 154(1): 41-47, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-34164780

RESUMO

INTRODUCTION: Venous thromboembolism (VTE) is a known complication of malignancy. While brain tumors in general predispose to VTE, the incidence in primary central nervous system lymphoma (PCNSL) is poorly characterized. We sought to characterize incidence, risk factors, management, and outcome of VTE in PCNSL METHOD: Retrospective study of 78 PCNSL patients from 2/1/2002 to 4/1/2020 at the University of Virginia RESULTS: 31% (24/78) of patients developed VTE. 12.8% (10/78) had deep venous thrombosis (DVT) alone, 11.5% (9/78) isolated pulmonary embolism (PE) and 6.4% (5/78) both. The median time from PCNSL diagnosis to VTE was 3 months. In a univariate competing risks analysis, previous VTE (p < 0.001), impaired ambulation (p = 0.035), baseline hemoglobin < 10 g/dL (p = 0.025) and history of diabetes mellitus (type 1 or 2) (p = 0.007) were associated with increased VTE risk. 34.8% were anticoagulated acutely with heparin (8/23) or 65.2% LMWH (15/23), and 25.0% (6/24) received warfarin, 41.7% (10/24) LMWH, and 33.3% (8/24) DOACs long-term. One adverse event was attributable to anticoagulation (arm hematoma with hemoglobin decrease). Five patients received IVC filters with concomitant oral anticoagulation; one experienced IVC thrombosis after anticoagulation discontinuation. Six of the 24 patients experienced recurrent VTE, four while anticoagulated. CONCLUSION: Patients with PCNSL are at high risk of VTE, most of which accrues in the first few months. History of VTE, diabetes mellitus (type 1 or 2), impaired ambulatory status, or hemoglobin < 10 g/dL may predispose patients to this complication. While optimal management is uncertain, anticoagulation prevented recurrent VTE in most patients without intracranial bleeding.


Assuntos
Neoplasias do Sistema Nervoso Central , Linfoma não Hodgkin , Tromboembolia Venosa , Neoplasias do Sistema Nervoso Central/complicações , Humanos , Incidência , Linfoma não Hodgkin/complicações , Estudos Retrospectivos , Fatores de Risco , Tromboembolia Venosa/epidemiologia , Tromboembolia Venosa/terapia
7.
Clin Trials ; 18(3): 314-323, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-33426919

RESUMO

BACKGROUND/AIMS: This article describes the proposed design of a phase I study evaluating the safety of ceramide nanoliposome and vinblastine among an initial set of 19 possible dose combinations in patients with relapsed/refractory acute myeloid leukemia and patients with untreated acute myeloid leukemia who are not candidates for intensive induction chemotherapy. METHODS: Extensive collaboration between statisticians and clinical investigators revealed the need to incorporate several adaptive features into the design, including the flexibility of adding or eliminating certain dose combinations based on safety criteria applied to multiple dose pairs. During the design stage, additional dose levels of vinblastine were added, increasing the dimension of the drug combination space and thus the complexity of the problem. Increased complexity made application of existing drug combination dose-finding methods unsuitable in their current form. RESULTS: Our solution to these challenges was to adapt a method based on isotonic regression to meet the research objectives of the study. Application of this adapted method is described herein, and a simulation study of the design's operating characteristics is conducted. CONCLUSION: The aim of this article is to bring to light examples of novel design applications as a means of augmenting the implementation of innovative designs in the future and to demonstrate the flexibility of adaptive designs in satisfying changing design conditions.


Assuntos
Ensaios Clínicos Adaptados como Assunto , Ensaios Clínicos Fase I como Assunto , Relação Dose-Resposta a Droga , Leucemia Mieloide Aguda , Projetos de Pesquisa , Simulação por Computador , Combinação de Medicamentos , Humanos , Leucemia Mieloide Aguda/tratamento farmacológico , Dose Máxima Tolerável
8.
Cancer Immunol Immunother ; 69(1): 95-102, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-31807879

RESUMO

INTRODUCTION: In contemporary oncology drug development, implementation of novel early-phase designs with the ability to address multiple research objectives is needed to better refine regimens. This paper describes an adaptive design strategy for identifying a range of optimal regimens based on two endpoints within multiple cohorts. The proposed design was developed to address objectives in an early-phase trial of cancer vaccines in combination with agonistic antibodies to CD40 and CD27. MATERIALS AND METHODS: We describe a model-based design strategy that was developed for a trial evaluating the safety and immunogenicity of vaccination with (1) peptides plus CD40 antibody and TLR3 ligand, (2) systemic administration of an agonistic CD27 antibody, and (3) to assess immune response from (1) and (2) compared to optimal controls in participants with stage IIB-IV melanoma. RESULTS AND CONCLUSIONS: The proposed design is a practical adaptive method for use with combined immunotherapy regimens with multiple objectives within multiple cohorts of interest. Further advances in the effectiveness of cancer immunotherapies will require new approaches that include redefining optimal strategies to take multiple regimens forward into later phases, incorporating additional endpoints in the dose selection process and testing drug combination therapies to improve efficacy and reduce toxicity. Our goal is to facilitate the acceptance and application of more novel designs in contemporary early development trials.


Assuntos
Imunoterapia/métodos , Melanoma/terapia , Projetos de Pesquisa , Neoplasias Cutâneas/terapia , Antineoplásicos Imunológicos/farmacologia , Antineoplásicos Imunológicos/uso terapêutico , Antígenos CD40/antagonistas & inibidores , Antígenos CD40/imunologia , Vacinas Anticâncer/uso terapêutico , Ensaios Clínicos Fase I como Assunto , Ensaios Clínicos Fase II como Assunto , Terapia Combinada/métodos , Desenvolvimento de Medicamentos , Humanos , Melanoma/imunologia , Neoplasias Cutâneas/imunologia , Membro 7 da Superfamília de Receptores de Fatores de Necrose Tumoral/antagonistas & inibidores , Membro 7 da Superfamília de Receptores de Fatores de Necrose Tumoral/imunologia
9.
Clin Trials ; 17(2): 157-165, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-31856602

RESUMO

BACKGROUND/AIMS: Dose feasibility is a challenge that may arise in the development of adoptive T cell therapies for cancer. In early-phase clinical trials, dose is quantified either by a fixed or per unit body weight number of cells infused. It may not be feasible, however, to administer a patient's assigned dose due to an insufficient number of cells harvested or functional heterogeneity of the product. The study objective becomes to identify the maximum tolerated dose with high feasibility of being administered. This article describes a new dose-finding method that adaptively accounts for safety and feasibility endpoints in guiding dose allocation. METHODS: We propose an adaptive dose-finding method that integrates accumulating feasibility and safety data to select doses for participant cohorts in early-phase trials examining adoptive cell immunotherapy. We sequentially model the probability of dose-limiting toxicity and the probability of feasibility using independent beta-binomial models. The probability model for toxicity borrows information across all dose levels using isotonic regression, allowing participants infused at a lower dose than his or her planned dose to contribute safety data to the dose-finding algorithm. We applied the proposed methodology in a single simulated trial and evaluated its operating characteristics through extensive simulation studies. RESULTS: In simulations conducted for a phase I study of adoptive immunotherapy for newly diagnosed glioblastoma, the proposed method demonstrates the ability to identify accurately the feasible maximum tolerated doses and to treat participants at and around these doses. Over 10 hypothesized scenarios studied, the percentage of correctly selecting the true feasible and maximum tolerated dose ranged from 50% to 90% with sample sizes averaging between 21 and 24 participants. A comparison to the only known existing method accounting for safety and feasibility yields competitive performance. CONCLUSION: We have developed a new practical adaptive dose-finding method to assess feasibility in early-phase adoptive cell therapy trials. A design that incorporates feasibility, as a function of the quantity and quality of the product manufactured, in addition to safety will have an impact on the recommended phase II doses in studies that evaluate patient outcomes.


Assuntos
Ensaios Clínicos Fase I como Assunto/métodos , Imunoterapia Adotiva/métodos , Dose Máxima Tolerável , Neoplasias/tratamento farmacológico , Algoritmos , Relação Dose-Resposta a Droga , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Determinação de Ponto Final , Estudos de Viabilidade , Humanos , Imunoterapia Adotiva/efeitos adversos , Modelos Estatísticos , Neoplasias/imunologia , Projetos de Pesquisa
10.
Pharm Stat ; 19(2): 137-144, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31692233

RESUMO

This paper studies the notion of coherence in interval-based dose-finding methods. An incoherent decision is either (a) a recommendation to escalate the dose following an observed dose-limiting toxicity or (b) a recommendation to deescalate the dose following a non-dose-limiting toxicity. In a simulated example, we illustrate that the Bayesian optimal interval method and the Keyboard method are not coherent. We generated dose-limiting toxicity outcomes under an assumed set of true probabilities for a trial of n=36 patients in cohorts of size 1, and we counted the number of incoherent dosing decisions that were made throughout this simulated trial. Each of the methods studied resulted in 13/36 (36%) incoherent decisions in the simulated trial. Additionally, for two different target dose-limiting toxicity rates, 20% and 30%, and a sample size of n=30 patients, we randomly generated 100 dose-toxicity curves and tabulated the number of incoherent decisions made by each method in 1000 simulated trials under each curve. For each method studied, the probability of incurring at least one incoherent decision during the conduct of a single trial is greater than 75%. Coherency is an important principle in the conduct of dose-finding trials. Interval-based methods violate this principle for cohorts of size 1 and require additional modifications to overcome this shortcoming. Researchers need to take a closer look at the dose assignment behavior of interval-based methods when using them to plan dose-finding studies.


Assuntos
Ensaios Clínicos como Assunto/métodos , Simulação por Computador , Dose Máxima Tolerável , Teorema de Bayes , Ensaios Clínicos como Assunto/estatística & dados numéricos , Simulação por Computador/estatística & dados numéricos , Relação Dose-Resposta a Droga , Humanos
11.
Clin Trials ; 16(6): 665-672, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-31547691

RESUMO

BACKGROUND: This article studies the notion of irrational dose assignment in Phase I clinical trials. This property was recently defined by Zhou and colleagues as a dose assignment that fails to de-escalate the dose when two out of three, three out of six, or four out of six patients have experienced a dose-limiting toxicity event at the current dose level. The authors claimed that a drawback of the well-known continual reassessment method is that it can result in irrational dose assignments. The aim of this article is to examine this definition of irrationality more closely within the conduct of the continual reassessment method. METHODS: Over a broad range of assumed dose-limiting toxicity probability scenarios for six study dose levels and a variety of target dose-limiting toxicity rates, we simulated 2000 trials of n = 36 patients. For each scenario, we counted the number of irrational dose assignments that were made by the continual reassessment method, according to the definitions of Zhou and colleagues. For each of the irrational decisions made, we classified the dose assignment as an underdose assignment, a target dose assignment, or an overdose assignment based on the true dose-limiting toxicity probability at that dose. RESULTS: Across eight dose-toxicity scenarios, there were a total of 181,581 dose assignments made in the simulation study. Of these assignments, 8165 (4.5%) decisions were made when two out of three, three out of six, or four out of six patients had experienced a dose-limiting toxicity at the current dose. Of these 8165 decisions, 1505 (18.4%) recommended staying at the current dose level and would therefore be classified as irrational by Zhou and colleagues. Among the irrational decisions, 41.2% were misclassified, meaning they were made either at the true target dose (17.9%) or at a true underdose (23.3%). The remaining 58.8% were made at a true overdose and therefore truly irrational. Overall, irrational dose assignments comprised <1% of the total dose assignments made during the simulation study. Similar findings are reported in simulations across 100 randomly generated dose-toxicity scenarios from a recently proposed family of curves. CONCLUSION: Zhou and colleagues argue that the behavior of the continual reassessment method is disturbing due to its ability to make irrational dose assignments. These definitions are based on rules that mimic the popular 3 + 3 design, which should not be the benchmark used to construct guidelines for trial conduct of modern Phase I methods. Our study illustrates that these dose assignments occur very seldom in the continual reassessment method and that even when they do occur, they can often be considered sensible when accounting for all accumulated data in the study.


Assuntos
Ensaios Clínicos Fase I como Assunto/métodos , Relação Dose-Resposta a Droga , Dose Máxima Tolerável , Modelos Estatísticos , Ensaios Clínicos Fase I como Assunto/estatística & dados numéricos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Humanos , Projetos de Pesquisa
12.
Clin Trials ; 16(1): 32-40, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30309262

RESUMO

BACKGROUND: Limited options are available for dose-finding clinical trials requiring group-specific dose selection. While conducting parallel trials for groups is an accessible approach to group-specific dose selection, this approach allows for maximum tolerated dose selection that does not align with clinically meaningful group order information. METHODS: The two-stage continual reassessment method is developed for dose-finding in studies involving three or more groups where group frailty order is known between some but not all groups, creating a partial order. This is an extension of the existing continual reassessment method shift model for two ordered groups. This method allows for dose selection by group, where maximum tolerated dose selection follows the known frailty order among groups. For example, if a group is known to be the most frail, the recommended maximum tolerated dose for this group should not exceed the maximum tolerated dose recommended for any other group. RESULTS: With limited alternatives for dose-finding in partially ordered groups, this method is compared to two alternatives: (1) an existing method for dose-finding in partially ordered groups which is less computationally accessible and (2) independent trials for each group using the two-stage continual reassessment method. Simulation studies show that when ignoring information on group frailty, using independent continual reassessment method trials by group, 30% of simulations would result in maximum tolerated dose selection that is out of order between groups. In addition, the two-stage continual reassessment method for partially ordered groups selects the maximum tolerated dose more often and assigns more patients to the maximum tolerated dose compared to using independent continual reassessment method trials within each group. Simulation results for the proposed method and the less computationally accessible approach are similar. CONCLUSION: The proposed continual reassessment method for partially ordered groups ensures appropriate maximum tolerated dose order and improves accuracy of maximum tolerated dose selection, while allowing for trial implementation that is computationally accessible.


Assuntos
Ensaios Clínicos Fase I como Assunto/métodos , Irinotecano/administração & dosagem , Dose Máxima Tolerável , Idoso , Relação Dose-Resposta a Droga , Idoso Fragilizado , Humanos , Projetos de Pesquisa
13.
J Biopharm Stat ; 29(2): 333-347, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30451068

RESUMO

In this article, we propose and evaluate three alternative randomization strategies to the adaptive randomization (AR) stage used in a seamless Phase I/II dose-finding design. The original design was proposed by Wages and Tait in 2015 for trials of molecularly targeted agents in cancer treatments, where dose-efficacy assumptions are not always monotonically increasing. Our goal is to improve the design's overall performance regarding the estimation of optimal dose as well as patient allocation to effective treatments. The proposed methods calculate randomization probabilities based on the likelihood of every candidate model as opposed to the original design which selects the best model and then randomizes doses based on estimations from the selected model. Unlike the original method, our proposed adaption does not require an arbitrarily specified sample size for the adaptive randomization stage. Simulations are used to compare the proposed strategies and a final strategy is recommended. Under most scenarios, our recommended method allocates more patients to the optimal dose while improving accuracy in selecting the final optimal dose without increasing the overall risk of toxicity.


Assuntos
Antineoplásicos/administração & dosagem , Ensaios Clínicos Fase I como Assunto/estatística & dados numéricos , Ensaios Clínicos Fase II como Assunto/estatística & dados numéricos , Modelos Estatísticos , Neoplasias/tratamento farmacológico , Ensaios Clínicos Controlados Aleatórios como Assunto/estatística & dados numéricos , Algoritmos , Antineoplásicos/efeitos adversos , Antineoplásicos/uso terapêutico , Ensaios Clínicos Fase I como Assunto/métodos , Ensaios Clínicos Fase II como Assunto/métodos , Simulação por Computador , Relação Dose-Resposta a Droga , Humanos , Dose Máxima Tolerável , Ensaios Clínicos Controlados Aleatórios como Assunto/métodos , Tamanho da Amostra , Resultado do Tratamento
14.
J Biopharm Stat ; 29(4): 635-647, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31264936

RESUMO

This article considers the problem of designing Phase I-II clinical trials with delayed toxicity and efficacy outcomes. The proposed design is motivated by a Phase I-II study evaluating all-trans retinoic acid (ATRA) in combination with a fixed dose of daratumumab in the treatment of relapsed or refractory multiple myeloma. The primary objective of the study is to identify a dose that maximizes efficacy and has an acceptable level of toxicity. The toxicity endpoint is observed in one cycle of therapy (i.e., 4 weeks) while the efficacy endpoint is assessed after 8 weeks of treatment. The difference in endpoint observation windows causes logistical challenges in conducting the trial, since it is not practical to wait until both outcomes for each patient have been fully observed before sequentially assigning the dose of a newly eligible patient. In order to avoid delays in treatment for newly enrolled patients and to accelerate trial progress, we generalize the time-to-event continual reassessment method (TITE-CRM) to bivariate outcomes. Simulation studies are conducted to evaluate the proposed method, and we found that the proposed design is able to accurately select doses that maximize efficacy and have acceptable toxicity, while using all available information in allocating patients at the time of dose assignment. We compare the proposed methodology to two existing methods in the area.


Assuntos
Anticorpos Monoclonais/administração & dosagem , Ensaios Clínicos Fase I como Assunto , Ensaios Clínicos Fase II como Assunto , Mieloma Múltiplo/tratamento farmacológico , Projetos de Pesquisa , Tretinoína/administração & dosagem , Anticorpos Monoclonais/efeitos adversos , Humanos , Tretinoína/efeitos adversos
15.
BMC Cancer ; 18(1): 133, 2018 02 05.
Artigo em Inglês | MEDLINE | ID: mdl-29402249

RESUMO

BACKGROUND: Broad implementation of model-based dose-finding methods, such as the continual reassessment method (CRM), has been limited, with traditional or modified 3 + 3 designs remaining in frequent use. Part of the reason is the lack of reliable, easy-to-use, and robust software tools for designing and implementing more efficient designs. RESULTS: With the aim of augmenting broader implementation of model-guided methods, we have developed a web application for the Bayesian CRM in the R programming language using the Shiny package. The application has two components, simulation and implementation. Within the application, one has the ability to generate simulated operating characteristics for the study design phase, and to sequentially provide the next dose recommendation for each new accrual or cohort based on the current data for the study implementation phase. At the conclusion of the study, it can be used to estimate the maximum tolerated dose (MTD). The web tool requires no programming knowledge, and it is free to access on any device with an internet browser. CONCLUSIONS: The application provides the type of simulation information that aid clinicians and reviewers in understanding operating characteristics for the accuracy and safety of the CRM, which we hope will augment phase I trial design. We believe that the development of this software will facilitate more efficient collaborations within study teams conducting single-agent dose-finding trials.


Assuntos
Ensaios Clínicos Fase I como Assunto/métodos , Internet , Projetos de Pesquisa , Software , Teorema de Bayes , Simulação por Computador , Humanos , Avaliação de Resultados em Cuidados de Saúde/métodos
16.
Clin Trials ; 15(5): 524-529, 2018 10.
Artigo em Inglês | MEDLINE | ID: mdl-30101616

RESUMO

Background/aims In the conduct of phase I trials, the limited use of innovative model-based designs in practice has led to an introduction of a class of "model-assisted" designs with the aim of effectively balancing the trade-off between design simplicity and performance. Prior to the recent surge of these designs, methods that allocated patients to doses based on isotonic toxicity probability estimates were proposed. Like model-assisted methods, isotonic designs allow investigators to avoid difficulties associated with pre-trial parametric specifications of model-based designs. The aim of this work is to take a fresh look at an isotonic design in light of the current landscape of model-assisted methods. Methods The isotonic phase I method of Conaway, Dunbar, and Peddada was proposed in 2004 and has been regarded primarily as a design for dose-finding in drug combinations. It has largely been overlooked in the single-agent setting. Given its strong simulation performance in application to more complex dose-finding problems, such as drug combinations and patient heterogeneity, as well as the recent development of user-friendly software to accompany the method, we take a fresh look at this design and compare it to a current model-assisted method. We generated operating characteristics of the Conaway-Dunbar-Peddada method using a new web application developed for simulating and implementing the design and compared it to the recently proposed Keyboard design that is based on toxicity probability intervals. Results The Conaway-Dunbar-Peddada method has better performance in terms of accuracy of dose recommendation and safety in patient allocation in 17 of 20 scenarios considered. The Conaway-Dunbar-Peddada method also allocated fewer patients to doses above the maximum tolerated dose than the Keyboard method in many of scenarios studied. Overall, the performance of the Conaway-Dunbar-Peddada method is strong when compared to the Keyboard method, making it a viable simple alternative to the model-assisted methods developed in recent years. Conclusion The Conaway-Dunbar-Peddada method does not rely on the specification and fitting of a parametric model for the entire dose-toxicity curve to estimate toxicity probabilities as other model-based designs do. It relies on a similar set of pre-trial specifications to toxicity probability interval-based methods, yet unlike model-assisted methods, it is able to borrow information across all dose levels, increasing its efficiency. We hope this concise study of the Conaway-Dunbar-Peddada method, and the availability of user-friendly software, will augment its use in practice.


Assuntos
Ensaios Clínicos Fase I como Assunto , Cálculos da Dosagem de Medicamento , Relação Dose-Resposta a Droga , Humanos , Projetos de Pesquisa
17.
Cancer Immunol Immunother ; 66(1): 33-43, 2017 01.
Artigo em Inglês | MEDLINE | ID: mdl-27770170

RESUMO

INTRODUCTION: Infiltration of non-small-cell lung cancer (NSCLC) by CD8+ T lymphocytes predicts improved patient survival; however, heterogeneity of intratumoral localization complicates this assessment. Strategies for tumor sampling may not accurately represent the whole tumor. We hypothesized that sampling strategies may alter the identification of tumors with high CD8 density and affect the prognostic significance. PATIENTS AND METHODS: Twenty-three primary NSCLC tumors were immunohistochemically stained for CD8 and were assessed using automated software with eight different sampling strategies or the whole tumor. Results of all sampling strategies were compared to the whole tumor counts (paired t tests, Pearson's r). Associations between CD8 densities and overall survival were assessed (log-rank test). RESULTS: Counts from all eight sampling strategies significantly correlated with whole tumor counts (p ≤ 0.001). However, the magnitude of CD8+ cell counts and categorization into high vs low infiltrate groups were affected by the sampling strategy. The most concordant values were derived from random sampling of 20 % of the tumor, a simulated core biopsy, or from sampling the tumor center. TIL infiltration was associated with survival when sampling the center (p = 0.038), but not the invasive margin (p > 0.2) or other strategies. CONCLUSION: Different tumor sampling strategies may yield discordant TIL density results and different stratification for risk assessment. Small biopsies may be particularly unrepresentative. Random sampling of larger tumor areas is recommended. Enumerating CD8+ T cells in the tumor center may have prognostic value.


Assuntos
Linfócitos T CD8-Positivos/imunologia , Carcinoma Pulmonar de Células não Pequenas/imunologia , Neoplasias Pulmonares/imunologia , Linfócitos do Interstício Tumoral/imunologia , Linfócitos T CD8-Positivos/patologia , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Carcinoma Pulmonar de Células não Pequenas/patologia , Humanos , Imuno-Histoquímica , Neoplasias Pulmonares/mortalidade , Neoplasias Pulmonares/patologia , Linfócitos do Interstício Tumoral/patologia , Prognóstico , Análise de Sobrevida
18.
Stat Med ; 36(2): 242-253, 2017 01 30.
Artigo em Inglês | MEDLINE | ID: mdl-26910586

RESUMO

The majority of phase I methods for multi-agent trials have focused on identifying a single maximum tolerated dose combination (MTDC) among those being investigated. Some published methods in the area have been based on the notion that there is no unique MTDC and that the set of dose combinations with acceptable toxicity forms an equivalence contour in two dimensions. Therefore, it may be of interest to find multiple MTDCs for further testing for efficacy in a phase II setting. In this paper, we present a new dose-finding method that extends the continual reassessment method to account for the location of multiple MTDCs. Operating characteristics are demonstrated through simulation studies and are compared with existing methodology. Some brief discussion of implementation and available software is also provided. Copyright © 2016 John Wiley & Sons, Ltd.


Assuntos
Antineoplásicos/administração & dosagem , Protocolos de Quimioterapia Combinada Antineoplásica/administração & dosagem , Ensaios Clínicos Fase I como Assunto/métodos , Antineoplásicos/toxicidade , Protocolos de Quimioterapia Combinada Antineoplásica/toxicidade , Bioestatística , Ensaios Clínicos Fase I como Assunto/estatística & dados numéricos , Simulação por Computador , Humanos , Funções Verossimilhança , Dose Máxima Tolerável , Modelos Estatísticos , Neoplasias/tratamento farmacológico , Probabilidade , Software
19.
Stat Med ; 36(2): 254-265, 2017 01 30.
Artigo em Inglês | MEDLINE | ID: mdl-27624880

RESUMO

We propose a new design for dose finding for cytotoxic agents in two ordered groups of patients. By ordered groups, we mean that prior to the study there is clinical information that would indicate that for a given dose one group would be more susceptible to toxicities than patients in the other group. The designs are evaluated relative to two previously proposed designs for ordered groups over a range of scenarios generated randomly from a family of dose-toxicity curves. Copyright © 2016 John Wiley & Sons, Ltd.


Assuntos
Ensaios Clínicos Fase I como Assunto/métodos , Algoritmos , Antineoplásicos/efeitos adversos , Antineoplásicos/toxicidade , Protocolos de Quimioterapia Combinada Antineoplásica/administração & dosagem , Protocolos de Quimioterapia Combinada Antineoplásica/toxicidade , Bioestatística , Ensaios Clínicos Fase I como Assunto/estatística & dados numéricos , Simulação por Computador , Relação Dose-Resposta a Droga , Humanos , Dose Máxima Tolerável , Modelos Estatísticos , Neoplasias/tratamento farmacológico
20.
Stat Med ; 36(2): 291-300, 2017 01 30.
Artigo em Inglês | MEDLINE | ID: mdl-27435150

RESUMO

Toxicity probability interval designs have received increasing attention as a dose-finding method in recent years. In this study, we compared the two-stage, likelihood-based continual reassessment method (CRM), modified toxicity probability interval (mTPI), and the Bayesian optimal interval design (BOIN) in order to evaluate each method's performance in dose selection for phase I trials. We use several summary measures to compare the performance of these methods, including percentage of correct selection (PCS) of the true maximum tolerable dose (MTD), allocation of patients to doses at and around the true MTD, and an accuracy index. This index is an efficiency measure that describes the entire distribution of MTD selection and patient allocation by taking into account the distance between the true probability of toxicity at each dose level and the target toxicity rate. The simulation study considered a broad range of toxicity curves and various sample sizes. When considering PCS, we found that CRM outperformed the two competing methods in most scenarios, followed by BOIN, then mTPI. We observed a similar trend when considering the accuracy index for dose allocation, where CRM most often outperformed both mTPI and BOIN. These trends were more pronounced with increasing number of dose levels. Copyright © 2016 John Wiley & Sons, Ltd.


Assuntos
Ensaios Clínicos Fase I como Assunto/métodos , Algoritmos , Teorema de Bayes , Bioestatística , Ensaios Clínicos Fase I como Assunto/estatística & dados numéricos , Simulação por Computador , Relação Dose-Resposta a Droga , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Humanos , Funções Verossimilhança , Dose Máxima Tolerável , Modelos Estatísticos
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