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Dhaenens BAE, Heimann G, Bakker A, Nievo M, Ferner RE, Evans DG, Wolkenstein P, Leubner J, Potratz C, Carton C, Iloeje U, Kirk G, Blakeley JO, Plotkin S, Fisher MJ, Kim A, Driever PH, Azizi AA, Widemann BC, Gross A, Parke T, Legius E, Oostenbrink R. Platform trial design for neurofibromatosis type 1, NF2-related schwannomatosis and non-NF2-related schwannomatosis: A potential model for rare diseases. Neurooncol Pract 2024; 11:395-403. [PMID: 39006526 PMCID: PMC11241353 DOI: 10.1093/nop/npae001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/16/2024] Open
Abstract
Background Neurofibromatosis type 1, NF2-related schwannomatosis and non-NF2-related schwannomatosis (grouped under the abbreviation "NF") are rare hereditary tumor predisposition syndromes. Due to the low prevalence, variability in the range, and severity of manifestations, as well as limited treatment options, these conditions require innovative trial designs to accelerate the development of new treatments. Methods Within European Patient-Centric Clinical Trial Platforms (EU-PEARL), we designed 2 platform-basket trials in NF. The trials were designed by a team of multidisciplinary NF experts and trial methodology experts. Results The trial will consist of an observational and a treatment period. The observational period will serve as a longitudinal natural history study. The platform trial design and randomization to a sequence of available interventions allow for the addition of interventions during the trial. If a drug does not meet the predetermined efficacy endpoint or reveals unacceptable toxicities, participants may stop treatment on that arm and re-enter the observational period, where they can be re-randomized to a different treatment arm if eligible. Intervention-specific eligibility criteria and endpoints are listed in intervention-specific-appendices, allowing the flexibility and adaptability needed for highly variable and rare conditions like NF. Conclusions These innovative platform-basket trials for NF may serve as a model for other rare diseases, as they will enhance the chance of identifying beneficial treatments through optimal learning from a small number of patients. The goal of these trials is to identify beneficial treatments for NF more rapidly and at a lower cost than traditional, single-agent clinical trials.
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Affiliation(s)
- Britt A E Dhaenens
- Department of General Paediatrics, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
- ENCORE Expertise Centre for Neurodevelopmental Disorders, Erasmus MC, Rotterdam, The Netherlands
| | - Günter Heimann
- Biostatistics & Pharmacometrics, Novartis Pharma AG, Basel, Switzerland
| | | | - Marco Nievo
- Children's Tumor Foundation, New York, New York, USA
| | - Rosalie E Ferner
- Neurofibromatosis Service, Department of Neurology, Guy's and St. Thomas' NHS Foundation Trust London, Great Maze Pond, London, UK
| | - D Gareth Evans
- Centre for Genomic Medicine, Division of Evolution, Infection and Genomic Sciences, University of Manchester, St Mary's Hospital, Manchester, UK
| | | | - Jonas Leubner
- Department of Pediatric Neurology, Charité Universitätsmedizin Berlin-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Cornelia Potratz
- Department of Pediatric Neurology, Charité Universitätsmedizin Berlin-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | | | - Uchenna Iloeje
- Medical Affairs, SpringWorks Therapeutics, Stamford, Connecticut, USA
| | | | - Jaishri O Blakeley
- Department of Neurology, Neuro-Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Scott Plotkin
- Cancer Center and Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Michael J Fisher
- Division of Oncology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - AeRang Kim
- Division of Oncology, Children's National Hospital, Washington DC, District of Columbia, USA
| | - Pablo Hernáiz Driever
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Amedeo A Azizi
- Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Wien, Austria
| | - Brigitte C Widemann
- Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Andrea Gross
- Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | | | - Eric Legius
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Department of Clinical Genetics, UZ Leuven, Leuven, Belgium
- Full Member of the European Reference Network on Genetic Tumour Risk Syndromes (ERN GENTURIS), Nijmegen, The Netherlands (E.L., R.O.)
| | - Rianne Oostenbrink
- Department of General Paediatrics, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
- ENCORE Expertise Centre for Neurodevelopmental Disorders, Erasmus MC, Rotterdam, The Netherlands
- Full Member of the European Reference Network on Genetic Tumour Risk Syndromes (ERN GENTURIS), Nijmegen, The Netherlands
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2
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Lee KM, Emsley R. The impact of heterogeneity on the analysis of platform trials with normally distributed outcomes. BMC Med Res Methodol 2024; 24:163. [PMID: 39080538 PMCID: PMC11290279 DOI: 10.1186/s12874-024-02293-4] [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] [Received: 11/15/2023] [Accepted: 07/19/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND A platform trial approach allows adding arms to on-going trials to speed up intervention discovery programs. A control arm remains open for recruitment in a platform trial while intervention arms may be added after the onset of the study and could be terminated early for efficacy and/or futility when early stopping is allowed. The topic of utilising non-concurrent control data in the analysis of platform trials has been explored and discussed extensively. A less familiar issue is the presence of heterogeneity, which may exist for example due to modification of enrolment criteria and recruitment strategy. METHOD We conduct a simulation study to explore the impact of heterogeneity on the analysis of a two-stage platform trial design. We consider heterogeneity in treatment effects and heteroscedasticity in outcome data across stages for a normally distributed endpoint. We examine the performance of some hypothesis testing procedures and modelling strategies. The use of non-concurrent control data is also considered accordingly. Alongside standard regression analysis, we examine the performance of a novel method that was known as the pairwise trials analysis. It is similar to a network meta-analysis approach but adjusts for treatment comparisons instead of individual studies using fixed effects. RESULTS Several testing strategies with concurrent control data seem to control the type I error rate at the required level when there is heteroscedasticity in outcome data across stages and/or a random cohort effect. The main parameter of treatment effects in some analysis models correspond to overall treatment effects weighted by stage wise sample sizes; while others correspond to the effect observed within a single stage. The characteristics of the estimates are not affected significantly by the presence of a random cohort effect and/ or heteroscedasticity. CONCLUSION In view of heterogeneity in treatment effect across stages, the specification of null hypotheses in platform trials may need to be more subtle. We suggest employing testing procedure of adaptive design as opposed to testing the statistics from regression models; comparing the estimates from the pairwise trials analysis method and the regression model with interaction terms may indicate if heterogeneity is negligible.
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Affiliation(s)
- Kim May Lee
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, London, UK.
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Richard Emsley
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, London, UK
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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Staibano P, Oulousian E, McKechnie T, Thabane A, Luo S, Gupta MK, Zhang H, Pasternak JD, Au M, Parpia S, Young JEM(T, Bhandari M. Adaptive clinical trials in surgery: A scoping review of methodological and reporting quality. PLoS One 2024; 19:e0299494. [PMID: 38805454 PMCID: PMC11132449 DOI: 10.1371/journal.pone.0299494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 02/11/2024] [Indexed: 05/30/2024] Open
Abstract
IMPORTANCE Adaptive surgical trials are scarce, but adopting these methods may help elevate the quality of surgical research when large-scale RCTs are impractical. OBJECTIVE Randomized-controlled trials (RCTs) are the gold standard for evidence-based healthcare. Despite an increase in the number of RCTs, the number of surgical trials remains unchanged. Adaptive clinical trials can streamline trial design and time to trial reporting. The advantages identified for ACTs may help to improve the quality of future surgical trials. We present a scoping review of the methodological and reporting quality of adaptive surgical trials. EVIDENCE REVIEW We performed a search of Ovid, Web of Science, and Cochrane Collaboration for all adaptive surgical RCTs performed from database inception to October 12, 2023. We included any published trials that had at least one surgical arm. All review and abstraction were performed in duplicate. Risk of bias (RoB) was assessed using the RoB 2.0 instrument and reporting quality was evaluated using CONSORT ACE 2020. All results were analyzed using descriptive methods. FINDINGS Of the 1338 studies identified, six trials met inclusion criteria. Trials were performed in cardiothoracic, oral, orthopedic, and urological surgery. The most common type of adaptive trial was group sequential design with pre-specified interim analyses planned for efficacy, futility, and/or sample size re-estimation. Two trials did use statistical simulations. Our risk of bias evaluation identified a high risk of bias in 50% of included trials. Reporting quality was heterogeneous regarding trial design and outcome assessment and details in relation to randomization and blinding concealment. CONCLUSION AND RELEVANCE Surgical trialists should consider implementing adaptive components to help improve patient recruitment and reduce trial duration. Reporting of future adaptive trials must adhere to existing CONSORT ACE 2020 guidelines. Future research is needed to optimize standardization of adaptive methods across medicine and surgery.
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Affiliation(s)
- Phillip Staibano
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methodology, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Emily Oulousian
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, McMaster University, Hamilton, Ontario, Canada
- McGill University School of Medicine, McGill University, Montreal, Quebec, Canada
| | - Tyler McKechnie
- Department of Health Research Methodology, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
- Division of General Surgery, Department of Surgery, McMaster University, Hamilton, Ontario, Canada
| | - Alex Thabane
- Department of Health Research Methodology, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Samuel Luo
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, McMaster University, Hamilton, Ontario, Canada
- Michael G. DeGroote School of Medicine, Hamilton, Ontario, Canada
| | - Michael K. Gupta
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, McMaster University, Hamilton, Ontario, Canada
| | - Han Zhang
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, McMaster University, Hamilton, Ontario, Canada
| | - Jesse D. Pasternak
- Endocrine Surgery Section Head, Division of General Surgery, Department of Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Michael Au
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, McMaster University, Hamilton, Ontario, Canada
| | - Sameer Parpia
- Department of Health Research Methodology, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - J. E. M. (Ted) Young
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, McMaster University, Hamilton, Ontario, Canada
| | - Mohit Bhandari
- Department of Health Research Methodology, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
- Division of Orthopedic Surgery, Department of Surgery, McMaster University, Hamilton, Ontario, Canada
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4
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Heath A, Baio G, Manolopoulou I, Welton NJ. Value of Information for Clinical Trial Design: The Importance of Considering All Relevant Comparators. PHARMACOECONOMICS 2024; 42:479-486. [PMID: 38583100 DOI: 10.1007/s40273-024-01372-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/05/2024] [Indexed: 04/08/2024]
Abstract
Value of Information (VOI) analyses calculate the economic value that could be generated by obtaining further information to reduce uncertainty in a health economic decision model. VOI has been suggested as a tool for research prioritisation and trial design as it can highlight economically valuable avenues for future research. Recent methodological advances have made it increasingly feasible to use VOI in practice for research; however, there are critical differences between the VOI approach and the standard methods used to design research studies such as clinical trials. We aimed to highlight key differences between the research design approach based on VOI and standard clinical trial design methods, in particular the importance of considering the full decision context. We present two hypothetical examples to demonstrate that VOI methods are only accurate when (1) all feasible comparators are included in the decision model when designing research, and (2) all comparators are retained in the decision model once the data have been collected and a final treatment recommendation is made. Omitting comparators from either the design or analysis phase of research when using VOI methods can lead to incorrect trial designs and/or treatment recommendations. Overall, we conclude that incorrectly specifying the health economic model by ignoring potential comparators can lead to misleading VOI results and potentially waste scarce research resources.
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Affiliation(s)
- Anna Heath
- Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
- Department of Statistical Science, University College London, London, UK.
| | - Gianluca Baio
- Department of Statistical Science, University College London, London, UK
| | | | - Nicky J Welton
- Bristol Medical School, University of Bristol, Bristol, UK
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5
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Gumber L, Agbeleye O, Inskip A, Fairbairn R, Still M, Ouma L, Lozano-Kuehne J, Bardgett M, Isaacs JD, Wason JM, Craig D, Pratt AG. Operational complexities in international clinical trials: a systematic review of challenges and proposed solutions. BMJ Open 2024; 14:e077132. [PMID: 38626966 PMCID: PMC11029458 DOI: 10.1136/bmjopen-2023-077132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 02/27/2024] [Indexed: 04/19/2024] Open
Abstract
OBJECTIVE International trials can be challenging to operationalise due to incompatibilities between country-specific policies and infrastructures. The aim of this systematic review was to identify the operational complexities of conducting international trials and identify potential solutions for overcoming them. DESIGN Systematic review. DATA SOURCES Medline, Embase and Health Management Information Consortium were searched from 2006 to 30 January 2023. ELIGIBILITY CRITERIA All studies reporting operational challenges (eg, site selection, trial management, intervention management, data management) of conducting international trials were included. DATA EXTRACTION AND SYNTHESIS Search results were independently screened by at least two reviewers and data were extracted into a proforma. RESULTS 38 studies (35 RCTs, 2 reports and 1 qualitative study) fulfilled the inclusion criteria. The median sample size was 1202 (IQR 332-4056) and median number of sites was 40 (IQR 13-78). 88.6% of studies had an academic sponsor and 80% were funded through government sources. Operational complexities were particularly reported during trial set-up due to lack of harmonisation in regulatory approvals and in relation to sponsorship structure, with associated budgetary impacts. Additional challenges included site selection, staff training, lengthy contract negotiations, site monitoring, communication, trial oversight, recruitment, data management, drug procurement and distribution, pharmacy involvement and biospecimen processing and transport. CONCLUSIONS International collaborative trials are valuable in cases where recruitment may be difficult, diversifying participation and applicability. However, multiple operational and regulatory challenges are encountered when implementing a trial in multiple countries. Careful planning and communication between trials units and investigators, with an emphasis on establishing adequately resourced cross-border sponsorship structures and regulatory approvals, may help to overcome these barriers and realise the benefits of the approach. OPEN SCIENCE FRAMEWORK REGISTRATION NUMBER: osf-registrations-yvtjb-v1.
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Affiliation(s)
- Leher Gumber
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Northumbria Healthcare NHS Foundation Trust, Northumbria, UK
| | - Opeyemi Agbeleye
- NIHR Innovation Observatory, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Alex Inskip
- NIHR Innovation Observatory, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Ross Fairbairn
- NIHR Innovation Observatory, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Madeleine Still
- NIHR Innovation Observatory, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Luke Ouma
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Jingky Lozano-Kuehne
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Michelle Bardgett
- Newcastle Clinical Trials Unit, Newcastle University, Newcastle upon Tyne, UK
| | - John D Isaacs
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Musculoskeletal Unit, Newcastle Upon Tyne Hospitals NHS Trust, Newcastle Upon Tyne, UK
| | - James Ms Wason
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Dawn Craig
- NIHR Innovation Observatory, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Arthur G Pratt
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Musculoskeletal Unit, Newcastle Upon Tyne Hospitals NHS Trust, Newcastle Upon Tyne, UK
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Duan XP, Qin BD, Jiao XD, Liu K, Wang Z, Zang YS. New clinical trial design in precision medicine: discovery, development and direction. Signal Transduct Target Ther 2024; 9:57. [PMID: 38438349 PMCID: PMC10912713 DOI: 10.1038/s41392-024-01760-0] [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: 11/30/2023] [Revised: 01/25/2024] [Accepted: 01/29/2024] [Indexed: 03/06/2024] Open
Abstract
In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.
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Affiliation(s)
- Xiao-Peng Duan
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Bao-Dong Qin
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Xiao-Dong Jiao
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Ke Liu
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Zhan Wang
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Yuan-Sheng Zang
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China.
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7
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Falkenbach F, Steuber T, Graefen M. [Local therapies for oligometastatic hormone-sensitive prostate cancer]. UROLOGIE (HEIDELBERG, GERMANY) 2024; 63:215-224. [PMID: 38329485 DOI: 10.1007/s00120-024-02280-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/15/2024] [Indexed: 02/09/2024]
Abstract
BACKGROUND Oligometastatic, hormone-sensitive prostate cancer (omHSPC) is increasingly diagnosed due to the implementation of molecular imaging. OmHSPC is mostly defined as a maximum of four bone metastases without visceral metastases on conventional imaging. OBJECTIVES This study highlights the existing evidence regarding local treatment of omHSPC, taking into account molecular imaging and modern therapies. MATERIALS AND METHODS Narrative review article based on expert consensus and national/international guideline recommendations, supported by a nonsystematic literature search in PubMed (MEDLINE). The authors consider the cited studies as the most significant works in this regard and these were selected to illustrate developments and fundamental concepts, without claiming completeness. RESULTS Initially, the STAMPEDE study prospectively demonstrated an oncologic benefit of radiotherapy (RT) to the prostate in addition to androgen deprivation therapy for omHSPC. At 3 years, overall survival (OS) was 81% with RT versus 73% without RT (hazard ratio [HR] 0.68; 95% confidence interval [CI] 0.52-0.90; p = 0.007). However, this benefit was not observed in polymetastatic HSPC (HR 1.07; 95% CI 0.90-1.28; p = 0.4). In a study by Dai et al., local therapy for omHSPC was performed surgically in 85% of cases, also demonstrating an OS advantage (HR 0.44; 95% CI 0.24-0.81; p = 0.008). CONCLUSION OmHSPC should be treated using adjunctive RT. Preliminary prospective evidence shows comparable efficacy with prostatectomy. Modern systemic combination therapies challenge the role of local therapy.
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Affiliation(s)
- Fabian Falkenbach
- Martini-Klinik Prostatakarzinomzentrum, Universitätsklinikum Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Deutschland
| | - Thomas Steuber
- Martini-Klinik Prostatakarzinomzentrum, Universitätsklinikum Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Deutschland
- Klinik und Poliklinik für Urologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Deutschland
| | - Markus Graefen
- Martini-Klinik Prostatakarzinomzentrum, Universitätsklinikum Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Deutschland.
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8
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Mei H, Xie J, Qin Y, Li Y. Network and covariate adjusted response-adaptive design for binary response. Stat Med 2023; 42:5369-5388. [PMID: 37750440 DOI: 10.1002/sim.9915] [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] [Received: 01/27/2023] [Revised: 08/31/2023] [Accepted: 09/13/2023] [Indexed: 09/27/2023]
Abstract
Randomization is a distinguishing feature of clinical trials for unbiased assessment of treatment efficacy. With a growing demand for more flexible and efficient randomization schemes and motivated by the idea of adaptive design, in this article we propose the network and covariate adjusted response-adaptive (NCARA) design that can concurrently manage three challenges: (1) maximizing benefits of a trial by assigning more patients to the superior treatment group randomly; (2) balancing social network ties across treatment arms to eliminate potential network interference; and (3) ensuring balance of important covariates, such as age, gender, and other potential confounders. We conduct simulation with different network structures and a variety of parameter settings. It is observed that the NCARA design outperforms four alternative randomization designs in solving the above-mentioned problems and has comparable power and type I error for detecting true difference between treatment groups. In addition, we conduct real data analysis to implement the new design in two clinical trials. Compared to equal randomization (the original design utilized in the trials), the NCARA design slightly increases power, largely increases the percentage of patients assigned to the better-performing group, and significantly improves network and covariate balances. It is also noted that the advantages of the NCARA design are augmented when the sample size is small and the level of network interference is high. In summary, the proposed NCARA design assists researchers in conducting clinical trials with high-quality and high-efficiency.
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Affiliation(s)
- Hao Mei
- Center for Applied Statistics, Renmin University of China, Beijing, China
- School of Statistics, Renmin University of China, Beijing, China
| | - Jiaxin Xie
- School of Statistics, Renmin University of China, Beijing, China
| | - Yichen Qin
- Department of Operations, Business Analytics and Information Systems, University of Cincinnati, Cincinnati, Ohio, USA
| | - Yang Li
- Center for Applied Statistics, Renmin University of China, Beijing, China
- School of Statistics, Renmin University of China, Beijing, China
- Statistical Consulting Center, Renmin University of China, Beijing, China
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Le Tourneau C, André F, Helland Å, Mileshkin L, Minnaard W, Schiel A, Taskén K, Thomas DM, Veronese ML, Durán-Pacheco G, Leyens L, Rufibach K, Thomas M, Krämer A. Modified study designs to expand treatment options in personalised oncology: a multistakeholder view. Eur J Cancer 2023; 194:113278. [PMID: 37820553 DOI: 10.1016/j.ejca.2023.113278] [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: 05/16/2023] [Revised: 07/31/2023] [Accepted: 08/01/2023] [Indexed: 10/13/2023]
Abstract
Personalised oncology, whereby patients are given therapies based on their molecular tumour profile, is rapidly becoming an essential part of optimal clinical care, at least partly facilitated by recent advances in next-generation sequencing-based technology using liquid- and tissue-based biopsies. Consequently, clinical trials have shifted in approach, from traditional studies evaluating cytotoxic chemotherapy in largely histology-based populations to modified, biomarker-driven studies (e.g. basket, umbrella, platform) of molecularly guided therapies and cancer immunotherapies in selected patient subsets. Such modified study designs may assess, within the same trial structure, multiple cancer types and treatments, and should incorporate a multistakeholder perspective. This is key to generating complementary, fit-for-purpose and timely evidence for molecularly guided therapies that can be used as proof-of-concept to inform further study designs, lead to approval by regulatory authorities and be used as confirmation of clinical benefit for health technology assessment bodies. In general, the future of cancer clinical trials requires a framework for the application of innovative technologies and dynamic design methodologies, in order to efficiently transform scientific discoveries into clinical utility. Next-generation, modified studies that involve the joint efforts of all key stakeholders will offer individualised strategies that ultimately contribute to globalised knowledge and collective learning. In this review, we outline the background and purpose of such modified study designs and detail key aspects from a multistakeholder perspective. We also provide methodological considerations for designing the studies and highlight how insights from already-ongoing studies may address current challenges and opportunities in the era of personalised oncology.
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Affiliation(s)
- Christophe Le Tourneau
- Department of Drug Development and Innovation (D3i), Institut Curie, INSERM U900 Research Unit, Paris-Saclay University, Paris, France
| | | | - Åslaug Helland
- Division of Cancer Medicine, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Linda Mileshkin
- Peter MacCallum Cancer Centre and Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia
| | | | | | - Kjetil Taskén
- Division of Cancer Medicine, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - David M Thomas
- Garvan Institute of Medical Research, Darlinghurst, Australia
| | | | | | - Lada Leyens
- F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | | | | | - Alwin Krämer
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center (DKFZ) and Department of Internal Medicine V, University of Heidelberg, Heidelberg, Germany.
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Vale CL, Fisher DJ, Godolphin PJ, Rydzewska LH, Boher JM, Burdett S, Chen YH, Clarke NW, Fizazi K, Gravis G, James ND, Liu G, Matheson D, Murphy L, Oldroyd RE, Parmar MKB, Rogozinska E, Sfumato P, Sweeney CJ, Sydes MR, Tombal B, White IR, Tierney JF. Which patients with metastatic hormone-sensitive prostate cancer benefit from docetaxel: a systematic review and meta-analysis of individual participant data from randomised trials. Lancet Oncol 2023; 24:783-797. [PMID: 37414011 PMCID: PMC7616350 DOI: 10.1016/s1470-2045(23)00230-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/19/2023] [Accepted: 05/10/2023] [Indexed: 07/08/2023]
Abstract
BACKGROUND Adding docetaxel to androgen deprivation therapy (ADT) improves survival in patients with metastatic, hormone-sensitive prostate cancer, but uncertainty remains about who benefits most. We therefore aimed to obtain up-to-date estimates of the overall effects of docetaxel and to assess whether these effects varied according to prespecified characteristics of the patients or their tumours. METHODS The STOPCAP M1 collaboration conducted a systematic review and meta-analysis of individual participant data. We searched MEDLINE (from database inception to March 31, 2022), Embase (from database inception to March 31, 2022), the Cochrane Central Register of Controlled Trials (from database inception to March 31, 2022), proceedings of relevant conferences (from Jan 1, 1990, to Dec 31, 2022), and ClinicalTrials.gov (from database inception to March 28, 2023) to identify eligible randomised trials that assessed docetaxel plus ADT compared with ADT alone in patients with metastatic, hormone-sensitive prostate cancer. Detailed and updated individual participant data were requested directly from study investigators or through relevant repositories. The primary outcome was overall survival. Secondary outcomes were progression-free survival and failure-free survival. Overall pooled effects were estimated using an adjusted, intention-to-treat, two-stage, fixed-effect meta-analysis, with one-stage and random-effects sensitivity analyses. Missing covariate values were imputed. Differences in effect by participant characteristics were estimated using adjusted two-stage, fixed-effect meta-analysis of within-trial interactions on the basis of progression-free survival to maximise power. Identified effect modifiers were also assessed on the basis of overall survival. To explore multiple subgroup interactions and derive subgroup-specific absolute treatment effects we used one-stage flexible parametric modelling and regression standardisation. We assessed the risk of bias using the Cochrane Risk of Bias 2 tool. This study is registered with PROSPERO, CRD42019140591. FINDINGS We obtained individual participant data from 2261 patients (98% of those randomised) from three eligible trials (GETUG-AFU15, CHAARTED, and STAMPEDE trials), with a median follow-up of 72 months (IQR 55-85). Individual participant data were not obtained from two additional small trials. Based on all included trials and patients, there were clear benefits of docetaxel on overall survival (hazard ratio [HR] 0·79, 95% CI 0·70 to 0·88; p<0·0001), progression-free survival (0·70, 0·63 to 0·77; p<0·0001), and failure-free survival (0·64, 0·58 to 0·71; p<0·0001), representing 5-year absolute improvements of around 9-11%. The overall risk of bias was assessed to be low, and there was no strong evidence of differences in effect between trials for all three main outcomes. The relative effect of docetaxel on progression-free survival appeared to be greater with increasing clinical T stage (pinteraction=0·0019), higher volume of metastases (pinteraction=0·020), and, to a lesser extent, synchronous diagnosis of metastatic disease (pinteraction=0·077). Taking into account the other interactions, the effect of docetaxel was independently modified by volume and clinical T stage, but not timing. There was no strong evidence that docetaxel improved absolute effects at 5 years for patients with low-volume, metachronous disease (-1%, 95% CI -15 to 12, for progression-free survival; 0%, -10 to 12, for overall survival). The largest absolute improvement at 5 years was observed for those with high-volume, clinical T stage 4 disease (27%, 95% CI 17 to 37, for progression-free survival; 35%, 24 to 47, for overall survival). INTERPRETATION The addition of docetaxel to hormone therapy is best suited to patients with poorer prognosis for metastatic, hormone-sensitive prostate cancer based on a high volume of disease and potentially the bulkiness of the primary tumour. There is no evidence of meaningful benefit for patients with metachronous, low-volume disease who should therefore be managed differently. These results will better characterise patients most and, importantly, least likely to gain benefit from docetaxel, potentially changing international practice, guiding clinical decision making, better informing treatment policy, and improving patient outcomes. FUNDING UK Medical Research Council and Prostate Cancer UK.
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Affiliation(s)
- Claire L Vale
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK.
| | - David J Fisher
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Peter J Godolphin
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Larysa H Rydzewska
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | | | - Sarah Burdett
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Yu-Hui Chen
- Department of Biostatistics and Computational Biology ECOG-ACRIN Cancer Research Group, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Noel W Clarke
- Department of Surgery and Department of Urology, The Christie and Salford Royal Hospitals, Manchester, UK
| | - Karim Fizazi
- Department of Cancer Medicine, Institut Gustave Roussy, Paris, France
| | - Gwenaelle Gravis
- Department of Medical Oncology, Institut Paoli-Calmettes, Marseille, France
| | | | - Glenn Liu
- Department of Urology, Department of Medicine, University of Wisconsin Carbone Cancer Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - David Matheson
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Laura Murphy
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Robert E Oldroyd
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Mahesh K B Parmar
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Ewelina Rogozinska
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Patrick Sfumato
- Biostatistics Unit, Institut Paoli-Calmettes, Marseille, France
| | | | - Matthew R Sydes
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Bertrand Tombal
- Institut de Recherche Clinique, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Ian R White
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Jayne F Tierney
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
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11
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Pericàs JM, Tacke F, Anstee QM, Di Prospero NA, Kjær MS, Mesenbrink P, Koenig F, Genescà J, Ratziu V. Platform trials to overcome major shortcomings of traditional clinical trials in non-alcoholic steatohepatitis? Pros and cons. J Hepatol 2023; 78:442-447. [PMID: 36216134 DOI: 10.1016/j.jhep.2022.09.021] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/07/2022] [Accepted: 09/20/2022] [Indexed: 12/04/2022]
Abstract
Non-alcoholic fatty liver disease is a condition that affects 25% of the population. Non-alcoholic steatohepatitis (NASH) is a progressive form of the disease that can lead to severe complications such as cirrhosis and hepatocellular carcinoma. Despite its high prevalence, no drugs are currently approved for the treatment of NASH. The drug development pipeline in NASH is very active, yet most assets do not progress to phase III trials and those that do reach phase III often fail to achieve the endpoints necessary for approval by regulatory agencies. Amongst other reasons, the methodological and operational features of traditional clinical trials in NASH might impede optimal drug development. In this regard, platform trials might be an attractive complement or alternative to conventional clinical trials. Platform trials use a master protocol which enables evaluation of multiple investigational medicinal products concurrently or sequentially with a single, shared control arm. Through Bayesian interim analyses, these trials allow for early exit of drugs from the trial based on success or futility, while providing participants better chances of receiving active compounds through adaptive randomisation. Overall, platform trials represent an alternative for patients, pharmaceutical companies, and clinicians in the quest to accelerate the approval of pharmacologic treatments for NASH.
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Affiliation(s)
- Juan M Pericàs
- Liver Unit, Internal Medicine Department, Vall d'Hebron University Hospital, Vall d'Hebron Institute for Research (VHIR), Universitat Autònoma de Barcelona, Centros de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas (CIBERehd), Barcelona, Spain.
| | - Frank Tacke
- Department of Hepatology and Gastroenterology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Quentin M Anstee
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NIHR Biomedical Research Centre, Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
| | | | | | - Peter Mesenbrink
- Analytics Department, Novartis Pharmaceuticals Corporation, East Hanover, New Jersey, USA
| | - Franz Koenig
- Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Joan Genescà
- Liver Unit, Internal Medicine Department, Vall d'Hebron University Hospital, Vall d'Hebron Institute for Research (VHIR), Universitat Autònoma de Barcelona, Centros de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas (CIBERehd), Barcelona, Spain
| | - Vlad Ratziu
- Department of Hepatology, Pitié-Salpêtrière Hospital, University Paris 6, France
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12
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Heynemann S, Lipworth W, McLachlan SA, Philip J, John T, Kerridge I. When research becomes practice: the concept of the therapeutic misconception and challenges to consent in clinical trials. Intern Med J 2023; 53:271-274. [PMID: 36822606 DOI: 10.1111/imj.16015] [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: 09/30/2022] [Accepted: 12/13/2022] [Indexed: 02/25/2023]
Abstract
Many factors influence patients' decisions to participate in clinical trials. For many, the primary motivation is the possibility that they might derive some benefit from participation. This is particularly true for patients with limited treatment options, such as patients with advanced cancer. While this is not surprising, it is potentially problematic if patients fail to recognise the distinction between research and clinical care (a phenomenon known as the 'therapeutic misconception'). This is becoming increasingly problematic as clinical trial designs become more complex, as clinical trials become more embedded in routine clinical care, and as trials are increasingly used by patients and clinicians to access new diagnostic platforms and therapies. We outline some of these recent trends, focusing on the cancer clinical trials landscape as this provides a good case study of the phenomenon. We conclude by making preliminary suggestions that changes to the consent process, perhaps using 'dynamic consent' platforms, might help to mitigate the therapeutic misconception and note the need for further research to guide strategies for improving communication and decision-making.
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Affiliation(s)
- Sarah Heynemann
- Sydney Health Ethics, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.,Department of Medical Oncology, St Vincent's Hospital, Melbourne, Victoria, Australia
| | - Wendy Lipworth
- Department of Philosophy, Macquarie University, New South Wales, Sydney, Australia
| | - Sue-Anne McLachlan
- Department of Medical Oncology, St Vincent's Hospital, Melbourne, Victoria, Australia.,Department of Medicine, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jennifer Philip
- Department of Medicine, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia.,Department of Palliative Care, St Vincent's Hospital, Melbourne, Victoria, Australia.,Department of Palliative Care, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Tom John
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.,Sir Peter MacCallum Department of Medical Oncology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Ian Kerridge
- Sydney Health Ethics, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.,Department of Philosophy, Macquarie University, New South Wales, Sydney, Australia.,Haematology Department, Royal North Shore Hospital, Sydney, New South Wales, Australia
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13
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Mukherjee A, Coad DS, Jana S. Covariate-adjusted response-adaptive designs for censored survival responses. J Stat Plan Inference 2023. [DOI: 10.1016/j.jspi.2023.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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14
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Fisher DJ, Burdett S, Vale C, White IR, Tierney JF. Duplicated network meta-analysis in advanced prostate cancer: a case study and recommendations for change. Syst Rev 2022; 11:274. [PMID: 36527153 PMCID: PMC9755764 DOI: 10.1186/s13643-022-02137-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 11/19/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Research overlap and duplication is a recognised problem in the context of both pairwise and network systematic reviews and meta-analyses. As a case study, we carried out a scoping review to identify and examine duplicated network meta-analyses (NMAs) in a specific disease setting where several novel therapies have recently emerged: hormone-sensitive metastatic prostate cancer (mHSPC). METHODS MEDLINE and EMBASE were systematically searched, in January 2020, for indirect or mixed treatment comparisons or network meta-analyses of the systemic treatments docetaxel and abiraterone acetate in the mHSPC setting, with a time-to-event outcome reported on the hazard-ratio scale. Eligibility decisions were made, and data extraction performed, by two independent reviewers. RESULTS A total of 13 eligible reviews were identified, analysing between 3 and 8 randomised comparisons, and comprising between 1773 and 7844 individual patients. Although the included trials and treatments showed a high degree of overlap, we observed considerable variation between identified reviews in terms of review aims, eligibility criteria and included data, statistical methodology, reporting and inference. Furthermore, crucial methodological details and specific source data were often unclear. CONCLUSIONS AND RECOMMENDATIONS Variation across duplicated NMAs, together with reporting inadequacies, may compromise identification of best-performing treatments. Particularly in fast-moving fields, review authors should be aware of all relevant studies, and of other reviews with potential for overlap or duplication. We recommend that review protocols be published in advance, with greater clarity regarding the specific aims or scope of the project, and that reports include information on how the work builds upon existing knowledge. Source data and results should be clearly and completely presented to allow unbiased interpretation.
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Affiliation(s)
- David J Fisher
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, Unversity College London, 90 High Holborn, London, WC1V 6LJ, UK.
| | - Sarah Burdett
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, Unversity College London, 90 High Holborn, London, WC1V 6LJ, UK
| | - Claire Vale
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, Unversity College London, 90 High Holborn, London, WC1V 6LJ, UK
| | - Ian R White
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, Unversity College London, 90 High Holborn, London, WC1V 6LJ, UK
| | - Jayne F Tierney
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, Unversity College London, 90 High Holborn, London, WC1V 6LJ, UK
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15
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Park JR, Villablanca JG, Hero B, Kushner BH, Wheatley K, Beiske KH, Ladenstein RL, Baruchel S, Macy ME, Moreno L, Seibel NL, Pearson AD, Matthay KK, Valteua-Couanet D. Early-phase clinical trial eligibility and response evaluation criteria for refractory, relapsed, or progressive neuroblastoma: A consensus statement from the National Cancer Institute Clinical Trials Planning Meeting. Cancer 2022; 128:3775-3783. [PMID: 36101004 PMCID: PMC9614386 DOI: 10.1002/cncr.34445] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 06/13/2022] [Accepted: 07/18/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND International standardized criteria for eligibility, evaluable disease sites, and disease response assessment in patients with refractory, progressive, or relapsed high-risk neuroblastoma enrolled in early-phase clinical trials are lacking. METHODS A National Cancer Institute-sponsored Clinical Trials Planning Meeting was convened to develop an international consensus to refine the tumor site eligibility criteria and evaluation of disease response for early-phase clinical trials in children with high-risk neuroblastoma. RESULTS Standardized data collection of patient and disease characteristics (including specified genomic data), eligibility criteria, a definition of evaluable disease, and response evaluations for primary and metastatic sites of disease were developed. Eligibility included two distinct patient groups: progressive disease and refractory disease. The refractory disease group was subdivided into responding persistent disease and stable persistent disease to better capture the clinical heterogeneity of refractory neuroblastoma. Requirements for defining disease evaluable for a response assessment were provided; they included requirements for biopsy to confirm viable neuroblastoma and/or ganglioneuroblastoma in those patients with soft tissue or bone disease not avid for iodine-123 meta-iodobenzylguanidine. Standardized evaluations for response components and time intervals for response evaluations were established. CONCLUSIONS The use of international consensus eligibility, evaluability, and response criteria for early-phase clinical studies will facilitate the collection of comparable data across international trials and promote more rapid identification of effective treatment regimens for high-risk neuroblastoma.
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Affiliation(s)
- Julie R. Park
- Seattle Children’s Hospital and Department of Pediatrics University of Washington School of Medicine, Seattle WA, 98105
| | - Judith G. Villablanca
- Children’s Hospital Los Angeles and Department of Pediatrics, USC Keck School of Medicine, Los Angeles, CA
| | - Barbara Hero
- Children’s Hospital and University of Cologne, D 50924 Koeln, Germany
| | | | | | - Klaus H. Beiske
- Oslo University Hospital, Department of Pathology, Oslo, Norway
| | - Ruth L. Ladenstein
- Children’s Cancer Research Institute, St Anna Children’s Hospital, Vienna, Austria
| | | | - Margaret E. Macy
- Department of Pediatrics, University of Colorado Anschutz Medical Campus and Children’s Hospital Colorado, Aurora, Colorado
| | - Lucas Moreno
- Division of Paediatric Haematology and Oncology, Vall d’Hebron Hospital Universitari, Barcelona, Spain
| | - Nita L. Seibel
- Clinical Investigations Branch, National Cancer Institute, Bethesda, MD 20892
| | - Andrew D. Pearson
- Divisions of Cancer Therapeutics and Clinical Studies, Institute of Cancer Research and Children and Young People’s Unit, The Royal Marsden NHS Foundation Trust, Sutton, Surrey UK (Retired)
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16
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Kong BY, Sim HW, Barnes EH, Nowak AK, Hovey EJ, Jeffree R, Harrup R, Parkinson J, Gan HK, Pinkham MB, Yip S, Hall M, Tu E, Carter C, Koh ES, Lwin Z, Dowling A, Simes JS, Gedye C. Multi-Arm GlioblastoMa Australasia (MAGMA): protocol for a multiarm randomised clinical trial for people affected by glioblastoma. BMJ Open 2022; 12:e058107. [PMID: 36104135 PMCID: PMC10441685 DOI: 10.1136/bmjopen-2021-058107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 08/12/2022] [Indexed: 11/04/2022] Open
Abstract
INTRODUCTION Glioblastoma (GBM) is the most common malignant primary central nervous system cancer in adults. The objective of the Multi-Arm GlioblastoMa Australasia (MAGMA) trial is to test hypotheses in real world setting to improve survival of people with GBM. Initial experimental arms are evaluating the effectiveness of interventions in newly diagnosed GBM (ndGBM). This study will compare maximal surgical resection followed by chemoradiotherapy plus adjuvant chemotherapy for 6 months with the addition of (1) 'neoadjuvant' chemotherapy beginning as soon as possible after surgery and/or (2) adjuvant chemotherapy continued until progression within the same study platform. METHODS AND ANALYSIS MAGMA will establish a platform for open-label, multiarm, multicentre randomised controlled testing of treatments for GBM. The study began recruiting in September 2020 and recruitment to the initial two interventions in MAGMA is expected to continue until September 2023.Adults aged ≥18 years with ndGBM will be given the option of undergoing randomisation to each study intervention separately, thereby giving rise to a partial factorial design, with two separate randomisation time points, one for neoadjuvant therapy and one for extended therapy. Patients will have the option of being randomised at each time point or continuing on with standard treatment.The primary outcome for the study is overall survival from the date of initial surgery until death from any cause. Secondary outcomes include progression-free survival, time to first non-temozolomide treatment, overall survival from each treatment randomisation, clinically significant toxicity as measured by grade 3 or 4 adverse events and health-related quality-of-life measures. Tertiary outcomes are predictive/prognostic biomarkers and health utilities and incremental cost-effectiveness ratio.The primary analysis of overall survival will be performed separately for each study intervention according to the intention to treat principle on all patients randomised to each study intervention. ETHICS AND DISSEMINATION The study (Protocol version 2.0 dated 23 November 2020) was approved by a lead Human Research Ethics Committee (Sydney Local Health District: 2019/ETH13297). The study will be conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice. TRIAL REGISTRATION NUMBER ACTRN12620000048987.
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Affiliation(s)
- Benjamin Y Kong
- NHMRC Clinical Trials Centre, Camperdown, New South Wales, Australia
- Department of Medical Oncology, Royal North Shore Hospital, St Leonards, New South Wales, Australia
| | - Hao-Wen Sim
- NHMRC Clinical Trials Centre, Camperdown, New South Wales, Australia
- St Vincent's Clinical School, University of New South Wales, Sydney, New South Wales, Australia
- Department of Medical Oncology, The Kinghorn Cancer Centre, Darlinghurst, NSW, Australia
- Department of Medical Oncology, Chris O'Brien Lifehouse, Camperdown, New South Wales, Australia
| | | | - Anna K Nowak
- Medical School, The University of Western Australia, Crawley, Western Australia, Australia
- Department of Medical Oncology, Sir Charles Gairdner Hospital, Nedlands, Perth, Australia
| | - Elizabeth J Hovey
- Department of Medical Oncology, Nelune Comprehensive Cancer Centre, Prince of Wales Hospital, Randwick, New South Wales, Australia
- Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Rosalind Jeffree
- Department of Neurosurgery, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia
| | - Rosemary Harrup
- Cancer and Blood Services, Royal Hobart Hospital, Hobart, Tasmania, Australia
| | - Jonathon Parkinson
- Department of Neurosurgery, Royal North Shore Hospital, St Leonards, New South Wales, Australia
| | - Hui K Gan
- Olivia Newton-John Cancer Research Institute, Austin Health, Heidelberg, Victoria, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, Victoria, Australia
- Department of Medicine, University of Melbourne Victorian Comprehensive Cancer Centre, Parkville, Victoria, Australia
- Department of Medical Oncology, Olivia Newton-John Cancer and Wellness Centre, Austin Health, Heidelberg, VIC, Australia
| | - Mark B Pinkham
- Department of Radiation Oncology, Princess Alexandra Hospital, Woolloongabba, Queensland, Australia
- School of Clinical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Sonia Yip
- NHMRC Clinical Trials Centre, Camperdown, New South Wales, Australia
| | - Merryn Hall
- NHMRC Clinical Trials Centre, Camperdown, New South Wales, Australia
| | - Emily Tu
- NHMRC Clinical Trials Centre, Camperdown, New South Wales, Australia
| | - Candace Carter
- NHMRC Clinical Trials Centre, Camperdown, New South Wales, Australia
| | - Eng-Siew Koh
- Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
- Radiation Oncology, Liverpool Cancer Therapy Centre, Liverpool, New South Wales, Australia
- Collaboration for Cancer Outcomes, Research and Evaluation, Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Zarnie Lwin
- Cancer Care Services, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia
- School of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Anthony Dowling
- Department of Medicine, University of Melbourne Victorian Comprehensive Cancer Centre, Parkville, Victoria, Australia
- Department of Medical Oncology, St Vincent's Hospital Melbourne Pty Ltd, Fitzroy, Victoria, Australia
| | - John S Simes
- NHMRC Clinical Trials Centre, Camperdown, New South Wales, Australia
- Department of Medical Oncology, Chris O'Brien Lifehouse, Camperdown, New South Wales, Australia
| | - Craig Gedye
- Department of Medical Oncology, Calvary Mater Newcastle, Waratah, New South Wales, Australia
- Hunter Medical Research Institute, New Lambton, New South Wales, Australia
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17
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Love SB, Cafferty F, Snowdon C, Carty K, Savage J, Pallmann P, McParland L, Brown L, Masters L, Schiavone F, Hague D, Townsend S, Amos C, South A, Sturgeon K, Langley R, Maughan T, James N, Hall E, Kernaghan S, Bliss J, Turner N, Tutt A, Yap C, Firth C, Kong A, Mehanna H, Watts C, Hills R, Thomas I, Copland M, Bell S, Sebag-Montefiore D, Jones R, Parmar MKB, Sydes MR. Practical guidance for running late-phase platform protocols for clinical trials: lessons from experienced UK clinical trials units. Trials 2022; 23:757. [PMID: 36068599 PMCID: PMC9449272 DOI: 10.1186/s13063-022-06680-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 08/20/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Late-phase platform protocols (including basket, umbrella, multi-arm multi-stage (MAMS), and master protocols) are generally agreed to be more efficient than traditional two-arm clinical trial designs but are not extensively used. We have gathered the experience of running a number of successful platform protocols together to present some operational recommendations. METHODS Representatives of six UK clinical trials units with experience in running late-phase platform protocols attended a 1-day meeting structured to discuss various practical aspects of running these trials. We report and give guidance on operational aspects which are either harder to implement compared to a traditional late-phase trial or are specific to platform protocols. RESULTS We present a list of practical recommendations for trialists intending to design and conduct late-phase platform protocols. Our recommendations cover the entire life cycle of a platform trial: from protocol development, obtaining funding, and trial set-up, to a wide range of operational and regulatory aspects such as staffing, oversight, data handling, and data management, to the reporting of results, with a particular focus on communication with trial participants and stakeholders as well as public and patient involvement. DISCUSSION Platform protocols enable many questions to be answered efficiently to the benefit of patients. Our practical lessons from running platform trials will support trial teams in learning how to run these trials more effectively and efficiently.
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Affiliation(s)
- Sharon B. Love
- MRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ UK
| | - Fay Cafferty
- The Institute of Cancer Research, London, SW7 3RP UK
| | | | - Karen Carty
- Cancer Research UK Clinical Trials Unit, Level 0 The Beatson West of Scotland Cancer Centre, 1053 Great Western Road, Glasgow, G12 0YN UK
| | - Joshua Savage
- Cancer Research UK Clinical Trials Unit (CRCTU), Institute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
| | - Philip Pallmann
- Centre for Trials Research, Cardiff University, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS UK
| | | | - Louise Brown
- MRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ UK
| | - Lindsey Masters
- MRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ UK
| | | | - Dominic Hague
- MRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ UK
| | - Stephen Townsend
- MRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ UK
| | - Claire Amos
- MRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ UK
| | - Annabelle South
- MRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ UK
| | - Kate Sturgeon
- MRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ UK
| | - Ruth Langley
- MRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ UK
| | | | | | - Emma Hall
- The Institute of Cancer Research, London, SW7 3RP UK
| | | | - Judith Bliss
- The Institute of Cancer Research, London, SW7 3RP UK
| | - Nick Turner
- The Institute of Cancer Research, London, SW7 3RP UK
| | - Andrew Tutt
- The Institute of Cancer Research, London, SW3 6JB UK
| | - Christina Yap
- The Institute of Cancer Research, London, SW7 3RP UK
- Cancer Research UK Clinical Trials Unit, Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT UK
| | - Charlotte Firth
- Cancer Research UK Clinical Trials Unit, Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT UK
| | - Anthony Kong
- Comprehensive Cancer Centre, King’s College London, Guy’s Campus, New Hunt’s House, Room 2.36b, London, SE1 1UL UK
| | - Hisham Mehanna
- Institute for Head and Neck Studies and Education, University of Birmingham, Birmingham, B15 2TT UK
| | - Colin Watts
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT UK
| | - Robert Hills
- Doll Building, CTSU, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF UK
| | - Ian Thomas
- Centre for Trials Research, Cardiff University, Neuadd Meirionnydd, Heath Park Way, Cardiff, CF14 4YS UK
| | - Mhairi Copland
- Paul O’Gorman Research Centre, Gartnavel General Hospital, Glasgow, G12 0YN UK
| | - Sue Bell
- Clinical Trials Research Unit (CTRU), Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, LS2 9JT UK
| | | | - Robert Jones
- Beatson West of Scotland Cancer Centre, Glasgow, UK
| | | | - Matthew R. Sydes
- MRC Clinical Trials Unit at UCL, 90 High Holborn, London, WC1V 6LJ UK
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18
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Halabi S, Zhou J, He Y, Bressler LR, Hernandez AF, Turner NA, Hong H. Landscape of coronavirus disease 2019 clinical trials: New frontiers and challenges. Clin Trials 2022; 19:561-572. [PMID: 35786000 DOI: 10.1177/17407745221105106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND/AIM The number of coronavirus disease 2019 deaths and cases continues to increase globally. Novel therapies are urgently needed to treat patients with coronavirus disease 2019. We sought to provide a critical review of trials designed during the coronavirus disease 2019 pandemic. Our primary goal was to provide a critical review of the landscape of clinical trials designed to address the coronavirus disease 2019 pandemic. Specifically, we were interested in assessing the design of phase II/III and phase III interventional trials. METHODS We utilized the ClinicalTrials.gov database to include trials registered between 1 December 2019 and 11 April 2021 to survey the current landscape of clinical trials for coronavirus disease 2019. Variables extracted included: National Clinical Trial number, title, location, sponsor, study type, start date, completion date, gender group, age group, primary outcome, secondary outcome, overall status, and associated references. RESULTS About 57% of studies were interventional, 14.5% were phase III trials, and the majority of the therapeutic trials included hospitalized patients. There were 52 primary composite outcomes and 285 unique interventions spanning 10 drug classes. The outcomes, disease severity, and comparators varied substantially across trials, and the trials were often too small to be definitive. CONCLUSION These findings are relevant as we strongly advocate for global coordination of efforts through the use of common platforms that enable harmonizing of endpoints, collection of common key variables and clear definition of disease severity to have clinically meaningful results from clinical trials.
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Affiliation(s)
- Susan Halabi
- Department of Biostatistics and Bioinformatics, Duke Health, Durham, NC, USA.,Duke Clinical Research Institute, Duke Health, Durham, NC, USA
| | - Jinyi Zhou
- Department of Biostatistics and Bioinformatics, Duke Health, Durham, NC, USA
| | - Yijie He
- Department of Biostatistics and Bioinformatics, Duke Health, Durham, NC, USA
| | | | | | - Nicholas A Turner
- Division of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA
| | - Hwanhee Hong
- Department of Biostatistics and Bioinformatics, Duke Health, Durham, NC, USA.,Duke Clinical Research Institute, Duke Health, Durham, NC, USA
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19
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Park JJH, Sharif B, Harari O, Dron L, Heath A, Meade M, Zarychanski R, Lee R, Tremblay G, Mills EJ, Jemiai Y, Mehta C, Wathen JK. Economic Evaluation of Cost and Time Required for a Platform Trial vs Conventional Trials. JAMA Netw Open 2022; 5:e2221140. [PMID: 35819785 PMCID: PMC9277502 DOI: 10.1001/jamanetworkopen.2022.21140] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
IMPORTANCE Platform trial design allows the introduction of new interventions after the trial is initiated and offers efficiencies to clinical research. However, limited guidance exists on the economic resources required to establish and maintain platform trials. OBJECTIVE To compare cost (US dollars) and time requirements of conducting a platform trial vs a series of conventional (nonplatform) trials using a real-life example. DESIGN, SETTING, AND PARTICIPANTS For this economic evaluation, an online survey was administered to a group of international experts (146 participants) with publication records of platform trials to elicit their opinions on cost and time to set up and conduct platform, multigroup, and 2-group trials. Using the reported entry dates of 10 interventions into Systemic Therapy in Advancing Metastatic Prostate Cancer: Evaluation of Drug Efficacy, the longest ongoing platform trial, 3 scenarios were designed involving a single platform trial (scenario 1), 1 multigroup followed by 5 2-group trials (scenario 2), and a series of 10 2-group trials (scenario 3). All scenarios started with 5 interventions, then 5 more interventions were either added to the platform or evaluated independently. Simulations with the survey results as inputs were used to compare the platform vs conventional trial designs. Data were analyzed from July to September 2021. EXPOSURE Platform trial design. MAIN OUTCOMES AND MEASURES Total trial setup and conduct cost and cumulative duration. RESULTS Although setup time and cost requirements of a single trial were highest for the platform trial, cumulative requirements of setting up a series of multiple trials in scenarios 2 and 3 were larger. Compared with the platform trial, there was a median (IQR) increase of 216.7% (202.2%-242.5%) in cumulative setup costs for scenario 2 and 391.1% (365.3%-437.9%) for scenario 3. In terms of total cost, there was a median (IQR) increase of 17.4% (12.1%-22.5%) for scenario 2 and 57.5% (43.1%-69.9%) for scenario 3. There was a median (IQR) increase in cumulative trial duration of 171.1% (158.3%-184.3%) for scenario 2 and 311.9% (282.0%-349.1%) for scenario 3. Cost and time reductions in the platform trial were observed in both the initial and subsequently evaluated interventions. CONCLUSIONS AND RELEVANCE Although setting up platform trials can take longer and be costly, the findings of this study suggest that having a single infrastructure can improve efficiencies with respect to costs and efforts.
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Affiliation(s)
- Jay J. H. Park
- Experimental Medicine, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University Health Sciences Centre, Hamilton, Ontario, Canada
| | | | | | | | - Anna Heath
- Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Department of Statistical Science, University College London, London, United Kingdom
| | - Maureen Meade
- Department of Health Research Methods, Evidence, and Impact, McMaster University Health Sciences Centre, Hamilton, Ontario, Canada
- Interdepartmental Division of Critical Care, Hamilton Health Sciences, Critical Care, Hamilton, Ontario, Canada
| | - Ryan Zarychanski
- Department of Internal Medicine, Section of Critical Care, University of Manitoba, Winnipeg, Manitoba, Canada
- Department of Internal Medicine, Section of Hematology/Medical Oncology, University of Manitoba, Winnipeg, Manitoba, Canada
| | | | | | - Edward J. Mills
- Department of Health Research Methods, Evidence, and Impact, McMaster University Health Sciences Centre, Hamilton, Ontario, Canada
| | | | - Cyrus Mehta
- Cytel, Inc, Waltham, Massachusetts
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Cambridge, Massachusetts
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20
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Li V, Leurent B, Barkhof F, Braisher M, Cafferty F, Ciccarelli O, Eshaghi A, Gray E, Nicholas JM, Parmar M, Peryer G, Robertson J, Stallard N, Wason J, Chataway J. Designing Multi-arm Multistage Adaptive Trials for Neuroprotection in Progressive Multiple Sclerosis. Neurology 2022; 98:754-764. [PMID: 35321926 PMCID: PMC9109150 DOI: 10.1212/wnl.0000000000200604] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 03/10/2022] [Indexed: 11/24/2022] Open
Abstract
There are few treatments shown to slow disability progression in progressive multiple sclerosis (PMS). One challenge has been efficiently testing the pipeline of candidate therapies from preclinical studies in clinical trials. Multi-arm multistage (MAMS) platform trials may accelerate evaluation of new therapies compared to traditional sequential clinical trials. We describe a MAMS design in PMS focusing on selection of interim and final outcome measures, sample size, and statistical considerations. The UK MS Society Expert Consortium for Progression in MS Clinical Trials reviewed recent phase II and III PMS trials to inform interim and final outcome selection and design measures. Simulations were performed to evaluate trial operating characteristics under different treatment effect, recruitment rate, and sample size assumptions. People with MS formed a patient and public involvement group and contributed to the trial design, ensuring it would meet the needs of the MS community. The proposed design evaluates 3 experimental arms compared to a common standard of care arm in 2 stages. Stage 1 (interim) outcome will be whole brain atrophy on MRI at 18 months, assessed for 123 participants per arm. Treatments with sufficient evidence for slowing brain atrophy will continue to the second stage. The stage 2 (final) outcome will be time to 6-month confirmed disability progression, based on a composite clinical score comprising the Expanded Disability Status Scale, Timed 25-Foot Walk test, and 9-Hole Peg Test. To detect a hazard ratio of 0.75 for this primary final outcome with 90% power, 600 participants per arm are required. Assuming one treatment progresses to stage 2, the trial will recruit ≈1,900 participants and last ≈6 years. This is approximately two-thirds the size and half the time of separate 2-arm phase II and III trials. The proposed MAMS trial design will substantially reduce duration and sample size compared to traditional clinical trials, accelerating discovery of effective treatments for PMS. The design was well-received by people with multiple sclerosis. The practical and statistical principles of MAMS trial design may be applicable to other neurodegenerative conditions to facilitate efficient testing of new therapies.
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Affiliation(s)
- Vivien Li
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Baptiste Leurent
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Frederik Barkhof
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Marie Braisher
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Fay Cafferty
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Olga Ciccarelli
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Arman Eshaghi
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Emma Gray
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Jennifer M Nicholas
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Mahesh Parmar
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Guy Peryer
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Jenny Robertson
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Nigel Stallard
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - James Wason
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Jeremy Chataway
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
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21
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Feng Z, Gu Y, Yuan M, Xiao R, Fei Z. Clinical Trials of Liposomes in Children’s Anticancer Therapy: A Comprehensive Analysis of Trials Registered on ClinicalTrials.gov. Int J Nanomedicine 2022; 17:1843-1850. [PMID: 35502234 PMCID: PMC9056094 DOI: 10.2147/ijn.s359666] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 04/12/2022] [Indexed: 12/12/2022] Open
Abstract
Objective Clinical trials have become essential for driving the development of medicine. However, little is known about the current status of clinical trials on liposomes in children’s anticancer therapy (LCAT). This study aimed to synthesize current finding from clinical trials of LCAT in ClinicalTrials.gov. Methods A cross-sectional descriptive study of clinical trials on LCAT was conducted, using studies registered on ClinicalTrials.gov through December 30, 2021. Results A total of 74 eligible trials were identified, accounting for 4.8% (74/1552) of all trials on liposomes for cancer therapy. Among these trials, 70 (94.6%) were interventional trials, and the remaining 4 (5.4%) were observational trials. Of the 70 interventional trials, 63 (90.0%) were for treatment, 48.6% were involving unlabeled allocations, 30.0% were randomized, 52.9% were single group assignment, 71.4% were without masking, 28.6% were Phase 3 trials, 30.0% were Phase 1 trials, and 24.3% were Phase 2 trials. Furthermore, 17 liposomal drugs for 123 types of cancer were investigated in the interventional trials, and these were mainly focused on organic chemicals (43/70, 61.4%). Of these cancers, the highest proportion was leukemia (15.4%), followed by lymphoma (9.8%) and ovarian cancer (8.9%). Conclusion High quality, adequately powered, masked, appropriately sized, and randomized clinical trials represent the critical priorities for conducting a high-quality clinical trial. However, most of these trials for LCAT were non-randomized, single group assignment, and non-blinded interventional trials of small scale, with various eligibility criteria and outcome measures. Our analysis highlights the need for improvement in the completeness of study designs curated on clinicalTrials.gov. We urge for decision-makers to avoid adopting entrenched positions about the study design of cancer clinical trials to avoid this problem. As such, tackling the problematic challenges related to cancer and designing efficient trials for cancer requires developing and applying new approaches and multiple strategies.
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Affiliation(s)
- Zhaosong Feng
- Pharmacy Department, Jianhu People’s Hospital, Jianhu, Jiangsu Province, 224700, People’s Republic of China
| | - Yuyang Gu
- Department of Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, 325000, People’s Republic of China
| | - Mengping Yuan
- Department of Gastroenterology, the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, 325000, People’s Republic of China
| | - Renzhong Xiao
- R&D Center, Hunan Royal Pharmaceutical Technology Co., Ltd., Changsha, Hunan Province, 410000, People’s Republic of China
- Correspondence: Renzhong Xiao, R&D Center, Hunan Royal Pharmaceutical Technology Co., Ltd., Changsha City, Hunan Province, 410000, People’s Republic of China, Email
| | - Zhenghua Fei
- Department of Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, 325000, People’s Republic of China
- Zhenghua Fei, Department of Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, 325000, People’s Republic of China, Email
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22
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Brown LC, Graham J, Fisher D, Adams R, Seligmann J, Seymour M, Kaplan R, Yates E, Parmar M, Richman SD, Quirke P, Butler R, Shiu K, Middleton G, Samuel L, Wilson RH, Maughan TS. Experiences of running a stratified medicine adaptive platform trial: Challenges and lessons learned from 10 years of the FOCUS4 trial in metastatic colorectal cancer. Clin Trials 2022; 19:146-157. [PMID: 35083924 PMCID: PMC9036145 DOI: 10.1177/17407745211069879] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Complex innovative design trials are becoming increasingly common and offer potential for improving patient outcomes in a faster time frame. FOCUS4 was the first molecularly stratified trial in metastatic colorectal cancer and it remains one of the first umbrella trial designs to be launched globally. Here, we aim to describe lessons learned from delivery of the trial over the last 10 years. METHODS FOCUS4 was a Phase II/III molecularly stratified umbrella trial testing the safety and efficacy of targeted therapies in metastatic colorectal cancer. It used adaptive statistical methodology to decide which sub-trial should close early, and new therapies were added as protocol amendments. Patients with newly diagnosed metastatic colorectal cancer were registered, and central laboratory testing was used to stratify their tumour into molecular subtypes. Following 16 weeks of first-line therapy, patients with stable or responding disease were eligible for randomisation into either a molecularly stratified sub-trial (FOCUS4-B, C or D) or non-stratified FOCUS4-N. The primary outcome for all studies was progression-free survival comparing the intervention with active monitoring/placebo. At the close of the trial, feedback was elicited from all investigators through surveys and interviews and consolidated into a series of recommendations and lessons learned for the delivery of similar future trials. RESULTS Between January 2014 and October 2020, 1434 patients were registered from 88 UK hospitals. Of the 20 drug combinations that were explored for inclusion in the platform trial, three molecularly targeted sub-trials were activated: FOCUS4-D (February 2014-March 2016) evaluated AZD8931 in the BRAF-PIK3CA-RAS wildtype subgroup; FOCUS4-B (February 2016-July 2018) evaluated aspirin in the PIK3CA mutant subgroup and FOCUS4-C (June 2017-October 2020) evaluated adavosertib in the RAS+TP53 double mutant subgroup. FOCUS4-N was active throughout and evaluated capecitabine monotherapy versus a treatment break. A total of 361 (25%) registered patients were randomised into a sub-trial. Feedback on the experiences of delivery of FOCUS4 could be grouped into three main areas of challenge: funding/infrastructure, biomarker testing procedures and trial design efficiencies within which 20 recommendations are summarised. CONCLUSION Adaptive stratified medicine platform studies are feasible in common cancers but present challenges. Our stakeholder feedback has helped to inform how these trial designs can succeed and answer multiple questions efficiently, providing resource is adequate.
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Affiliation(s)
| | - Janet Graham
- The Beatson West of Scotland Cancer Centre, Glasgow, UK
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | | | - Richard Adams
- Centre for Trials Research, Cardiff University and Velindre NHS Trust, Cardiff, UK
| | - Jenny Seligmann
- Leeds Institute of Medical Research at St James’s, University of Leeds, Leeds, UK
| | - Matthew Seymour
- Leeds Institute of Medical Research at St James’s, University of Leeds, Leeds, UK
| | | | - Emma Yates
- MRC Clinical Trials Unit at UCL, London, UK
| | | | - Susan D Richman
- Leeds Institute of Medical Research at St James’s, University of Leeds, Leeds, UK
| | - Philip Quirke
- Leeds Institute of Medical Research at St James’s, University of Leeds, Leeds, UK
| | | | | | | | | | - Richard H Wilson
- The Beatson West of Scotland Cancer Centre, Glasgow, UK
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Timothy S Maughan
- MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, UK
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23
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Bourdette D, Sormani MP. Thinking Anew: Accelerating Clinical Trials of New Therapies for Progressive Multiple Sclerosis. Neurology 2022; 98:743-744. [PMID: 35321927 DOI: 10.1212/wnl.0000000000200597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Dennis Bourdette
- Department of Neurology, Oregon Health & Science University (D.B.)
| | - Maria Pia Sormani
- Department of Health Sciences, University of Genoa.,IRCCS Ospedale Policlinico San Martino, Genoa, Italy (M.P. S.)
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24
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Noor NM, Love SB, Isaacs T, Kaplan R, Parmar MKB, Sydes MR. Uptake of the multi-arm multi-stage (MAMS) adaptive platform approach: a trial-registry review of late-phase randomised clinical trials. BMJ Open 2022; 12:e055615. [PMID: 35273052 PMCID: PMC8915371 DOI: 10.1136/bmjopen-2021-055615] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND For medical conditions with numerous interventions worthy of investigation, there are many advantages of a multi-arm multi-stage (MAMS) platform trial approach. However, there is currently limited knowledge on uptake of the MAMS design, especially in the late-phase setting. We sought to examine uptake and characteristics of late-phase MAMS platform trials, to enable better planning for teams considering future use of this approach. DESIGN We examined uptake of registered, late-phase MAMS platforms in the EU clinical trials register, Australian New Zealand Clinical Trials Registry, International Standard Randomised Controlled Trial Number registry, Pan African Clinical Trials Registry, WHO International Clinical Trial Registry Platform and databases: PubMed, Medline, Cochrane Library, Global Health Library and EMBASE. Searching was performed and review data frozen on 1 April 2021. MAMS platforms were defined as requiring two or more comparison arms, with two or more trial stages, with an interim analysis allowing for stopping of recruitment to arms and typically the ability to add new intervention arms. RESULTS 62 late-phase clinical trials using an MAMS approach were included. Overall, the number of late-phase trials using the MAMS design has been increasing since 2001 and been accelerated by COVID-19. The majority of current MAMS platforms were either targeting infectious diseases (52%) or cancers (29%) and all identified trials were for treatment interventions. 89% (55/62) of MAMS platforms were evaluating medications, with 45% (28/62) of the MAMS platforms having at least one or more repurposed medication as a comparison arm. CONCLUSIONS Historically, late-phase trials have adhered to long-established standard (two-arm) designs. However, the number of late-phase MAMS platform trials is increasing, across a range of different disease areas. This study highlights the potential scope of MAMS platform trials and may assist research teams considering use of this approach in the late-phase randomised clinical trial setting. PROSPERO REGISTRATION NUMBER CRD42019153910.
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Affiliation(s)
| | | | - Talia Isaacs
- Institute of Education, University College London, London, UK
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25
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Park JJH, Detry MA, Murthy S, Guyatt G, Mills EJ. How to Use and Interpret the Results of a Platform Trial: Users' Guide to the Medical Literature. JAMA 2022; 327:67-74. [PMID: 34982138 DOI: 10.1001/jama.2021.22507] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Platform trials are a type of randomized clinical trial that allow simultaneous comparison of multiple intervention groups against a single control group that serves as a common control based on a prespecified interim analysis plan. The platform trial design enables introduction of new interventions after the trial is initiated to evaluate multiple interventions in an ongoing manner using a single overarching protocol called a master (or core) protocol. When multiple treatment candidates are available, rapid scientific therapeutic discoveries may be made. Platform trials have important potential advantages in creating an efficient trial infrastructure that can help address critical clinical questions as the evidence evolves. Platform trials have recently been used in investigations of evolving therapies for patients with COVID-19. The purpose of this Users' Guide to the Medical Literature is to describe fundamental concepts of platform trials and master protocols and review issues in the conduct and interpretation of these studies. This Users' Guide is intended to help clinicians and readers understand articles reporting on interventions evaluated using platform trial designs.
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Affiliation(s)
- Jay J H Park
- Division of Experimental Medicine, Department of Medicine, University of British Columbia, Vancouver, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | | | - Srinivas Murthy
- Department of Pediatrics, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Gordon Guyatt
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Edward J Mills
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
- Cytel Inc, Vancouver, British Columbia, Canada
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26
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Clarke CS, Hunter RM, Gabrio A, Brawley CD, Ingleby FC, Dearnaley DP, Matheson D, Attard G, Rush HL, Jones RJ, Cross W, Parker C, Russell JM, Millman R, Gillessen S, Malik Z, Lester JF, Wylie J, Clarke NW, Parmar MKB, Sydes MR, James ND. Cost-utility analysis of adding abiraterone acetate plus prednisone/prednisolone to long-term hormone therapy in newly diagnosed advanced prostate cancer in England: Lifetime decision model based on STAMPEDE trial data. PLoS One 2022; 17:e0269192. [PMID: 35653395 PMCID: PMC9162346 DOI: 10.1371/journal.pone.0269192] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 05/14/2022] [Indexed: 01/27/2023] Open
Abstract
Adding abiraterone acetate (AA) plus prednisolone (P) to standard of care (SOC) improves survival in newly diagnosed advanced prostate cancer (PC) patients starting hormone therapy. Our objective was to determine the value for money to the English National Health Service (NHS) of adding AAP to SOC. We used a decision analytic model to evaluate cost-effectiveness of providing AAP in the English NHS. Between 2011-2014, the STAMPEDE trial recruited 1917 men with high-risk localised, locally advanced, recurrent or metastatic PC starting first-line androgen-deprivation therapy (ADT), and they were randomised to receive SOC plus AAP, or SOC alone. Lifetime costs and quality-adjusted life-years (QALYs) were estimated using STAMPEDE trial data supplemented with literature data where necessary, adjusting for baseline patient and disease characteristics. British National Formulary (BNF) prices (£98/day) were applied for AAP. Costs and outcomes were discounted at 3.5%/year. AAP was not cost-effective. The incremental cost-effectiveness ratio (ICER) was £149,748/QALY gained in the non-metastatic (M0) subgroup, with 2.4% probability of being cost-effective at NICE's £30,000/QALY threshold; and the metastatic (M1) subgroup had an ICER of £47,503/QALY gained, with 12.0% probability of being cost-effective. Scenario analysis suggested AAP could be cost-effective in M1 patients if priced below £62/day, or below £28/day in the M0 subgroup. AAP could dominate SOC in the M0 subgroup with price below £11/day. AAP is effective for non-metastatic and metastatic disease but is not cost-effective when using the BNF price. AAP currently only has UK approval for use in a subset of M1 patients. The actual price currently paid by the English NHS for abiraterone acetate is unknown. Broadening AAP's indication and having a daily cost below the thresholds described above is recommended, given AAP improves survival in both subgroups and its cost-saving potential in M0 subgroup.
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Affiliation(s)
- Caroline S. Clarke
- Research Department of Primary Care and Population Health, University College London, London, United Kingdom
- * E-mail:
| | - Rachael M. Hunter
- Research Department of Primary Care and Population Health, University College London, London, United Kingdom
| | - Andrea Gabrio
- Department of Methodology and Statistics, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Christopher D. Brawley
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, United Kingdom
| | - Fiona C. Ingleby
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, United Kingdom
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - David P. Dearnaley
- Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - David Matheson
- Patient Representative, University of Wolverhampton, Wolverhampton, United Kingdom
| | - Gerhardt Attard
- University College London Cancer Institute, London, United Kingdom
| | - Hannah L. Rush
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, United Kingdom
- Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Rob J. Jones
- Beatson West of Scotland Cancer Centre, Glasgow, United Kingdom
- Institute of Cancer Sciences, University of Glasgow, Glasgow, United Kingdom
| | - William Cross
- Department of Urology, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Chris Parker
- Royal Marsden Hospital and Institute of Cancer Research, Sutton, United Kingdom
| | - J. Martin Russell
- Beatson West of Scotland Cancer Centre, Glasgow, United Kingdom
- Institute of Cancer Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Robin Millman
- Patient Representative, MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, United Kingdom
| | - Silke Gillessen
- Division of Cancer Sciences, University of Manchester, Manchester, United Kingdom
- Oncology Institute of Southern Switzerland, EOC, Bellinzona, Switzerland
- Università della Svizzera Italiana, Lugano, Switzerland
| | - Zafar Malik
- Clatterbridge Cancer Centre NHS Foundation Trust, Birkenhead, United Kingdom
| | - Jason F. Lester
- South West Wales Cancer Centre, Singleton Hospital, Swansea, United Kingdom
| | - James Wylie
- Christie NHS Foundation Trust, Manchester, United Kingdom
| | - Noel W. Clarke
- Christie NHS Foundation Trust, Manchester, United Kingdom
- Salford Royal Hospital, Salford, United Kingdom
| | - Mahesh K. B. Parmar
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, United Kingdom
| | - Matthew R. Sydes
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, United Kingdom
| | - Nicholas D. James
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, United Kingdom
- Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
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27
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Speich B, Chammartin F, Smith D, Stoeckle MP, Amico P, Eichenberger AL, Hasse B, Schuurmans MM, Müller T, Tamm M, Dickenmann M, Abela IA, Trkola A, Hirsch HH, Manuel O, Cavassini M, Hemkens LG, Briel M, Mueller NJ, Rauch A, Günthard HF, Koller MT, Bucher HC, Kusejko K. A trial platform to assess approved SARS-CoV-2 vaccines in immunocompromised patients: first sub-protocol for a pilot trial comparing the mRNA vaccines Comirnaty® and COVID-19 mRNA Vaccine Moderna®. Trials 2021; 22:724. [PMID: 34674742 PMCID: PMC8529365 DOI: 10.1186/s13063-021-05664-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 09/15/2021] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Late 2019, a new highly contagious coronavirus SARS-CoV-2 has emerged in Wuhan, China, causing within 2 months a pandemic with the highest disease burden in elderly and people with pre-existing medical conditions. The pandemic has highlighted that new and more flexible clinical trial approaches, such as trial platforms, are needed to assess the efficacy and safety of interventions in a timely manner. The two existing Swiss cohorts of immunocompromised patients (i.e., Swiss HIV Cohort Study (SHCS) and Swiss Transplant Cohort Study (STCS)) are an ideal foundation to set-up a trial platform in Switzerland leveraging routinely collected data. Within a newly founded trial platform, we plan to assess the efficacy of the first two mRNA SARS-CoV-2 vaccines that reached market authorization in Switzerland in the frame of a pilot randomized controlled trial (RCT) while at the same time assessing the functionality of the trial platform. METHODS We will conduct a multicenter randomized controlled, open-label, 2-arm sub-study pilot trial of a platform trial nested into two Swiss cohorts. Patients included in the SHCS or the STCS will be eligible for randomization to either receiving the mRNA vaccine Comirnaty® (Pfizer/BioNTech) or the COVID-19 mRNA Vaccine Moderna®. The primary clinical outcome will be change in pan-lg antibody response (pan-Ig anti-S1-RBD; baseline vs. 3 months after first vaccination; binary outcome, considering ≥ 0.8 units/ml as a positive antibody response). The pilot study will also enable us to assess endpoints related to trial conduct feasibility (i.e., duration of RCT set-up; time of patient recruitment; patient consent rate; proportion of missing data). Assuming vaccine reactivity of 90% in both vaccine groups, we power our trial, using a non-inferiority margin such that a 95% two-sided confidence interval excludes a difference in favor of the reference group of more than 10%. A sample size of 380 (190 in each treatment arm) is required for a statistical power of 90% and a type I error of 0.025. The study is funded by the Swiss National Science Foundation (National Research Program NRP 78, "COVID-19"). DISCUSSION This study will provide crucial information about the efficacy and safety of the mRNA SARS-CoV-2 vaccines in HIV patients and organ transplant recipients. Furthermore, this project has the potential to pave the way for further platform trials in Switzerland. TRIAL REGISTRATION ClinicalTrials.gov NCT04805125 . Registered on March 18, 2021.
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Affiliation(s)
- Benjamin Speich
- Department of Clinical Research, Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, University of Basel, Basel, Switzerland.
- Nuffield Department of Orthopaedics, Centre for Statistics in Medicine, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
| | - Frédérique Chammartin
- Department of Clinical Research, Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Daniel Smith
- University of Zurich, Institute of Medical Virology, Zurich, Switzerland
| | - Marcel P Stoeckle
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital of Basel, University of Basel, Basel, Switzerland
| | - Patrizia Amico
- Clinic for Transplantation Immunology and Nephrology, University Hospital Basel, Basel, Switzerland
| | - Anna L Eichenberger
- Department of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
| | - Barbara Hasse
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Macé M Schuurmans
- Division of Pulmonology, University Hospital Zurich, Zurich, Switzerland
| | - Thomas Müller
- Nephrology Clinic, University Hospital Zurich, Zurich, Switzerland
| | - Michael Tamm
- Clinic of Respiratory Medicine and Pulmonary Cell Research, University Hospital of Basel, Petersgraben 4, 4031, Basel, Switzerland
| | - Michael Dickenmann
- Department of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
| | - Irene A Abela
- University of Zurich, Institute of Medical Virology, Zurich, Switzerland
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Alexandra Trkola
- University of Zurich, Institute of Medical Virology, Zurich, Switzerland
| | - Hans H Hirsch
- Clinical Virology, Laboratory Medicine, University Hospital Basel, Basel, Switzerland
- Transplantation & Clinical Virology, Department Biomedicine, University Hospital Basel, Basel, Switzerland
| | - Oriol Manuel
- Infectious Diseases Service, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Transplantation Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Matthias Cavassini
- Infectious Diseases Service, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Lars G Hemkens
- Department of Clinical Research, Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, University of Basel, Basel, Switzerland
- Meta-Research Innovation Center Berlin (METRICS-B), Berlin Institute of Health, Berlin, Germany
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA
| | - Matthias Briel
- Department of Clinical Research, Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, University of Basel, Basel, Switzerland
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Nicolas J Mueller
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Andri Rauch
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Huldrych F Günthard
- University of Zurich, Institute of Medical Virology, Zurich, Switzerland
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Michael T Koller
- Department of Clinical Research, Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Heiner C Bucher
- Department of Clinical Research, Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Katharina Kusejko
- University of Zurich, Institute of Medical Virology, Zurich, Switzerland
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
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28
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Dixit V, Mitra P, Simonsen K. Multi-arm multi-stage clinical trials for time-to-event outcomes. J Biopharm Stat 2021; 31:838-851. [PMID: 34606418 DOI: 10.1080/10543406.2021.1979575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
This paper investigates the use of a general multi-arm multi-stage (MAMS) approach for time-to-event outcomes that would streamline simultaneous comparison of a large number of promising therapies in clinical trials, thus significantly reducing the time and the number of patients needed to evaluate the treatment. Controlling type I error in this setting is different than regular clinical trials as this approach incorporates both multiple comparison between arms and multiple stages. Historically, pairwise (PWER) and familywise (FWER) type I error rates have been primarily used to regulate the type I error in such designs. This paper will focus on constructing the efficacy and futility boundaries for a MAMS clinical trial in two different scenarios. In the first, it is assumed that the same outcome is used throughout the clinical trial for both intermediate and final assessments. In this scenario, we propose using the generalized Dunnett procedure that controls FWER. In the latter scenario, where intermediate and final outcomes are different in nature, we propose modifications to the existing method that originally concentrated on controlling PWER and extend the method to include FWER in the design. We also explore the performance of the proposed MAMS design in a setting where the proportional hazard assumption is violated in the presence of a delayed treatment effect and demonstrate the loss of power because of that. An alternative test statistic that can help circumvent this problem to maintain the desired power is also suggested.
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Affiliation(s)
- Vaidehi Dixit
- Department of Statistics, North Carolina State University, Raleigh, North Carolina, USA
| | - Priyam Mitra
- Global Biometrics and Data Sciences, Global Drug Development Oncology, Bristol Myers Squibb, Princeton, NJ, USA
| | - Katy Simonsen
- Global Biometrics and Data Sciences, Global Drug Development Oncology, Bristol Myers Squibb, Princeton, NJ, USA
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29
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Meade A, Oza B, Frangou E, Smith B, Bryant H, Kaplan R, Choodari-Oskooei B, Powles T, Stewart GD, Albiges L, Bex A, Choueiri TK, Davis ID, Eisen T, Fielding A, Harrison DJ, McWhirter A, Mulhere S, Nathan P, Rini B, Ritchie A, Scovell S, Shakeshaft C, Stockler MR, Thorogood N, Larkin J, Parmar MKB. RAMPART: A model for a regulatory-ready academic-led phase III trial in the adjuvant renal cell carcinoma setting. Contemp Clin Trials 2021; 108:106481. [PMID: 34538401 DOI: 10.1016/j.cct.2021.106481] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 06/07/2021] [Accepted: 06/09/2021] [Indexed: 01/27/2023]
Abstract
The development of therapeutics in oncology is a highly active research area for the pharmaceutical and biotechnology industries, but also has a strong academic base. Many new agents have been developed in recent years, most with specific biological targets. This has mandated the need to look at different ways to streamline the evaluation of new agents. One solution has been the development of adaptive trial designs that allow the evaluation of multiple agents, concentrating on the most promising agents while screening out those which are unlikely to benefit patients. Another way forward has been the growth of partnerships between academia and industry with the shared goal of designing and conducting high quality clinical trials which answer important clinical questions as efficiently as possible. The RAMPART trial (NCT03288532) brings together both of these processes in an attempt to improve outcomes for patients with locally advanced renal cell carcinoma (RCC), where no globally acceptable adjuvant strategy after nephrectomy currently exist. RAMPART is led by the MRC CTU at University College London (UCL), in collaboration with other international academic groups and industry. We aim to facilitate the use of data from RAMPART, (dependent on outcomes), for a future regulatory submission that will extend the license of the agents being investigated. We share our experience in order to lay the foundations for an effective trial design and conduct framework and to guide others who may be considering similar collaborations. Trial Registration: ISRCTN #: ISRCTN53348826, NCT #: NCT03288532, EUDRACT #: 2017-002329-39. CTA #: 20363/0380/001-0001. MREC #: 17/LO/1875. ClinicalTrials.gov Identifier: NCT03288532 RAMPART grant number: MC_UU_12023/25. . RAMPART Protocol version 5.0.
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Affiliation(s)
- Angela Meade
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | - Bhavna Oza
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ.
| | - Eleni Frangou
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | - Ben Smith
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | - Hanna Bryant
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | - Rick Kaplan
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | - Babak Choodari-Oskooei
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | - Tom Powles
- St Bartholomew's Hospital, W Smithfield, London EC1A 7B, UK
| | - Grant D Stewart
- University of Cambridge, Department of Surgery, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ,UK
| | - Laurence Albiges
- Institut Gustave Roussy, 114 Rue Edouard Vaillant, 94805, Villejuif, France
| | - Axel Bex
- Royal Free London NHS Foundation Trust UCL Division of Surgery and Interventional Science, Pond Street, London NW3 2QG, UK; The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Toni K Choueiri
- Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02215, United States
| | - Ian D Davis
- Monash University Eastern Health Clinical School, Level 2, 5 Arnold Street, Box Hill, VIC 3128, Australia; Department of Medical Oncology, Eastern Health, Melbourne, Australia; ANZUP Cancer Trials Group, Sydney, Australia
| | - Tim Eisen
- Department of Oncology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge Biomedical Campus, Hill's Road, Cambridge CB2 0QQ, UK
| | - Alison Fielding
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | | | - Anita McWhirter
- Royal Marsden Hospital, Royal Marsden Hospital, 203 Fulham Rd, Chelsea, London SW3 6JJ, UK
| | - Salena Mulhere
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | - Paul Nathan
- Mount Vernon Cancer Centre, Rickmansworth Rd, Northwood HA6 2RN, UK
| | - Brian Rini
- Cleveland Clinic, Cleveland Clinic Taussig Cancer Institute, Cleveland, OH, USA
| | - Alastair Ritchie
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | - Sarah Scovell
- St Bartholomew's Hospital, W Smithfield, London EC1A 7B, UK
| | - Clare Shakeshaft
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | - Martin R Stockler
- ANZUP Cancer Trials Group, Sydney, Australia; NHMRC Clinical Trials Centre, University of Sydney, Camperdown, NSW 2006, Australia
| | - Nat Thorogood
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
| | - James Larkin
- Royal Marsden Hospital, Royal Marsden Hospital, 203 Fulham Rd, Chelsea, London SW3 6JJ, UK
| | - Mahesh K B Parmar
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, 2nd Floor 90 High Holborn, London WC1V 6LJ
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Park JJH, Ford N, Xavier D, Ashorn P, Grais RF, Bhutta ZA, Goossens H, Thorlund K, Socias ME, Mills EJ. Randomised trials at the level of the individual. LANCET GLOBAL HEALTH 2021; 9:e691-e700. [PMID: 33865474 DOI: 10.1016/s2214-109x(20)30540-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 12/08/2020] [Accepted: 12/10/2020] [Indexed: 12/31/2022]
Abstract
In global health research, short-term, small-scale clinical trials with fixed, two-arm trial designs that generally do not allow for major changes throughout the trial are the most common study design. Building on the introductory paper of this Series, this paper discusses data-driven approaches to clinical trial research across several adaptive trial designs, as well as the master protocol framework that can help to harmonise clinical trial research efforts in global health research. We provide a general framework for more efficient trial research, and we discuss the importance of considering different study designs in the planning stage with statistical simulations. We conclude this second Series paper by discussing the methodological and operational complexity of adaptive trial designs and master protocols and the current funding challenges that could limit uptake of these approaches in global health research.
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Affiliation(s)
- Jay J H Park
- Department of Experimental Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Nathan Ford
- Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Denis Xavier
- Department of Pharmacology and Divison of Clinical Research, St John's Medical College, Bangalore, India
| | - Per Ashorn
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | | | - Zulfiqar A Bhutta
- Centre for Global Child Health, Hospital for Sick Children, Toronto, ON, Canada; Institute of Global Health and Development, and Centre of Excellence in Women and Child Health, Aga Khan University, Karachi, Pakistan
| | - Herman Goossens
- Laboratory of Medical Microbiology, University of Antwerp, Antwerp, Belgium
| | - Kristian Thorlund
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Maria Eugenia Socias
- Fundación Huésped, Buenos Aires, Argentina; British Columbia Centre for Substance Use, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Edward J Mills
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada; School of Public Health, University of Rwanda, Kigali, Rwanda; Cytel, Vancouver, BC, Canada.
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Pathologically Node-Positive Prostate Cancer: Casting for Cure When the Die Is Cast? ACTA ACUST UNITED AC 2021; 26:58-63. [PMID: 31977387 DOI: 10.1097/ppo.0000000000000426] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
The postoperative management of men with lymph node involved prostate cancer (pN+) remains a challenge as there is a general lack of randomized trial data and a range of management strategies. Retrospective studies suggest a variable clinic course for patients with pN+ prostate cancer. Some men progress rapidly to metastatic disease despite further therapies, whereas other men can have a period of prolonged quiescence without adjuvant androgen deprivation therapy (ADT) or radiation therapy (RT). For men who have undergone radical prostatectomy, randomized trial data indicate that the addition of ADT in pN+ disease extends metastasis-free, prostate cancer-specific, and overall survival. Additional retrospective studies suggest that adding RT is potentially beneficial in this setting, improving overall and cancer-specific survival especially in men with certain pathologic parameters. Conversely, men with lower disease burden in their lymph nodes have longer times to progression and may be candidates for observation and salvage therapy as opposed to adjuvant ADT/RT.
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Stewart AG, Harris PNA, Chatfield M, Evans SR, van Duin D, Paterson DL. Modern Clinician-initiated Clinical Trials to Determine Optimal Therapy for Multidrug-resistant Gram-negative Infections. Clin Infect Dis 2021; 71:433-439. [PMID: 31738398 DOI: 10.1093/cid/ciz1132] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Accepted: 11/15/2019] [Indexed: 12/26/2022] Open
Abstract
Treatment options for multidrug-resistant (MDR) gram-negative infection are growing. However, postregistration, pragmatic, and clinician-led clinical trials in this field are few, recruit small sample sizes, and experience deficiencies in design and operations. MDR gram-negative therapeutic trials are often inefficient, only evaluating a single antibiotic or strategy at a time. Novel clinical trial designs offer potential solutions by attempting to obtain clinically meaningful conclusions at the end or during a trial, for many treatment strategies, simultaneously. An integrated, consensus approach to MDR gram-negative infection trial design is crucial.
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Affiliation(s)
- Adam G Stewart
- Centre for Clinical Research, Faculty of Medicine, University of Queensland, Royal Brisbane and Women's Hospital Campus, Brisbane, Queensland, Australia.,Department of Infectious Diseases, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
| | - Patrick N A Harris
- Centre for Clinical Research, Faculty of Medicine, University of Queensland, Royal Brisbane and Women's Hospital Campus, Brisbane, Queensland, Australia.,Department of Microbiology, Pathology Queensland, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
| | - Mark Chatfield
- Centre for Clinical Research, Faculty of Medicine, University of Queensland, Royal Brisbane and Women's Hospital Campus, Brisbane, Queensland, Australia
| | - Scott R Evans
- Epidemiology and Biostatistics and Centre for Biostatistics, George Washington University, Rockville, Maryland, USA
| | - David van Duin
- Division of Infectious Diseases, University of North Carolina, Chapel Hill, North Carolina, USA
| | - David L Paterson
- Centre for Clinical Research, Faculty of Medicine, University of Queensland, Royal Brisbane and Women's Hospital Campus, Brisbane, Queensland, Australia.,Department of Infectious Diseases, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
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Lee KM, Brown LC, Jaki T, Stallard N, Wason J. Statistical consideration when adding new arms to ongoing clinical trials: the potentials and the caveats. Trials 2021; 22:203. [PMID: 33691748 PMCID: PMC7944243 DOI: 10.1186/s13063-021-05150-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 02/24/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Platform trials improve the efficiency of the drug development process through flexible features such as adding and dropping arms as evidence emerges. The benefits and practical challenges of implementing novel trial designs have been discussed widely in the literature, yet less consideration has been given to the statistical implications of adding arms. MAIN: We explain different statistical considerations that arise from allowing new research interventions to be added in for ongoing studies. We present recent methodology development on addressing these issues and illustrate design and analysis approaches that might be enhanced to provide robust inference from platform trials. We also discuss the implication of changing the control arm, how patient eligibility for different arms may complicate the trial design and analysis, and how operational bias may arise when revealing some results of the trials. Lastly, we comment on the appropriateness and the application of platform trials in phase II and phase III settings, as well as publicly versus industry-funded trials. CONCLUSION Platform trials provide great opportunities for improving the efficiency of evaluating interventions. Although several statistical issues are present, there are a range of methods available that allow robust and efficient design and analysis of these trials.
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Affiliation(s)
- Kim May Lee
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SR, UK.
- Pragmatic Clinical Trials Unit, Queen Mary University of London, Yvonne Carter Building, 58 Turner Street, London, E1 2AB, UK.
| | - Louise C Brown
- MRC Clinical Trials Unit, University College London, 90 High Holborn 2nd Floor, London, WC1V 6LJ, UK
| | - Thomas Jaki
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SR, UK
- Medical and Pharmaceutical Statistics Research Unit, Department of Mathematics and Statistics, Lancaster University, Lancaster, UK
| | - Nigel Stallard
- Statistics and Epidemiology, Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK
| | - James Wason
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SR, UK
- Population Health Sciences Institute, Baddiley-Clark Building, Newcastle University, Richardson Road, Newcastle upon Tyne, UK
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Meyer EL, Mesenbrink P, Mielke T, Parke T, Evans D, König F. Systematic review of available software for multi-arm multi-stage and platform clinical trial design. Trials 2021; 22:183. [PMID: 33663579 PMCID: PMC7931508 DOI: 10.1186/s13063-021-05130-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 02/13/2021] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND In recent years, the popularity of multi-arm multi-stage, seamless adaptive, and platform trials has increased. However, many design-related questions and questions regarding which operating characteristics should be evaluated to determine the potential performance of a specific trial design remain and are often further complicated by the complexity of such trial designs. METHODS A systematic search was conducted to review existing software for the design of platform trials, whereby multi-arm multi-stage trials were also included. The results of this search are reported both on the literature level and the software level, highlighting the software judged to be particularly useful. RESULTS In recent years, many highly specialized software packages targeting single design elements on platform studies have been released. Only a few of the developed software packages provide extensive design flexibility, at the cost of limited access due to being commercial or not being usable as out-of-the-box solutions. CONCLUSIONS We believe that both an open-source modular software similar to OCTOPUS and a collaborative effort will be necessary to create software that takes advantage of and investigates the impact of all the flexibility that platform trials potentially provide.
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Affiliation(s)
- Elias Laurin Meyer
- Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Peter Mesenbrink
- Novartis Pharmaceuticals Corporation, One Health Plaza, East Hanover, NJ, USA
| | | | | | | | - Franz König
- Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
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Mahlich J, Bartol A, Dheban S. Can adaptive clinical trials help to solve the productivity crisis of the pharmaceutical industry? - a scenario analysis. HEALTH ECONOMICS REVIEW 2021; 11:4. [PMID: 33454837 PMCID: PMC7811738 DOI: 10.1186/s13561-021-00302-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 01/05/2021] [Indexed: 06/12/2023]
Abstract
AIM The productivity of pharmaceutical research and development (R&D) investments is declining due to high failure rates in clinical research. Recently, the US Food and Drug Administration (FDA) acknowledged that adaptive designs can make drug development more efficient and less costly. Our objective is to simulate cost-saving effects and estimate the impact on global R&D expenditures as well as possible outcomes measured in life-years gained. METHODS Based on published drug-development cost data we calculate potential cost savings derived from variations in clinical success rates that result from employing adaptive trial designs. In a subsequent step we estimate how those cost changes affect global R&D expenditures and outcomes. RESULTS Our calculations indicate that an adaptive trial design with the potential to increase success rates of clinical trials by 4 percentage points could lower development costs for a new drug from 2.6 to 2.2bn USD. On a global scale, this cost reduction would free up an additional 4.2bn USD for investment into pharmaceutical R&D to bring about drug innovations that in turn would be capable of generating up to 3.5 million life-years. CONCLUSION New clinical trial designs are crucial to improving productivity within the pharmaceutical industry and to fostering a sustainable health-care system.
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Affiliation(s)
- Jörg Mahlich
- Health Economics and Outcomes Research, Janssen, Pharmaceutical Companies of Johnson & Johnson, Neuss, Germany.
- Düsseldorf Institute of Competition Economics (DICE), University of Düsseldorf, Düsseldorf, Germany.
| | - Arne Bartol
- Government Affairs, Janssen, Pharmaceutical Companies of Johnson & Johnson, Neuss, Germany
| | - Srirangan Dheban
- Health Economics and Outcomes Research, Janssen, Pharmaceutical Companies of Johnson & Johnson, Neuss, Germany
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36
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Howard DR, Hockaday A, Brown JM, Gregory WM, Todd S, Munir T, Oughton JB, Dimbleby C, Hillmen P. A platform trial in practice: adding a new experimental research arm to the ongoing confirmatory FLAIR trial in chronic lymphocytic leukaemia. Trials 2021; 22:38. [PMID: 33419469 PMCID: PMC7792072 DOI: 10.1186/s13063-020-04971-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 12/14/2020] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND The FLAIR trial in chronic lymphocytic leukaemia has a randomised, controlled, open-label, confirmatory, platform design. FLAIR was successfully amended to include an emerging promising experimental therapy to expedite its assessment, greatly reducing the time to reach the primary outcome compared to running a separate trial and without compromising the validity of the research or the ability to recruit to the trial and report the outcomes. The methodological and practical issues are presented, describing how they were addressed to ensure the amendment was a success. METHODS FLAIR was designed as a two-arm trial requiring 754 patients. In stage 2, two new arms were added: a new experimental arm and a second control arm to protect the trial in case of a change in practice. In stage 3, the original experimental arm was closed as its planned recruitment target was reached. In total, 1516 participants will be randomised to the trial. RESULTS The changes to the protocol and randomisation to add and stop arms were made seamlessly without pausing recruitment. The statistical considerations to ensure the results for the original and new hypotheses are unbiased were approved following peer review by oversight committees, Cancer Research UK, ethical and regulatory committees and pharmaceutical partners. These included the use of concurrent comparators in case of any stage effect, appropriate control of the type I error rate and consideration of analysis methods across trial stages. The operational aspects of successfully implementing the amendments are described, including gaining approvals and additional funding, data management requirements and implementation at centres. CONCLUSIONS FLAIR is an exemplar of how an emerging experimental therapy can be assessed within an existing trial structure without compromising the conduct, reporting or validity of the trial. This strategy offered considerable resource savings and allowed the new experimental therapy to be assessed within a confirmatory trial in the UK years earlier than would have otherwise been possible. Despite the clear efficiencies, treatment arms are rarely added to ongoing trials in practice. This paper demonstrates how this strategy is acceptable, feasible and beneficial to patients and the wider research community. TRIAL REGISTRATION ISRCTN Registry ISRCTN01844152 . Registered on August 08, 2014.
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Affiliation(s)
- Dena R Howard
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK.
| | - Anna Hockaday
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Julia M Brown
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Walter M Gregory
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Susan Todd
- Department of Mathematics and Statistics, University of Reading, Reading, UK
| | - Tahla Munir
- St James's Institute of Oncology, St James's University Hospital, Leeds, UK
| | - Jamie B Oughton
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Claire Dimbleby
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Peter Hillmen
- St James's Institute of Oncology, St James's University Hospital, Leeds, UK
- Section of Experimental Haematology, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
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37
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Puthucheary ZA, Gensichen JS, Cakiroglu AS, Cashmore R, Edbrooke L, Heintze C, Neumann K, Wollersheim T, Denehy L, Schmidt KFR. Implications for post critical illness trial design: sub-phenotyping trajectories of functional recovery among sepsis survivors. CRITICAL CARE : THE OFFICIAL JOURNAL OF THE CRITICAL CARE FORUM 2020; 24:577. [PMID: 32977833 PMCID: PMC7517819 DOI: 10.1186/s13054-020-03275-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 09/04/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Patients who survive critical illness suffer from a significant physical disability. The impact of rehabilitation strategies on health-related quality of life is inconsistent, with population heterogeneity cited as one potential confounder. This secondary analysis aimed to (1) examine trajectories of functional recovery in critically ill patients to delineate sub-phenotypes and (2) to assess differences between these cohorts in both clinical characteristics and clinimetric properties of physical function assessment tools. METHODS Two hundred ninety-one adult sepsis survivors were followed-up for 24 months by telephone interviews. Physical function was assessed using the Physical Component Score (PCS) of the Short Form-36 Questionnaire (SF-36) and Activities of Daily Living and the Extra Short Musculoskeletal Function Assessment (XSFMA-F/B). Longitudinal trajectories were clustered by factor analysis. Logistical regression analyses were applied to patient characteristics potentially determining cluster allocation. Responsiveness, floor and ceiling effects and concurrent validity were assessed within clusters. RESULTS One hundred fifty-nine patients completed 24 months of follow-up, presenting overall low PCS scores. Two distinct sub-cohorts were identified, exhibiting complete recovery or persistent impairment. A third sub-cohort could not be classified into either trajectory. Age, education level and number of co-morbidities were independent determinants of poor recovery (AUROC 0.743 ((95%CI 0.659-0.826), p < 0.001). Those with complete recovery trajectories demonstrated high levels of ceiling effects in physical function (PF) (15%), role physical (RP) (45%) and body pain (BP) (57%) domains of the SF-36. Those with persistent impairment demonstrated high levels of floor effects in the same domains: PF (21%), RP (71%) and BP (12%). The PF domain demonstrated high responsiveness between ICU discharge and at 6 months and was predictive of a persistent impairment trajectory (AUROC 0.859 (95%CI 0.804-0.914), p < 0.001). CONCLUSIONS Within sepsis survivors, two distinct recovery trajectories of physical recovery were demonstrated. Older patients with more co-morbidities and lower educational achievements were more likely to have a persistent physical impairment trajectory. In regard to trajectory prediction, the PF score of the SF-36 was more responsive than the PCS and could be considered for primary outcomes. Future trials should consider adaptive trial designs that can deal with non-responders or sub-cohort specific outcome measures more effectively.
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Affiliation(s)
- Zudin A Puthucheary
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. .,Critical Care and Perioperative Medicine Research Group, Adult Critical Care Unit, Royal London Hospital, London, E1 1BB, UK.
| | - Jochen S Gensichen
- Institute of General Practice and Family Medicine, Jena University Hospital, Jena, Germany.,Institute of Family Medicine, University Hospital of the Ludwig Maximilian University, Munich, Germany.,Center of Sepsis Care and Control, Jena University Hospital, Jena, Germany
| | | | - Richard Cashmore
- Critical Care and Perioperative Medicine Research Group, Adult Critical Care Unit, Royal London Hospital, London, E1 1BB, UK
| | - Lara Edbrooke
- Physiotherapy Department, The University of Melbourne, Melbourne, Australia.,Allied Health Department, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Christoph Heintze
- Institute of General Practice and Family Medicine, Charité University Medicine Berlin, Berlin, Germany
| | - Konrad Neumann
- Institute of Biometry and Clinical Epidemiology, Charité University Medicine Berlin, Berlin, Germany
| | - Tobias Wollersheim
- Department of Anesthesiology and Operative Intensive Care Medicine, Charité University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Linda Denehy
- Physiotherapy Department, The University of Melbourne, Melbourne, Australia.,Allied Health Department, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Konrad F R Schmidt
- Institute of General Practice and Family Medicine, Jena University Hospital, Jena, Germany.,Center of Sepsis Care and Control, Jena University Hospital, Jena, Germany.,Institute of General Practice and Family Medicine, Charité University Medicine Berlin, Berlin, Germany
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38
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Noor NM, Pett SL, Esmail H, Crook AM, Vale CL, Sydes MR, Parmar MK. Adaptive platform trials using multi-arm, multi-stage protocols: getting fast answers in pandemic settings. F1000Res 2020; 9:1109. [PMID: 33149899 PMCID: PMC7596806 DOI: 10.12688/f1000research.26253.1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/07/2020] [Indexed: 12/15/2022] Open
Abstract
Global health pandemics, such as coronavirus disease 2019 (COVID-19), require efficient and well-conducted trials to determine effective interventions, such as treatments and vaccinations. Early work focused on rapid sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), subsequent in-vitro and in-silico work, along with greater understanding of the different clinical phases of the infection, have helped identify a catalogue of potential therapeutic agents requiring assessment. In a pandemic, there is a need to quickly identify efficacious treatments, and reject those that are non-beneficial or even harmful, using randomised clinical trials. Whilst each potential treatment could be investigated across multiple, separate, competing two-arm trials, this is a very inefficient process. Despite the very large numbers of interventional trials for COVID-19, the vast majority have not used efficient trial designs. Well conducted, adaptive platform trials utilising a multi-arm multi-stage (MAMS) approach provide a solution to overcome limitations of traditional designs. The multi-arm element allows multiple different treatments to be investigated simultaneously against a shared, standard-of-care control arm. The multi-stage element uses interim analyses to assess accumulating data from the trial and ensure that only treatments showing promise continue to recruitment during the next stage of the trial. The ability to test many treatments at once and drop insufficiently active interventions significantly speeds up the rate at which answers can be achieved. This article provides an overview of the benefits of MAMS designs and successes of trials, which have used this approach to COVID-19. We also discuss international collaboration between trial teams, including prospective agreement to synthesise trial results, and identify the most effective interventions. We believe that international collaboration will help provide faster answers for patients, clinicians, and health care systems around the world, including for future waves of COVID-19, and enable preparedness for future global health pandemics.
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Affiliation(s)
- Nurulamin M. Noor
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Sarah L. Pett
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Hanif Esmail
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Angela M. Crook
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Claire L. Vale
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Matthew R. Sydes
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Mahesh K.B. Parmar
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
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Noor NM, Pett SL, Esmail H, Crook AM, Vale CL, Sydes MR, Parmar MK. Adaptive platform trials using multi-arm, multi-stage protocols: getting fast answers in pandemic settings. F1000Res 2020; 9:1109. [PMID: 33149899 PMCID: PMC7596806 DOI: 10.12688/f1000research.26253.2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/19/2020] [Indexed: 12/15/2022] Open
Abstract
Global health pandemics, such as coronavirus disease 2019 (COVID-19), require efficient and well-conducted trials to determine effective interventions, such as treatments and vaccinations. Early work focused on rapid sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), subsequent in-vitro and in-silico work, along with greater understanding of the different clinical phases of the infection, have helped identify a catalogue of potential therapeutic agents requiring assessment. In a pandemic, there is a need to quickly identify efficacious treatments, and reject those that are non-beneficial or even harmful, using randomised clinical trials. Whilst each potential treatment could be investigated across multiple, separate, competing two-arm trials, this is a very inefficient process. Despite the very large numbers of interventional trials for COVID-19, the vast majority have not used efficient trial designs. Well conducted, adaptive platform trials utilising a multi-arm multi-stage (MAMS) approach provide a solution to overcome limitations of traditional designs. The multi-arm element allows multiple different treatments to be investigated simultaneously against a shared, standard-of-care control arm. The multi-stage element uses interim analyses to assess accumulating data from the trial and ensure that only treatments showing promise continue to recruitment during the next stage of the trial. The ability to test many treatments at once and drop insufficiently active interventions significantly speeds up the rate at which answers can be achieved. This article provides an overview of the benefits of MAMS designs and successes of trials, which have used this approach to COVID-19. We also discuss international collaboration between trial teams, including prospective agreement to synthesise trial results, and identify the most effective interventions. We believe that international collaboration will help provide faster answers for patients, clinicians, and health care systems around the world, including for each further wave of COVID-19, and enable preparedness for future global health pandemics.
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Affiliation(s)
- Nurulamin M. Noor
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Sarah L. Pett
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Hanif Esmail
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Angela M. Crook
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Claire L. Vale
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Matthew R. Sydes
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
| | - Mahesh K.B. Parmar
- Medical Research Council Clinical Trials Unit, University College London, London, WC1V6LJ, UK
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The Evolution of Master Protocol Clinical Trial Designs: A Systematic Literature Review. Clin Ther 2020; 42:1330-1360. [DOI: 10.1016/j.clinthera.2020.05.010] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 04/10/2020] [Accepted: 05/11/2020] [Indexed: 02/07/2023]
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Noor NM, Hart AL, Irving PM, Ghosh S, Parkes M, Raine T. Clinical Trials [and Tribulations]: The Immediate Effects of COVID-19 on IBD Clinical Research Activity in the UK. J Crohns Colitis 2020; 14:1769-1776. [PMID: 32598438 PMCID: PMC7337665 DOI: 10.1093/ecco-jcc/jjaa137] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
There have been immediate and profound impacts of SARS-CoV-2 and COVID-19 on health care services worldwide, with major consequences for non COVID-19 related health care. Alongside efforts to reconfigure services and enable continued delivery of safe clinical care for patients with IBD, consideration must also be given to management of IBD research activity. In many centres there has been an effective shutdown of IBD clinical trial activity as research sites have switched focus to either COVID-19 related research or clinical care only. As a result, the early termination of trial programmes, and loss of potentially effective therapeutic options for IBD, has become a real and worrying prospect. Moreover, in many countries research activity has become embedded into clinical care-with clinical trials often providing access to new therapies or strategies-which would otherwise not have been available in standard clinical pathways. This pandemic has significant implications for the design, conduct, analysis, and reporting of clinical trials in IBD. In this Viewpoint, we share our experiences from a clinical and academic perspective in the UK, highlighting the early challenges encountered, and consider implications for patients and staff at research sites, sponsors, research ethics committees, funders, and regulators. We also offer potential solutions both for now and for when we enter a recovery phase from the pandemic.
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Affiliation(s)
- Nurulamin M Noor
- Department of Gastroenterology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Trust, Cambridge, UK,Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge, UK,Medical Research Council Clinical Trials Unit, University College London, London, UK
| | - Ailsa L Hart
- St Mark’s Hospital, IBD Unit, Harrow, London, UK
| | - Peter M Irving
- IBD Centre, Guy’s and St. Thomas’ NHS Foundation Trust, London, UK,School of Immunology and Microbial Sciences, King’s College London, London, UK
| | - Subrata Ghosh
- Institute of Translational Medicine, NIHR Biomedical Research Centre, University of Birmingham, Birmingham, UK
| | - Miles Parkes
- Department of Gastroenterology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Trust, Cambridge, UK,Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Tim Raine
- Department of Gastroenterology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Trust, Cambridge, UK,Corresponding author: Dr Tim Raine, MB BChir PhD, Department of Gastroenterology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Trust, Hills Road, Cambridge CB2 OQQ, UK. Tel.: +441223 245151;
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Dimairo M, Pallmann P, Wason J, Todd S, Jaki T, Julious SA, Mander AP, Weir CJ, Koenig F, Walton MK, Nicholl JP, Coates E, Biggs K, Hamasaki T, Proschan MA, Scott JA, Ando Y, Hind D, Altman DG. The adaptive designs CONSORT extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design. Trials 2020; 21:528. [PMID: 32546273 PMCID: PMC7298968 DOI: 10.1186/s13063-020-04334-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised.This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process.The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text.The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits. In order to encourage its wide dissemination this article is freely accessible on the BMJ and Trials journal websites."To maximise the benefit to society, you need to not just do research but do it well" Douglas G Altman.
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Affiliation(s)
- Munyaradzi Dimairo
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK.
| | | | - James Wason
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Institute of Health and Society, Newcastle University, Newcastle, UK
| | - Susan Todd
- Department of Mathematics and Statistics, University of Reading, Reading, UK
| | - Thomas Jaki
- Department of Mathematics and Statistics, Lancaster University, Lancaster, UK
| | - Steven A Julious
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK
| | - Adrian P Mander
- Centre for Trials Research, Cardiff University, Cardiff, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Christopher J Weir
- Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Franz Koenig
- Centre for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Marc K Walton
- Janssen Pharmaceuticals, Titusville, New Jersey, USA
| | - Jon P Nicholl
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK
| | - Elizabeth Coates
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK
| | - Katie Biggs
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK
| | | | - Michael A Proschan
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, USA
| | - John A Scott
- Division of Biostatistics in the Center for Biologics Evaluation and Research, Food and Drug Administration, Rockville, USA
| | - Yuki Ando
- Pharmaceuticals and Medical Devices Agency, Tokyo, Japan
| | - Daniel Hind
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK
| | - Douglas G Altman
- Centre for Statistics in Medicine, University of Oxford, Oxford, UK
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43
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Dimairo M, Pallmann P, Wason J, Todd S, Jaki T, Julious SA, Mander AP, Weir CJ, Koenig F, Walton MK, Nicholl JP, Coates E, Biggs K, Hamasaki T, Proschan MA, Scott JA, Ando Y, Hind D, Altman DG. The Adaptive designs CONSORT Extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design. BMJ 2020; 369:m115. [PMID: 32554564 PMCID: PMC7298567 DOI: 10.1136/bmj.m115] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/19/2019] [Indexed: 12/11/2022]
Abstract
Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised.This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process.The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text.The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits.
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Affiliation(s)
- Munyaradzi Dimairo
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | | | - James Wason
- MRC Biostatistics Unit, University of Cambridge, UK
- Institute of Health and Society, Newcastle University, UK
| | - Susan Todd
- Department of Mathematics and Statistics, University of Reading, UK
| | - Thomas Jaki
- Department of Mathematics and Statistics, Lancaster University, UK
| | - Steven A Julious
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | - Adrian P Mander
- Centre for Trials Research, Cardiff University, UK
- MRC Biostatistics Unit, University of Cambridge, UK
| | - Christopher J Weir
- Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, UK
| | - Franz Koenig
- Centre for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Austria
| | | | - Jon P Nicholl
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | - Elizabeth Coates
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | - Katie Biggs
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | | | - Michael A Proschan
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA
| | - John A Scott
- Division of Biostatistics in the Center for Biologics Evaluation and Research, Food and Drug Administration, USA
| | - Yuki Ando
- Pharmaceuticals and Medical Devices Agency, Japan
| | - Daniel Hind
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
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Buonerba C, Ferro M, Dolce P, Crocetto F, Verde A, Lucarelli G, Scafuri L, Facchini S, Vaia A, Marinelli A, Terracciano D, Montella L, Longo N, Imbimbo C, Mirone V, Di Lorenzo G, De Placido S, Sonpavde G. Predictors of efficacy of androgen-receptor-axis-targeted therapies in patients with metastatic castration-sensitive prostate cancer: A systematic review and meta-analysis. Crit Rev Oncol Hematol 2020; 151:102992. [PMID: 32474391 DOI: 10.1016/j.critrevonc.2020.102992] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 05/05/2020] [Accepted: 05/14/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Both docetaxel and androgen-receptor-axis-targeted (ARAT) agents are approved in metastatic castration-sensitive prostate cancer (mCSPC) patients. Predictive factors of therapy efficacy are lacking. METHODS We included articles reporting data about randomized-controlled clinical trials (RCTs) testing an ARAT agent plus ADT vs. ADT. We aimed to obtain pooled estimates of efficacy outcomes and assess differences in pooled estimates of efficacy outcomes between sub-groups. RESULTS A total of 5427 mCSPC patients enrolled in five RCTs were evaluable for OS (Overall Survival) and PFS (Progression-free survival). Pooled OS-HR (Hazard Ratio) was 0.66 (95 % CI: 0.60-0.74), while pooled PFS-HR was 0.46 (95 % CI: 0.40-0.53). Combined treatment with docetaxel was associated with differential OS outcomes, while tumor volume according to the CHAARTED criteria and visceral metastasis were associated with differential PFS outcomes. CONCLUSION Our results add evidence that ARAT agents improve OS in mCSPC and discourage their combined use with docetaxel in this setting.
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Affiliation(s)
- Carlo Buonerba
- Regional Reference Center for Rare Tumors, Department of Oncology and Hematology, AOU Federico II of Naples, 80131 Naples, Italy; National Reference Center for Environmental Health, Zoo-prophylactic Institute of Southern Italy, 80055 Portici, Italy.
| | - Matteo Ferro
- Division of Urology, European Institute of Oncology-IRCCS, Milan, Italy
| | - Pasquale Dolce
- Department of Public Health, Federico II University of Naples, 80131 Naples, Italy
| | - Felice Crocetto
- Department of Neurosciences, Human Reproduction and Odontostomatology, University of Naples Federico II, Naples, Italy
| | - Antonio Verde
- Department of Clinical Medicine and Surgery, University Federico II of Naples, Via Pansini 5, 80131 Naples, Italy
| | - Giuseppe Lucarelli
- Department of Emergency and Organ Transplantation, Urology, Andrology and Kidney Transplantation Unit, University of Bari, Bari, Italy
| | - Luca Scafuri
- Department of Clinical Medicine and Surgery, University Federico II of Naples, Via Pansini 5, 80131 Naples, Italy
| | - Sergio Facchini
- Department of Neurosciences, Human Reproduction and Odontostomatology, University of Naples Federico II, Naples, Italy
| | - Angelo Vaia
- Department of Clinical Medicine and Surgery, University Federico II of Naples, Via Pansini 5, 80131 Naples, Italy
| | - Alfredo Marinelli
- Department of Clinical Medicine and Surgery, University Federico II of Naples, Via Pansini 5, 80131 Naples, Italy
| | - Daniela Terracciano
- Department of Translational Medical Sciences, University Federico II, Napoli, Italy
| | - Liliana Montella
- Medical Oncology Unit, S.Maria delle Grazie Hospital, Pozzuoli, Italy
| | - Nicola Longo
- Department of Neurosciences, Human Reproduction and Odontostomatology, University of Naples Federico II, Naples, Italy
| | - Ciro Imbimbo
- Department of Neurosciences, Human Reproduction and Odontostomatology, University of Naples Federico II, Naples, Italy
| | - Vincenzo Mirone
- Department of Neurosciences, Human Reproduction and Odontostomatology, University of Naples Federico II, Naples, Italy
| | - Giuseppe Di Lorenzo
- Department of Oncology, Hospital "Andrea Tortora", ASL Salerno, 84016 Pagani, Italy
| | - Sabino De Placido
- Department of Clinical Medicine and Surgery, University Federico II of Naples, Via Pansini 5, 80131 Naples, Italy
| | - Guru Sonpavde
- Genitourinary Oncology Section, Dana Farber Cancer Institute, Boston, MA, USA
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45
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An overview of platform trials with a checklist for clinical readers. J Clin Epidemiol 2020; 125:1-8. [PMID: 32416336 DOI: 10.1016/j.jclinepi.2020.04.025] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 04/16/2020] [Accepted: 04/22/2020] [Indexed: 12/23/2022]
Abstract
OBJECTIVES The objective of the study was to outline key considerations for general clinical readers when critically evaluating publications on platform trials and for researchers when designing these types of clinical trials. STUDY DESIGN AND SETTING In this review, we describe key concepts of platform trials with case study discussion of two hallmark platform trials in STAMPEDE and I-SPY2. We provide reader's guide to platform trials with a critical appraisal checklist. RESULTS Platform trials offer flexibilities of dropping ineffective arms early based on interim data and introducing new arms into the trial. For platform trials, it is important to consider how interventions are compared and evaluated throughout and how new interventions are introduced. For intervention comparisons, it is important to consider what the primary analysis is, what and how many interventions are active simultaneously, and allocation between different arms. Interim evaluation considerations should include the number and timing of interim evaluations and outcomes and statistical rules used to drop interventions. New interventions are usually introduced based on scientific merits, so consideration of these merits is important, together with the timing and mechanisms in which new interventions are added. CONCLUSION More efforts are needed to improve the scientific literacy of platform trials. Our review provides an overview of the important concepts of platform trials.
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Wang D, Luo Y, Guo Y, Li G, Li F. A-kinase interacting protein 1, a potential biomarker associated with advanced tumor features and CXCL1/2 in prostate cancer. Int J Biol Markers 2020; 35:74-81. [PMID: 32339056 DOI: 10.1177/1724600820914944] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
OBJECTIVE This study aimed to investigate the correlation of A-kinase interacting protein 1 (AKIP1) with chemokine (C-X-C motif) ligand 1 (CXCL1) and CXCL2, as well as their associations with clinical characteristics and prognosis in prostate cancer patients. METHODS A total of 248 eligible prostate cancer patients who underwent surgery were consecutively recruited, and tumor tissues were collected during the surgery. AKIP1, CXCL1, and CXCL2 expression in tumor tissues were assessed by immunohistochemistry. Disease-free survival and overall survival were recorded, and the median follow-up time was 27 months. RESULTS The proportion of patients with AKIP1, CXCL1, and CXCL2 high expression was 56.5%, 63.7%, and 56.9%, respectively. Additionally, AKIP1 expression positively correlated with CXCL1 expression (P<0.001) and CXCL2 expression (P<0.001), and CXCL1 expression was positively associated with CXCL2 expression (P<0.001). Furthermore, AKIP1 expression positively correlated with pathological T stage (P<0.001) and pathological N stage (P=0.003). CXCL1 expression was positively associated with pathological T stage (P<0.001) and pathological N stage (P<0.001) as well. However, the CXCL2 expression only positively correlated with pathological T stage (P=0.002). Also, AKIP1 high expression correlated with worse disease-free survival (P=0.049) and OS (P=0.013), and CXCL1 high expression was associated with unfavorable disease-free survival (P=0.023) but not overall survival (P=0.052). CXCL2 expression was not correlated with disease-free survival (P=0.083) or overall survival (P=0.065). Multivariate Cox's regression disclosed that AKIP1 high expression independently predicted worse overall survival (P=0.009). CONCLUSION AKIP1 positively associates with CXCL1/2 and is a potential biomarker for disease monitoring as well as prognosis in prostate cancer.
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Affiliation(s)
- Danlan Wang
- Department of Urology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Yuanfang Luo
- Department of Urology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Yonglian Guo
- Department of Urology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Guohao Li
- Department of Urology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Fan Li
- Department of Urology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
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Bennett M, Mander AP. Designs for adding a treatment arm to an ongoing clinical trial. Trials 2020; 21:251. [PMID: 32143729 PMCID: PMC7060622 DOI: 10.1186/s13063-020-4073-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 01/13/2020] [Indexed: 11/21/2022] Open
Abstract
Background For many disease areas, there are often treatments in different stages of the development process. We consider the design of a two-arm parallel group trial where it is planned to add a new experimental treatment arm during the trial. This could potentially save money, patients, time and resources; however, the addition of a treatment arm creates a multiple comparison problem. Current practice in trials when a new treatment arm has been added is to compare the new treatment only to controls randomised concurrently, and this is the setting we consider here. Furthermore, for standard multi-arm trials, optimal allocation randomises a larger number of patients to the control arm than to each experimental treatment arm. Methods In this paper we propose an adaptive design, the aim of which is to adapt the sample size of the trial when the new treatment arm is added to control the family-wise error rate (FWER) in the strong sense, whilst maintaining the marginal power of each treatment-to-control comparison at the level of the original study. We explore optimal allocation for designs where a treatment arm is added with the aim of increasing the overall power of the study, where we define the overall power to be the probability of detecting all treatments that are better than the control. Results and conclusions An increase in sample size is required to maintain the marginal power for each pairwise comparison when adding a treatment arm if control of the FWER is required at the level of the type I error in the original study. When control of the FWER is required in a single trial which adds an additional experimental treatment arm, but control of the FWER is not required in separate trials, depending on the design characteristics, it may be better to run a separate trial for each experimental treatment, in terms of the number of patients required. An increase in overall power can be achieved when optimal allocation is used once a treatment arm has been added to the trial, rather than continuing with equal allocation to all treatment arms.
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Affiliation(s)
- Maxine Bennett
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
| | - Adrian P Mander
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
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Choodari-Oskooei B, Bratton DJ, Gannon MR, Meade AM, Sydes MR, Parmar MK. Adding new experimental arms to randomised clinical trials: Impact on error rates. Clin Trials 2020; 17:273-284. [PMID: 32063029 PMCID: PMC7263043 DOI: 10.1177/1740774520904346] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Experimental treatments pass through various stages of development. If a treatment passes through early-phase experiments, the investigators may want to assess it in a late-phase randomised controlled trial. An efficient way to do this is adding it as a new research arm to an ongoing trial while the existing research arms continue, a so-called multi-arm platform trial. The familywise type I error rate is often a key quantity of interest in any multi-arm platform trial. We set out to clarify how it should be calculated when new arms are added to a trial some time after it has started. METHODS We show how the familywise type I error rate, any-pair and all-pairs powers can be calculated when a new arm is added to a platform trial. We extend the Dunnett probability and derive analytical formulae for the correlation between the test statistics of the existing pairwise comparison and that of the newly added arm. We also verify our analytical derivation via simulations. RESULTS Our results indicate that the familywise type I error rate depends on the shared control arm information (i.e. individuals in continuous and binary outcomes and primary outcome events in time-to-event outcomes) from the common control arm patients and the allocation ratio. The familywise type I error rate is driven more by the number of pairwise comparisons and the corresponding (pairwise) type I error rates than by the timing of the addition of the new arms. The familywise type I error rate can be estimated using Šidák's correction if the correlation between the test statistics of pairwise comparisons is less than 0.30. CONCLUSIONS The findings we present in this article can be used to design trials with pre-planned deferred arms or to add new pairwise comparisons within an ongoing platform trial where control of the pairwise error rate or familywise type I error rate (for a subset of pairwise comparisons) is required.
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Affiliation(s)
- Babak Choodari-Oskooei
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
| | | | - Melissa R Gannon
- Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK
| | - Angela M Meade
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
| | - Matthew R Sydes
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
| | - Mahesh Kb Parmar
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
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Hoyle AP, Ali A, James ND, Cook A, Parker CC, de Bono JS, Attard G, Chowdhury S, Cross WR, Dearnaley DP, Brawley CD, Gilson C, Ingleby F, Gillessen S, Aebersold DM, Jones RJ, Matheson D, Millman R, Mason MD, Ritchie AWS, Russell M, Douis H, Parmar MKB, Sydes MR, Clarke NW. Abiraterone in "High-" and "Low-risk" Metastatic Hormone-sensitive Prostate Cancer. Eur Urol 2019; 76:719-728. [PMID: 31447077 DOI: 10.1016/j.eururo.2019.08.006] [Citation(s) in RCA: 130] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Accepted: 08/07/2019] [Indexed: 12/18/2022]
Abstract
BACKGROUND Abiraterone acetate received licencing for use in only "high-risk" metastatic hormone-naïve prostate cancer (mHNPC) following the LATITUDE trial findings. However, a "risk"-related effect was not seen in the STAMPEDE trial. There remains uncertainty as to whether men with LATITUDE "low-risk" M1 disease benefit from androgen deprivation therapy (ADT) combined with abiraterone acetate and prednisolone (AAP). OBJECTIVE Evaluation of heterogeneity of effect between LATITUDE high- and low-risk M1 prostate cancer patients receiving ADT + AAP in the STAMPEDE trial. DESIGN, SETTING, AND PARTICIPANTS A post hoc subgroup analysis of the 2017 STAMPEDE "abiraterone comparison". Staging scans for M1 patients contemporaneously randomised to ADT or ADT + AAP within the STAMPEDE trial were evaluated centrally and blind to treatment assignment. Stratification was by risk according to the criteria set out in the LATITUDE trial. Exploratory subgroup stratification incorporated the CHAARTED criteria. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The primary outcome measure was overall survival (OS) and the secondary outcome measure was failure-free survival (FFS). Further exploratory analysis evaluated clinical skeletal-related events, progression-free survival (PFS), and prostate cancer-specific death. Standard Cox-regression and Kaplan-Meier survival estimates were employed for analysis. RESULTS AND LIMITATIONS A total of 901 M1 STAMPEDE patients were evaluated after exclusions. Of the patients, 428 (48%) were identified as having a low risk and 473 (52%) a high risk. Patients receiving ADT + AAP had significantly improved OS (low-risk hazard ratio [HR]: 0.66, 95% confidence interval or CI [0.44-0.98]) and FFS (low-risk HR: 0.24, 95% CI [0.17-0.33]) compared with ADT alone. Heterogeneity of effect was not seen between low- and high-risk groups for OS or FFS. For OS benefit in low risk, the number needed to treat was four times greater than that for high risk. However, this was not observed for the other measured endpoints. CONCLUSIONS Men with mHNPC gain treatment benefit from ADT + AAP irrespective of risk stratification for "risk" or "volume". PATIENT SUMMARY Coadministration of abiraterone acetate and prednisolone with androgen deprivation therapy (ADT) is associated with prolonged overall survival and disease control, compared with ADT alone, in all men with metastatic disease starting hormone therapy for the first time.
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Affiliation(s)
- Alex P Hoyle
- The Christie and Royal Salford Hospitals, Manchester, UK; Genito Urinary Cancer Research Group and the FASTMAN Centre of Excellence, Division of Cancer Sciences, The University of Manchester, Manchester, UK
| | - Adnan Ali
- The Christie and Royal Salford Hospitals, Manchester, UK
| | - Nicholas D James
- Institute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston, Birmingham, UK
| | - Adrian Cook
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, UCL, London, UK
| | | | | | | | | | | | | | - Christopher D Brawley
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, UCL, London, UK
| | - Clare Gilson
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, UCL, London, UK
| | | | - Silke Gillessen
- Division of Oncology and Haematology, Kantonsspital St. Gallen, St. Gallen, Switzerland; Christie Hospital, Manchester, UK; University of Manchester, Manchester, UK; Swiss Group for Cancer Clinical Research (SAKK), Bern, Switzerland
| | | | - Rob J Jones
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK; Beatson West of Scotland Cancer Centre, University of Glasgow, Glasgow, UK
| | | | | | | | | | - Martin Russell
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK; Beatson West of Scotland Cancer Centre, University of Glasgow, Glasgow, UK
| | - Hassan Douis
- Institute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston, Birmingham, UK
| | - Mahesh K B Parmar
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, UCL, London, UK
| | - Matthew R Sydes
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, UCL, London, UK
| | - Noel W Clarke
- The Christie and Royal Salford Hospitals, Manchester, UK; Genito Urinary Cancer Research Group and the FASTMAN Centre of Excellence, Division of Cancer Sciences, The University of Manchester, Manchester, UK.
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Narayan VM, Dahm P. The future of clinical trials in urological oncology. Nat Rev Urol 2019; 16:722-733. [PMID: 31605037 DOI: 10.1038/s41585-019-0243-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/19/2019] [Indexed: 12/11/2022]
Abstract
Well-designed clinical trials in urological oncology help to guide treatment decisions and aid in counselling patients, ultimately serving to improve outcomes. Since the term evidence-based medicine was first used by Gordon Guyatt in 1991, a renewed emphasis on methodology, transparent trial design and study reporting has helped to improve clinical research and in turn, the landscape of medical literature. Novel clinical trial designs (including multi-arm, multistage trials, basket and umbrella studies and research from big data sources, such as electronic health records, administrative claims databases and quality monitoring registries) are well suited to advance innovation in urological oncology. Existing urological clinical trials are often limited by small numbers, are statistically underpowered and many face difficulties with accrual. Thus, efforts to improve trial design are of considerable importance. The development and use of standard outcome sets and adherence to reporting guidelines offer researchers the opportunity to guide value-oriented care, minimize research waste and efficiently identify solutions to the unanswered questions in urology cancer care.
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Affiliation(s)
- Vikram M Narayan
- Minneapolis VA Medical Center and University of Minnesota Department of Urology, Minneapolis, MN, 55417, USA.,University of Texas MD Anderson Cancer Center, Department of Urology, Houston, TX, 77030, USA
| | - Philipp Dahm
- Minneapolis VA Medical Center and University of Minnesota Department of Urology, Minneapolis, MN, 55417, USA.
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