1
|
Zhang J, Lin R, Chen X, Yan F. Adaptive Bayesian information borrowing methods for finding and optimizing subgroup-specific doses. Clin Trials 2024; 21:308-321. [PMID: 38243401 PMCID: PMC11132956 DOI: 10.1177/17407745231212193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2024]
Abstract
In precision oncology, integrating multiple cancer patient subgroups into a single master protocol allows for the simultaneous assessment of treatment effects in these subgroups and promotes the sharing of information between them, ultimately reducing sample sizes and costs and enhancing scientific validity. However, the safety and efficacy of these therapies may vary across different subgroups, resulting in heterogeneous outcomes. Therefore, identifying subgroup-specific optimal doses in early-phase clinical trials is crucial for the development of future trials. In this article, we review various innovative Bayesian information-borrowing strategies that aim to determine and optimize subgroup-specific doses. Specifically, we discuss Bayesian hierarchical modeling, Bayesian clustering, Bayesian model averaging or selection, pairwise borrowing, and other relevant approaches. By employing these Bayesian information-borrowing methods, investigators can gain a better understanding of the intricate relationships between dose, toxicity, and efficacy in each subgroup. This increased understanding significantly improves the chances of identifying an optimal dose tailored to each specific subgroup. Furthermore, we present several practical recommendations to guide the design of future early-phase oncology trials involving multiple subgroups when using the Bayesian information-borrowing methods.
Collapse
Affiliation(s)
- Jingyi Zhang
- Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Ruitao Lin
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xin Chen
- Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Fangrong Yan
- Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China
| |
Collapse
|
2
|
Chiuzan C, Dehbi HM. The 3 + 3 design in dose-finding studies with small sample sizes: Pitfalls and possible remedies. Clin Trials 2024; 21:350-357. [PMID: 38618916 DOI: 10.1177/17407745241240401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
In the last few years, numerous novel designs have been proposed to improve the efficiency and accuracy of phase I trials to identify the maximum-tolerated dose (MTD) or the optimal biological dose (OBD) for noncytotoxic agents. However, the conventional 3+3 approach, known for its and poor performance, continues to be an attractive choice for many trials despite these alternative suggestions. The article seeks to underscore the importance of moving beyond the 3+3 design by highlighting a different key element in trial design: the estimation of sample size and its crucial role in predicting toxicity and determining the MTD. We use simulation studies to compare the performance of the most used phase I approaches: 3+3, Continual Reassessment Method (CRM), Keyboard and Bayesian Optimal Interval (BOIN) designs regarding three key operating characteristics: the percentage of correct selection of the true MTD, the average number of patients allocated per dose level, and the average total sample size. The simulation results consistently show that the 3+3 algorithm underperforms in comparison to model-based and model-assisted designs across all scenarios and metrics. The 3+3 method yields significantly lower (up to three times) probabilities in identifying the correct MTD, often selecting doses one or even two levels below the actual MTD. The 3+3 design allocates significantly fewer patients at the true MTD, assigns higher numbers to lower dose levels, and rarely explores doses above the target dose-limiting toxicity (DLT) rate. The overall performance of the 3+3 method is suboptimal, with a high level of unexplained uncertainty and significant implications for accurately determining the MTD. While the primary focus of the article is to demonstrate the limitations of the 3+3 algorithm, the question remains about the preferred alternative approach. The intention is not to definitively recommend one model-based or model-assisted method over others, as their performance can vary based on parameters and model specifications. However, the presented results indicate that the CRM, Keyboard, and BOIN designs consistently outperform the 3+3 and offer improved efficiency and precision in determining the MTD, which is crucial in early-phase clinical trials.
Collapse
Affiliation(s)
- Cody Chiuzan
- Northwell Health, New Hyde Park, NY, USA
- Institute of Health System Science, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Hakim-Moulay Dehbi
- Comprehensive Clinical Trials Unit, University College London, London, UK
| |
Collapse
|
3
|
Celum C, Conaway M. A model-assisted design for partially or completely ordered groups. Pharm Stat 2024. [PMID: 38769904 DOI: 10.1002/pst.2396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 04/11/2024] [Accepted: 04/29/2024] [Indexed: 05/22/2024]
Abstract
This paper proposes a trial design for locating group-specific doses when groups are partially or completely ordered by dose sensitivity. Previous trial designs for partially ordered groups are model-based, whereas the proposed method is model-assisted, providing clinicians with a design that is simpler. The proposed method performs similarly to model-based methods, providing simplicity without losing accuracy. Additionally, to the best of our knowledge, the proposed method is the first paper on dose-finding for partially ordered groups with convergence results. To generalize the proposed method, a framework is introduced that allows partial orders to be transferred to a grid format with a known ordering across rows but an unknown ordering within rows.
Collapse
Affiliation(s)
- Connor Celum
- Department of Statistics, University of Virginia, Charlottesville, Virginia, USA
| | - Mark Conaway
- Department of Statistics, University of Virginia, Charlottesville, Virginia, USA
- Department of Public Health Sciences, Division of Translational Research and Applied Statistics, University of Virginia, Charlottesville, Virginia, USA
| |
Collapse
|
4
|
Celum C, Horton BJ, Conaway M. The quasi-CRM shift method for partially ordered groups. Contemp Clin Trials 2024; 136:107400. [PMID: 38000453 DOI: 10.1016/j.cct.2023.107400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 11/01/2023] [Accepted: 11/18/2023] [Indexed: 11/26/2023]
Abstract
This paper proposes a phase-I clinical trial design that uses ordinal toxicity to locate group-specific doses when groups are partially or completely ordered prior to the start of the trial. There has been previous work on dose-finding for groups and on dose-finding with ordinal toxicity but a solution to the problem of dose-finding for groups with ordinal toxicity has not been proposed. Simulations compared the proposed method against two methods; one that uses ordinal toxicity but does not use group information and one that uses group information but does not use ordinal toxicity. One issue with the first method is the potential for reversals, when the recommended dose for a more sensitive group is higher than the recommended dose for a less sensitive group. The proposed method avoids reversals, allocates patients to optimal doses more frequently during the trial, and selects optimal doses more frequently at the end of the trial.
Collapse
Affiliation(s)
- Connor Celum
- Department of Statistics, University of Virginia, Charlottesville, VA, USA.
| | - Bethany Jablonski Horton
- Division Of Translational Research and Applied Statistics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Mark Conaway
- Department of Statistics, University of Virginia, Charlottesville, VA, USA; Division Of Translational Research and Applied Statistics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| |
Collapse
|
5
|
Solovyeva O, Dimairo M, Weir CJ, Hee SW, Espinasse A, Ursino M, Patel D, Kightley A, Hughes S, Jaki T, Mander A, Evans TRJ, Lee S, Hopewell S, Rantell KR, Chan AW, Bedding A, Stephens R, Richards D, Roberts L, Kirkpatrick J, de Bono J, Yap C. Development of consensus-driven SPIRIT and CONSORT extensions for early phase dose-finding trials: the DEFINE study. BMC Med 2023; 21:246. [PMID: 37408015 PMCID: PMC10324137 DOI: 10.1186/s12916-023-02937-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 06/12/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Early phase dose-finding (EPDF) trials are crucial for the development of a new intervention and influence whether it should be investigated in further trials. Guidance exists for clinical trial protocols and completed trial reports in the SPIRIT and CONSORT guidelines, respectively. However, both guidelines and their extensions do not adequately address the characteristics of EPDF trials. Building on the SPIRIT and CONSORT checklists, the DEFINE study aims to develop international consensus-driven guidelines for EPDF trial protocols (SPIRIT-DEFINE) and reports (CONSORT-DEFINE). METHODS The initial generation of candidate items was informed by reviewing published EPDF trial reports. The early draft items were refined further through a review of the published and grey literature, analysis of real-world examples, citation and reference searches, and expert recommendations, followed by a two-round modified Delphi process. Patient and public involvement and engagement (PPIE) was pursued concurrently with the quantitative and thematic analysis of Delphi participants' feedback. RESULTS The Delphi survey included 79 new or modified SPIRIT-DEFINE (n = 36) and CONSORT-DEFINE (n = 43) extension candidate items. In Round One, 206 interdisciplinary stakeholders from 24 countries voted and 151 stakeholders voted in Round Two. Following Round One feedback, one item for CONSORT-DEFINE was added in Round Two. Of the 80 items, 60 met the threshold for inclusion (≥ 70% of respondents voted critical: 26 SPIRIT-DEFINE, 34 CONSORT-DEFINE), with the remaining 20 items to be further discussed at the consensus meeting. The parallel PPIE work resulted in the development of an EPDF lay summary toolkit consisting of a template with guidance notes and an exemplar. CONCLUSIONS By detailing the development journey of the DEFINE study and the decisions undertaken, we envision that this will enhance understanding and help researchers in the development of future guidelines. The SPIRIT-DEFINE and CONSORT-DEFINE guidelines will allow investigators to effectively address essential items that should be present in EPDF trial protocols and reports, thereby promoting transparency, comprehensiveness, and reproducibility. TRIAL REGISTRATION SPIRIT-DEFINE and CONSORT-DEFINE are registered with the EQUATOR Network ( https://www.equator-network.org/ ).
Collapse
Affiliation(s)
| | - Munyaradzi Dimairo
- Clinical Trials Research Unit, School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - Christopher J Weir
- Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Siew Wan Hee
- University Hospitals Coventry & Warwickshire NHS Trust, Coventry, UK
- University of Warwick, Coventry, UK
| | | | - Moreno Ursino
- Inserm, Centre de Recherche Des Cordeliers, Sorbonne UniversitéUniversité Paris Cité, 75006, Paris, France
- HeKA, Inria Paris, 75015, Paris, France
- Unit of Clinical Epidemiology, AP-HP, CHU Robert Debré, CIC-EC 1426, Paris, France
- RECaP/F-CRIN, Inserm, 5400, Nancy, France
| | | | - Andrew Kightley
- Patient and Public Involvement and Engagement (PPIE) Lead, Lichfield, UK
| | | | - Thomas Jaki
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- University of Regensburg, Regensburg, Germany
| | | | | | - Shing Lee
- Columbia University, Mailman School of Public Health, New York, USA
| | - Sally Hopewell
- Oxford Clinical Trials Research Unit, University of Oxford, Oxford, UK
| | | | - An-Wen Chan
- Department of Medicine, Women's College Research Institute, University of Toronto, Toronto, Canada
| | | | | | | | | | | | - Johann de Bono
- The Institute of Cancer Research, London, UK
- The Royal Marsden NHS Foundation Trust, London, UK
| | | |
Collapse
|
6
|
Wages NA, Saleh RR, Braun TM. Concurrent dose-finding of a novel cancer drug with and without a second agent. J Clin Transl Sci 2023; 7:e126. [PMID: 37313388 PMCID: PMC10260343 DOI: 10.1017/cts.2023.542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 04/13/2023] [Accepted: 05/01/2023] [Indexed: 06/15/2023] Open
Abstract
Introduction More complex research questions are being posed in early-phase oncology clinical trials, necessitating design strategies tailored to contemporary study objectives. This paper describes the proposed design of a Phase I trial concurrently evaluating the safety of a hematopoietic progenitor kinase-1 inhibitor (Agent A) as a single agent and in combination with an anti-PD-1 agent in patients with advanced malignancies. The study's primary objective was to concurrently determine the maximum tolerated dose (MTD) of Agent A with and without anti-PD-1 therapy among seven possible study dose levels. Methods Our solution to this challenge was to apply a continual reassessment method shift model to meet the research objectives of the study. Results The application of this method is described herein, and a simulation study of the design's operating characteristics is conducted. This work was developed through collaboration and mentoring between the authors at the American Association for Cancer Research (AACR) and the American Society of Clinical Oncology (ASCO) annual AACR/ASCO Methods in Clinical Cancer Research Workshop. Conclusions The aim of this manuscript is to highlight 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 modern design conditions. Although the design is presented using an investigation of Agent A with and without anti-PD-1 therapy as an illustrative example, the approach described is not specific to these agents and could be applied to other concurrent monotherapy and combination therapy studies with well-defined binary safety endpoints.
Collapse
Affiliation(s)
- Nolan A. Wages
- Department of Biostatistics, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
- Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA
| | - Ramy R. Saleh
- Division of Medical Oncology & Hematology, Department of Medicine, Princess Margaret Cancer Centre, and the University of Toronto, Toronto, ON, Canada
| | - Thomas M. Braun
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| |
Collapse
|