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Cui L, Zhang L. On the efficiency of adaptive sample size design. Stat Med 2018; 38:933-944. [DOI: 10.1002/sim.8034] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 09/24/2018] [Accepted: 10/22/2018] [Indexed: 11/07/2022]
Affiliation(s)
- Lu Cui
- AbbVie Inc North Chicago Illinois
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Cui L, Zhang L, Yang B. Optimal adaptive group sequential design with flexible timing of sample size determination. Contemp Clin Trials 2017; 63:8-12. [DOI: 10.1016/j.cct.2017.04.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Revised: 04/03/2017] [Accepted: 04/22/2017] [Indexed: 11/26/2022]
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Bauer P, Bretz F, Dragalin V, König F, Wassmer G. Twenty-five years of confirmatory adaptive designs: opportunities and pitfalls. Stat Med 2016; 35:325-47. [PMID: 25778935 PMCID: PMC6680191 DOI: 10.1002/sim.6472] [Citation(s) in RCA: 130] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2014] [Revised: 02/03/2015] [Accepted: 02/19/2015] [Indexed: 12/26/2022]
Abstract
'Multistage testing with adaptive designs' was the title of an article by Peter Bauer that appeared 1989 in the German journal Biometrie und Informatik in Medizin und Biologie. The journal does not exist anymore but the methodology found widespread interest in the scientific community over the past 25 years. The use of such multistage adaptive designs raised many controversial discussions from the beginning on, especially after the publication by Bauer and Köhne 1994 in Biometrics: Broad enthusiasm about potential applications of such designs faced critical positions regarding their statistical efficiency. Despite, or possibly because of, this controversy, the methodology and its areas of applications grew steadily over the years, with significant contributions from statisticians working in academia, industry and agencies around the world. In the meantime, such type of adaptive designs have become the subject of two major regulatory guidance documents in the US and Europe and the field is still evolving. Developments are particularly noteworthy in the most important applications of adaptive designs, including sample size reassessment, treatment selection procedures, and population enrichment designs. In this article, we summarize the developments over the past 25 years from different perspectives. We provide a historical overview of the early days, review the key methodological concepts and summarize regulatory and industry perspectives on such designs. Then, we illustrate the application of adaptive designs with three case studies, including unblinded sample size reassessment, adaptive treatment selection, and adaptive endpoint selection. We also discuss the availability of software for evaluating and performing such designs. We conclude with a critical review of how expectations from the beginning were fulfilled, and - if not - discuss potential reasons why this did not happen.
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Affiliation(s)
- Peter Bauer
- Section of Medical StatisticsMedical University of ViennaSpitalgasse 231090 WienAustria
| | - Frank Bretz
- Novartis Pharma AGLichtstrasse 354002BaselSwitzerland
- Shanghai University of Finance and EconomicsChina
| | | | - Franz König
- Section of Medical StatisticsMedical University of ViennaSpitalgasse 231090 WienAustria
| | - Gernot Wassmer
- Aptiv Solutions, an ICON plc companyRobert‐Perthel‐Str. 77a50739KölnGermany
- Institute for Medical Statistics, Informatics and EpidemiologyUniversity of Cologne50924KölnGermany
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Abstract
Adaptive designs have generated a great deal of attention to clinical trial communities. The literature contains many statistical methods to deal with added statistical uncertainties concerning the adaptations. Increasingly encountered in regulatory applications are adaptive statistical information designs that allow modification of sample size or related statistical information and adaptive selection designs that allow selection of doses or patient populations during the course of a clinical trial. For adaptive statistical information designs, a few statistical testing methods are mathematically equivalent, as a number of articles have stipulated, but arguably there are large differences in their practical ramifications. We pinpoint some undesirable features of these methods in this work. For adaptive selection designs, the selection based on biomarker data for testing the correlated clinical endpoints may increase statistical uncertainty in terms of type I error probability, and most importantly the increased statistical uncertainty may be impossible to assess.
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Affiliation(s)
- H M James Hung
- a Division of Biometrics I , Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration , Silver Spring , Maryland , USA
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Elsäßer A, Regnstrom J, Vetter T, Koenig F, Hemmings RJ, Greco M, Papaluca-Amati M, Posch M. Adaptive clinical trial designs for European marketing authorization: a survey of scientific advice letters from the European Medicines Agency. Trials 2014; 15:383. [PMID: 25278265 PMCID: PMC4196072 DOI: 10.1186/1745-6215-15-383] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2014] [Accepted: 09/08/2014] [Indexed: 11/28/2022] Open
Abstract
Background Since the first methodological publications on adaptive study design approaches in the 1990s, the application of these approaches in drug development has raised increasing interest among academia, industry and regulators. The European Medicines Agency (EMA) as well as the Food and Drug Administration (FDA) have published guidance documents addressing the potentials and limitations of adaptive designs in the regulatory context. Since there is limited experience in the implementation and interpretation of adaptive clinical trials, early interaction with regulators is recommended. The EMA offers such interactions through scientific advice and protocol assistance procedures. Methods We performed a text search of scientific advice letters issued between 1 January 2007 and 8 May 2012 that contained relevant key terms. Letters containing questions related to adaptive clinical trials in phases II or III were selected for further analysis. From the selected letters, important characteristics of the proposed design and its context in the drug development program, as well as the responses of the Committee for Human Medicinal Products (CHMP)/Scientific Advice Working Party (SAWP), were extracted and categorized. For 41 more recent procedures (1 January 2009 to 8 May 2012), additional details of the trial design and the CHMP/SAWP responses were assessed. In addition, case studies are presented as examples. Results Over a range of 5½ years, 59 scientific advices were identified that address adaptive study designs in phase II and phase III clinical trials. Almost all were proposed as confirmatory phase III or phase II/III studies. The most frequently proposed adaptation was sample size reassessment, followed by dropping of treatment arms and population enrichment. While 12 (20%) of the 59 proposals for an adaptive clinical trial were not accepted, the great majority of proposals were accepted (15, 25%) or conditionally accepted (32, 54%). In the more recent 41 procedures, the most frequent concerns raised by CHMP/SAWP were insufficient justifications of the adaptation strategy, type I error rate control and bias. Conclusions For the majority of proposed adaptive clinical trials, an overall positive opinion was given albeit with critical comments. Type I error rate control, bias and the justification of the design are common issues raised by the CHMP/SAWP.
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Affiliation(s)
| | | | | | | | | | | | | | - Martin Posch
- Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
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Chen YHJ, Gesser R, Luxembourg A. A seamless phase IIB/III adaptive outcome trial: design rationale and implementation challenges. Clin Trials 2014; 12:84-90. [PMID: 25278227 DOI: 10.1177/1740774514552110] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The licensed four-valent prophylactic human papillomavirus vaccine is highly efficacious in preventing cervical, vulvar, vaginal, and anal cancers and related precancers caused by human papillomavirus types 6, 11, 16, and 18. These four types account for approximately 70% of cervical cancers. A nine-valent human papillomavirus vaccine, including the four original types (6, 11, 16, and 18) plus the next five most prevalent types in cervical cancer (31, 33, 45, 52, and 58) could provide approximately 90% overall cervical cancer coverage. To expedite the nine-valent human papillomavirus vaccine clinical development, an adaptive, seamless Phase IIB/III outcome trial with ∼ 15,000 subjects was conducted to facilitate dose formulation selection and provide pivotal evidence of safety and efficacy for regulatory registrations. PURPOSE We discuss the design rationale and implementation challenges of the outcome trial, focusing on the adaptive feature of the seamless Phase IIB/III design. METHODS Subjects were enrolled in two parts (Part A and Part B). Approximately 1240 women, 16-26 years of age, were enrolled in Part A for Phase IIB evaluation and equally randomized to one of three dose formulations of the nine-valent human papillomavirus vaccine or the four-valent human papillomavirus vaccine (active control). Based on an interim analysis of immunogenicity and safety, one dose formulation of the nine-valent human papillomavirus vaccine was selected for evaluation in the Phase III part of the study. Subjects enrolled in Part A who received the selected dose formulation of the nine-valent human papillomavirus vaccine or four-valent human papillomavirus vaccine continued to be followed up and contributed to the final efficacy and safety analyses. In addition, ∼ 13,400 women 16-26 years of age were enrolled in Part B, randomized to nine-valent human papillomavirus vaccine at the selected dose formulation or four-valent human papillomavirus vaccine, and followed for immunogenicity, efficacy, and safety. RESULTS A seamless Phase IIB/III design was justified by the extensive pre-existing knowledge of the licensed four-valent human papillomavirus vaccine and the development objectives for the nine-valent human papillomavirus vaccine. Subjects enrolled in Part A who received either the selected nine-valent human papillomavirus formulation or four-valent human papillomavirus vaccine contributed ∼ 10% of person-years of follow-up due to its earlier start-thereby maximizing the overall efficiency of the trial. Some of the challenges encountered in the implementation of the adaptive design included practical considerations during Phase IIB formulation selection by internal and external committees, End-of-Phase II discussion with health authorities and managing changes in the assay for immunological endpoints. LIMITATIONS Application of the experience and lesson learned from this seamless adaptive design to other clinical programs may depend on case-by-case consideration. CONCLUSION A seamless Phase IIB/III adaptive design was successfully implemented in this large outcome study. The development time of the second-generation nine-valent human papillomavirus vaccine was shortened due to improved statistical efficiency.
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Affiliation(s)
| | - Richard Gesser
- Merck & Co., Inc., Whitehouse Station, NJ, USA Sanofi-Pasteur, Swiftwater, PA, USA
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Bebu I, Dragalin V, Luta G. Confidence intervals for confirmatory adaptive two-stage designs with treatment selection. Biom J 2014; 55:294-309. [DOI: 10.1002/bimj.201200053] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2012] [Revised: 02/04/2013] [Accepted: 02/08/2013] [Indexed: 11/08/2022]
Affiliation(s)
- Ionut Bebu
- Infectious Disease Clinical Research Program; Department of Preventive Medicine and Biometrics; Uniformed Services University of the Health Sciences; 4301 Jones Bridge Road Bethesda MD 20814 USA
| | | | - George Luta
- Department of Biostatistics; Bioinformatics, and Biomathematics; Georgetown University Medical Center; 4000 Reservoir Road Washington DC 20057 USA
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Hung HMJ, Wang SJ. Multiple comparisons in complex clinical trial designs. Biom J 2014; 55:420-9. [DOI: 10.1002/bimj.201200048] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2012] [Revised: 12/04/2012] [Accepted: 12/14/2012] [Indexed: 11/08/2022]
Affiliation(s)
- H. M. James Hung
- Division of Biometrics I; OB/OTS/CDER; US FDA; 10903 New Hampshire Ave, HFD-710 Silver Spring MD 20993-0002 USA
| | - Sue-Jane Wang
- Office of Biostatistics; OTS/CDER; US FDA; 10903 New Hampshire Ave, HFD-700 Silver Spring MD 20993-0002 USA
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10
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Abstract
Developments in genomics are providing a biological basis for the heterogeneity of clinical course and response to treatment that have long been apparent to clinicians. The ability to molecularly characterize human diseases presents new opportunities to develop more effective treatments and new challenges for the design and analysis of clinical trials. In oncology, treatment of broad populations with regimens that benefit a minority of patients is less economically sustainable with expensive molecularly targeted therapeutics. The established molecular heterogeneity of human diseases requires the development of new paradigms for the design and analysis of randomized clinical trials as a reliable basis for predictive medicine. We review prospective designs for the development of new therapeutics and predictive biomarkers to inform their use. We cover designs for a wide range of settings. At one extreme is the development of a new drug with a single candidate biomarker and strong biological evidence that marker negative patients are unlikely to benefit from the new drug. At the other extreme are phase III clinical trials involving both genome-wide discovery of a predictive classifier and internal validation of that classifier. We have outlined a prediction based approach to the analysis of randomized clinical trials that both preserves the type I error and provides a reliable internally validated basis for predicting which patients are most likely or unlikely to benefit from a new regimen.
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Affiliation(s)
- Richard Simon
- Biometric Research Branch, National Cancer Institute , Bethesda, MD , USA
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Wang* SJ, Brannath* W, Brückner M, James Hung HM, Koch A. Unblinded Adaptive Statistical Information Design Based on Clinical Endpoint or Biomarker. Stat Biopharm Res 2013. [DOI: 10.1080/19466315.2013.791639] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Verheugt FW, Clemmensen P, Mehran R, Agewall S, Pocock SJ, Goldstein S, Torp-Pedersen C, Simoons ML, Borer JS, Khder YM, Burton P, Deliargyris E, McMurray JJ, Berkowitz SD, Stough WG, Zannad F. Antithrombotic outcome trials in acute coronary syndromes: seeking the optimal balance between safety and efficacy†. Eur Heart J 2013; 34:1621-9. [DOI: 10.1093/eurheartj/eht013] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Wang SJ, Hung HMJ, O'Neill R. Paradigms for adaptive statistical information designs: practical experiences and strategies. Stat Med 2012; 31:3011-23. [PMID: 22927234 DOI: 10.1002/sim.5410] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2012] [Accepted: 03/16/2012] [Indexed: 11/07/2022]
Abstract
In the last decade or so, interest in adaptive design clinical trials has gradually been directed towards their use in regulatory submissions by pharmaceutical drug sponsors to evaluate investigational new drugs. Methodological advances of adaptive designs are abundant in the statistical literature since the 1970s. The adaptive design paradigm has been enthusiastically perceived to increase the efficiency and to be more cost-effective than the fixed design paradigm for drug development. Much interest in adaptive designs is in those studies with two-stages, where stage 1 is exploratory and stage 2 depends upon stage 1 results, but where the data of both stages will be combined to yield statistical evidence for use as that of a pivotal registration trial. It was not until the recent release of the US Food and Drug Administration Draft Guidance for Industry on Adaptive Design Clinical Trials for Drugs and Biologics (2010) that the boundaries of flexibility for adaptive designs were specifically considered for regulatory purposes, including what are exploratory goals, and what are the goals of adequate and well-controlled (A&WC) trials (2002). The guidance carefully described these distinctions in an attempt to minimize the confusion between the goals of preliminary learning phases of drug development, which are inherently substantially uncertain, and the definitive inference-based phases of drug development. In this paper, in addition to discussing some aspects of adaptive designs in a confirmatory study setting, we underscore the value of adaptive designs when used in exploratory trials to improve planning of subsequent A&WC trials. One type of adaptation that is receiving attention is the re-estimation of the sample size during the course of the trial. We refer to this type of adaptation as an adaptive statistical information design. Specifically, a case example is used to illustrate how challenging it is to plan a confirmatory adaptive statistical information design. We highlight the substantial risk of planning the sample size for confirmatory trials when information is very uninformative and stipulate the advantages of adaptive statistical information designs for planning exploratory trials. Practical experiences and strategies as lessons learned from more recent adaptive design proposals will be discussed to pinpoint the improved utilities of adaptive design clinical trials and their potential to increase the chance of a successful drug development.
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Affiliation(s)
- Sue-Jane Wang
- Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, U.S.A.
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Wang SJ, Hung HMJ, O'Neill R. Regulatory perspectives on multiplicity in adaptive design clinical trials throughout a drug development program. J Biopharm Stat 2011; 21:846-59. [PMID: 21516573 DOI: 10.1080/10543406.2011.552878] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
A clinical research program for drug development often consists of a sequence of clinical trials that may begin with uncontrolled and nonrandomized trials, followed by randomized trials or randomized controlled trials. Adaptive designs are not infrequently proposed for use. In the regulatory setting, the success of a drug development program can be defined to be that the experimental treatment at a specific dose level including regimen and frequency is approved based on replicated evidence from at least two confirmatory trials. In the early stage of clinical research, multiplicity issues are very broad. What is the maximum tolerable dose in an adaptive dose escalation trial? What should the dose range be to consider in an adaptive dose-ranging trial? What is the minimum effective dose in an adaptive dose-response study given the tolerability and the toxicity observable in short term or premarketing trials? Is establishing the dose-response relationship important or the ability to select a superior treatment with high probability more important? In the later stage of clinical research, multiplicity problems can be formulated with better focus, depending on whether the study is for exploration to estimate or select design elements or for labeling consideration. What is the study objective for an early-phase versus a later phase adaptive clinical trial? How many doses are to be studied in the early exploratory adaptive trial versus in the confirmatory adaptive trial? Is the intended patient population well defined or is the applicable patient population yet to be adaptively selected in the trial due to the potential patient and/or disease heterogeneity? Is the primary efficacy endpoint well defined or still under discussion providing room for adaptation? What are the potential treatment indications that may adaptively lead to an intended-to-treat patient population and the primary efficacy endpoint? In this work we stipulate the multiplicity issues with adaptive designs encountered in regulatory applications. For confirmatory adaptive design clinical trials, controlling studywise type I error and type II error is of paramount importance. For exploratory adaptive trials, we define the probability of correct selection of design features, e.g., dose, effect size, and the probability of correct decision for drug development. We assert that maximizing these probabilities would be critical to determine whether the drug development program continues or how to plan the confirmatory trials if the development continues.
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Affiliation(s)
- Sue-Jane Wang
- Office of Biostatistics, OTS/CDER, FDA, Silver Spring, Maryland 20993-0002, USA.
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Wang SJ. Editorial: Adaptive designs: appealing in development of therapeutics, and where do controversies lie? J Biopharm Stat 2011; 20:1083-7. [PMID: 21058102 DOI: 10.1080/10543406.2010.514461] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Brefz F, Wang SJ. From Adaptive Design to Modern Protocol Design for Drug Development: Part II. Success Probabilities and Effect Estimates for Phase 3 Development Programs. ACTA ACUST UNITED AC 2010. [DOI: 10.1177/009286151004400315] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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