579 results
Search Results
2. Multiplicity Adjustment in Seamless Phase II/III Adaptive Trials Using Biomarkers for Dose Selection
- Author
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Li, Pei, Zhao, Yanli, Sun, Xiao, Chan, Ivan S.F., Chen, Jiahua, Series editor, Chen, Ding-Geng (Din), Series editor, Chen, Zhen, editor, Liu, Aiyi, editor, Qu, Yongming, editor, Tang, Larry, editor, Ting, Naitee, editor, and Tsong, Yi, editor
- Published
- 2015
- Full Text
- View/download PDF
3. Using Graph Transformations in Distributed Adaptive Design System
- Author
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Kotulski, Leszek, Strug, Barbara, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Bolc, Leonard, editor, Kulikowski, Juliusz L., editor, and Wojciechowski, Konrad, editor
- Published
- 2009
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4. Perspective on adaptive designs: 4 years European Medicines Agency reflection paper, 1 year draft US FDA guidance – where are we now?
- Author
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Armin Koch, Frank Miller, Sue-Jane Wang, Martin Posch, Brenda Gaydos, and Marc Vandemeulebroecke
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medicine.medical_specialty ,Reflection (computer programming) ,business.industry ,Adaptive design ,Agency (sociology) ,Perspective (graphical) ,Alternative medicine ,Medicine ,Guidance documents ,General Medicine ,Public relations ,business ,Panel discussion - Abstract
Adaptive clinical trials attract great attention from academia, industry and regulatory authorities. Both the European Medicines Agency and the US FDA have clarified their positions in recently issued (final or draft) guidance documents. With this background, current trends and issues were analyzed in a panel discussion at the International Society for Biopharmaceutical Statistics (ISBS) meeting in March 2011. In this article, members of the panel summarize their thoughts based on this discussion.
- Published
- 2012
5. Leading changes through adaptive design : Change management practice in one of the universities in a developing nation
- Author
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Muluneh, Girma Shimelis and Gedifew, Matebe Tafere
- Published
- 2018
- Full Text
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6. Introduction to Discussion Papers on Draft FDA Guidance on Adaptive Designs
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Mark Chang
- Subjects
Pharmacology ,Statistics and Probability ,Food and drug administration ,Engineering management ,Computer science ,Process (engineering) ,Adaptive design ,Pharmacology (medical) ,health care economics and organizations - Abstract
Congratulations to the Food and Drug Administration (FDA) on its draft guidance on adaptive design (AD). It is a huge step toward adopting an innovative approach and streamlining the process of ada...
- Published
- 2010
7. Survey and Optimization Design of Urban Public Space in China
- Author
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LUXiaohui, HEQuan, and LIQi
- Published
- 2018
- Full Text
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8. Optimal promising zone designs
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Cyrus R. Mehta, Lingyun Liu, and Samuel T. Hsiao
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Statistics and Probability ,Optimal design ,Mathematical optimization ,Biometry ,Computer science ,01 natural sciences ,gold standard sample size reassessment rule ,promising zone design ,sample size reassessment ,010104 statistics & probability ,03 medical and health sciences ,0302 clinical medicine ,Interim ,Test statistic ,adaptive design ,power comparisons of adaptive versus nonadaptive ,Humans ,030212 general & internal medicine ,group sequential design ,0101 mathematics ,trial optimization ,Expected utility hypothesis ,Clinical Trials as Topic ,optimal adaptive design ,General Medicine ,Decision rule ,Class (biology) ,Research Papers ,Pancreatic Neoplasms ,Sample size determination ,Statistics, Probability and Uncertainty ,Construct (philosophy) ,Research Paper - Abstract
Clinical trials with adaptive sample size reassessment based on an unblinded analysis of interim results are perhaps the most popular class of adaptive designs (see Elsäßer et al., 2007). Such trials are typically designed by prespecifying a zone for the interim test statistic, termed the promising zone, along with a decision rule for increasing the sample size within that zone. Mehta and Pocock (2011) provided some examples of promising zone designs and discussed several procedures for controlling their type‐1 error. They did not, however, address how to choose the promising zone or the corresponding sample size reassessment rule, and proposed instead that the operating characteristics of alternative promising zone designs could be compared by simulation. Jennison and Turnbull (2015) developed an approach based on maximizing expected utility whereby one could evaluate alternative promising zone designs relative to a gold‐standard optimal design. In this paper, we show how, by eliciting a few preferences from the trial sponsor, one can construct promising zone designs that are both intuitive and achieve the Jennison and Turnbull (2015) gold‐standard for optimality.
- Published
- 2018
9. A novel equivalence probability weighted power prior for using historical control data in an adaptive clinical trial design: a comparison to standard methods
- Author
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Nicky Best, Adrian Mander, Maxine Bennett, Simon R. White, Bennett, Maxine [0000-0001-6298-519X], White, Simon [0000-0001-8642-7037], Best, Nicky [0000-0003-4120-9727], and Apollo - University of Cambridge Repository
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Statistics and Probability ,Computer science ,Bayesian probability ,01 natural sciences ,Bayesian ,law.invention ,borrowing ,010104 statistics & probability ,03 medical and health sciences ,0302 clinical medicine ,Randomized controlled trial ,law ,Statistics ,Prior probability ,Main Paper ,adaptive design ,Humans ,Pharmacology (medical) ,030212 general & internal medicine ,0101 mathematics ,Equivalence (measure theory) ,priors ,Probability ,Pharmacology ,Adaptive clinical trial ,Bayes Theorem ,Interim analysis ,historical data ,Research Design ,Sample Size ,Binary data ,Main Papers ,Type I and type II errors - Abstract
Funder: National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre, A standard two-arm randomised controlled trial usually compares an intervention to a control treatment with equal numbers of patients randomised to each treatment arm and only data from within the current trial are used to assess the treatment effect. Historical data are used when designing new trials and have recently been considered for use in the analysis when the required number of patients under a standard trial design cannot be achieved. Incorporating historical control data could lead to more efficient trials, reducing the number of controls required in the current study when the historical and current control data agree. However, when the data are inconsistent, there is potential for biased treatment effect estimates, inflated type I error and reduced power. We introduce two novel approaches for binary data which discount historical data based on the agreement with the current trial controls, an equivalence approach and an approach based on tail area probabilities. An adaptive design is used where the allocation ratio is adapted at the interim analysis, randomising fewer patients to control when there is agreement. The historical data are down-weighted in the analysis using the power prior approach with a fixed power. We compare operating characteristics of the proposed design to historical data methods in the literature: the modified power prior; commensurate prior; and robust mixture prior. The equivalence probability weight approach is intuitive and the operating characteristics can be calculated exactly. Furthermore, the equivalence bounds can be chosen to control the maximum possible inflation in type I error.
- Published
- 2021
10. Molecular Recognition of Disaccharides in Water: Preorganized Macrocyclic or Adaptive Acyclic?
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Oscar Francesconi, Francesco Milanesi, Stefano Roelens, and Cristina Nativi
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Models, Molecular ,Molecular model ,carbohydrates ,Hot Paper ,receptors ,Disaccharides ,010402 general chemistry ,01 natural sciences ,Catalysis ,Core fragment ,Molecular recognition ,Full Paper ,010405 organic chemistry ,Chemistry ,chitobiose ,hydrogen bonds ,molecular recognition ,Carbohydrates ,Hydrogen Bonding ,Water ,Organic Chemistry ,Binding properties ,General Chemistry ,Full Papers ,Combinatorial chemistry ,0104 chemical sciences ,Adaptive design - Abstract
When facing the dilemma of following a preorganized or adaptive design approach in conceiving the architecture of new biomimetic receptors for carbohydrates, shape‐persistent macrocyclic structures were most often chosen to achieve effective recognition of neutral saccharides in water. In contrast, acyclic architectures have seldom been explored, even though potentially simpler and more easily accessible. In this work, comparison of the binding properties of two structurally related diaminocarbazolic receptors, featuring a macrocyclic and an acyclic tweezer‐shaped architecture, highlighted the advantages provided by the acyclic receptor in terms of selectivity in the recognition of 1,4‐disaccharides of biological interest. Selective recognition of GlcNAc2, the core fragment of N‐glycans exposed on the surface of enveloped viruses, stands as an emblematic example. NMR spectroscopic data and molecular modeling calculations were used to ascertain the differences in binding mode and to shed light on the origin of recognition efficacy and selectivity., Adaptive to be selective: Comparison of the binding properties of two structurally related biomimetic receptors toward disaccharides sheds light on the differences between a rigid macrocyclic architecture and a flexible tweezer‐shaped structure showing, counterintuitively, that the adaptive structure can be advantageous in terms of selectivity. NMR spectroscopy and molecular modeling calculations were used to provide a 3D description of the receptor‐disaccharide complexes in solution and explaining the origin of the observed selectivity.
- Published
- 2021
11. Approach to Human-Centered, Evidence-Driven Adaptive Design (AHEAD) for Health Care Interventions: a Proposed Framework
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Meredith Fischer, Marie C. Haverfield, Cati Brown-Johnson, Nadia Safaeinili, Dani Zionts, and Donna M. Zulman
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Review Paper ,Process management ,business.industry ,Intervention design ,010102 general mathematics ,Innovation process ,Health services research ,Psychological intervention ,01 natural sciences ,03 medical and health sciences ,0302 clinical medicine ,Research Design ,Adaptive design ,Health care ,Internal Medicine ,Medicine ,Humans ,030212 general & internal medicine ,Health Services Research ,0101 mathematics ,Empathy ,User needs ,business ,Delivery of Health Care ,User-centered design - Abstract
Human-centered design (HCD), an empathy-driven approach to innovation that focuses on user needs, offers promise for the rapid design of health care interventions that are acceptable to patients, clinicians, and other stakeholders. Reviews of HCD in healthcare, however, note a need for greater rigor, suggesting an opportunity for integration of elements from traditional research and HCD. A strategy that combines HCD principles with evidence-grounded health services research (HSR) methods has the potential to strengthen the innovation process and outcomes. In this paper, we review the strengths and limitations of HCD and HSR methods for intervention design, and propose a novel Approach to Human-centered, Evidence-driven Adaptive Design (AHEAD) framework. AHEAD offers a practical guide for the design of creative, evidence-based, pragmatic solutions to modern healthcare challenges.
- Published
- 2020
12. Mobile isolation wards in a fever clinic: a novel operation model during the COVID-19 pandemic
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Yilin Chen, Bin Zhou, Yong Gao, Peng Sun, Rui Chang, Anbang Cheng, Fanjun Cheng, and Hui Qiu
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0301 basic medicine ,2019-20 coronavirus outbreak ,China ,fever clinic ,Isolation (health care) ,Coronavirus disease 2019 (COVID-19) ,Fever ,Epidemiology ,Patient Isolation ,03 medical and health sciences ,0302 clinical medicine ,Battlefield ,Medical waste ,Pandemic ,Medicine ,Humans ,030212 general & internal medicine ,Operation model ,Original Paper ,Infection Control ,business.industry ,COVID-19 ,medicine.disease ,innovation ,030104 developmental biology ,Infectious Diseases ,mobile isolation wards ,Adaptive design ,Models, Organizational ,Medical emergency ,business - Abstract
A fever clinic within a hospital plays a vital role in pandemic control because it serves as an outpost for pandemic discovery, monitoring and handling. As the outbreak of coronavirus disease 2019 (COVID-19) in Wuhan was gradually brought under control, the fever clinic in the West Campus of Wuhan Union Hospital introduced a new model for construction and management of temporary mobile isolation wards. A traditional battlefield hospital model was combined with pandemic control regulations, to build a complex of mobile isolation wards that used adaptive design and construction for medical operational, medical waste management and water drainage systems. The mobile isolation wards allowed for the sharing of medical resources with the fever clinic. This increased the capacity and efficiency of receiving, screening, triaging and isolation and observation of patients with fever. The innovative mobile isolation wards also controlled new sudden outbreaks of COVID-19. We document the adaptive design and construction model of the novel complex of mobile isolation wards and explain its characteristics, functions and use.
- Published
- 2021
13. Blinded and unblinded sample size reestimation in crossover trials balanced for period
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Adrian Mander, Michael J. Grayling, and James Wason
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Statistics and Probability ,Biometry ,Randomization ,Blinding ,Computer science ,Crossover ,Kaplan-Meier Estimate ,01 natural sciences ,Statistics, Nonparametric ,sample size reestimation ,010104 statistics & probability ,03 medical and health sciences ,0302 clinical medicine ,Statistics ,Humans ,030212 general & internal medicine ,0101 mathematics ,Clinical Trials as Topic ,Cross-Over Studies ,Models, Statistical ,Clinical study design ,Estimator ,Issues in Complex Clinical Trials ,General Medicine ,Crossover study ,blinded ,Sample size determination ,Sample Size ,Adaptive design ,Heart Transplantation ,Regression Analysis ,crossover trial ,Statistics, Probability and Uncertainty ,internal pilot study ,Research Paper - Abstract
The determination of the sample size required by a crossover trial typically depends on the specification of one or more variance components. Uncertainty about the value of these parameters at the design stage means that there is often a risk a trial may be under‐ or overpowered. For many study designs, this problem has been addressed by considering adaptive design methodology that allows for the re‐estimation of the required sample size during a trial. Here, we propose and compare several approaches for this in multitreatment crossover trials. Specifically, regulators favor reestimation procedures to maintain the blinding of the treatment allocations. We therefore develop blinded estimators for the within and between person variances, following simple or block randomization. We demonstrate that, provided an equal number of patients are allocated to sequences that are balanced for period, the proposed estimators following block randomization are unbiased. We further provide a formula for the bias of the estimators following simple randomization. The performance of these procedures, along with that of an unblinded approach, is then examined utilizing three motivating examples, including one based on a recently completed four‐treatment four‐period crossover trial. Simulation results show that the performance of the proposed blinded procedures is in many cases similar to that of the unblinded approach, and thus they are an attractive alternative.
- Published
- 2018
14. A constrained optimum adaptive design for dose finding in early phase clinical trials.
- Author
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Alam, M. Iftakhar, Bogacka, Barbara, and Coad, D. Stephen
- Abstract
Recently, interest has grown in the development of dose-finding methods that consider both toxicity and efficacy as endpoints. Along with responses on these, the incorporation of pharmacokinetic (PK) data can be beneficial in terms of patients’ safety and can also increase the efficiency of the design for finding the best dose for the next phase. In this paper, the maximum concentration (${C_{\max }}$Cmax) is used as the PK measure guiding the dose selection. The ethically attractive approach, which is based on the probability of efficacy, is used as a dose optimisation criterion. At each stage of an adaptive trial, that dose is selected for which the criterion is maximised, subject to the constraints imposed on the ${C_{\max }}$Cmax and the probability of toxicity. The inter-patient variability of the PK model parameters is considered, and population $D$D-optimal sampling time points for measuring the concentration of a drug in the blood are calculated. The method is illustrated with a one-compartment PK model with first-order absorption, with the parameters being assumed to be random. The Cox model for bivariate binary responses is employed to model the dose–response outcomes. The results of a simulation study for several plausible dose–response scenarios show a significant gain in the efficiency of the design, as well as a reduction in the proportion of toxic responses. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
15. A review and re‐interpretation of a group‐sequential approach to sample size re‐estimation in two‐stage trials
- Author
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Jack Bowden and Adrian Mander
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Pharmacology ,Statistics and Probability ,Research design ,Estimation ,conditional power ,Computer science ,sample size re-estimation ,Standard methods ,median unbiased estimation ,Interpretation (model theory) ,Research Design ,Sample size determination ,Data Interpretation, Statistical ,Sample Size ,Adaptive design ,Statistics ,Group sequential ,Econometrics ,Main Papers ,two-stage trial ,Humans ,Pharmacology (medical) ,Biostatistics ,Randomized Controlled Trials as Topic - Abstract
In this paper, we review the adaptive design methodology of Li et al. (Biostatistics 3:277–287) for two-stage trials with mid-trial sample size adjustment. We argue that it is closer in principle to a group sequential design, in spite of its obvious adaptive element. Several extensions are proposed that aim to make it even more attractive and transparent alternative to a standard (fixed sample size) trial for funding bodies to consider. These enable a cap to be put on the maximum sample size and for the trial data to be analysed using standard methods at its conclusion. The regulatory view of trials incorporating unblinded sample size re-estimation is also discussed. © 2014 The Authors. Pharmaceutical Statistics published by John Wiley & Sons, Ltd.
- Published
- 2014
16. An adaptive seamless 2-in-1 design with biomarker-driven subgroup enrichment.
- Author
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Wu, Liwen and Lin, Jianchang
- Abstract
Adaptive seamless phase 2/3 subgroup enrichment design plays a pivotal role in streamlining efficient drug development within a competitive landscape, while also enhancing patient access to promising treatments. This design approach identifies biomarker subgroups with the highest potential to benefit from investigational regimens. The seamless integration of Phase 2 and Phase 3 ensures a timely confirmation of clinical benefits. One significant challenge in adaptive enrichment decisions is determining the optimal timing and maturity of the primary endpoint. In this paper, we propose an adaptive seamless 2-in-1 biomarker-driven subgroup enrichment design that addresses this challenge by allowing subgroup selection using an early intermediate endpoint that predicts clinical benefits (i.e. a surrogate endpoint). The proposed design initiates with a Phase 2 stage involving all participants and can potentially expand into a Phase 3 study focused on the subgroup demonstrating the most favorable clinical outcomes. We will show that, under certain correlation assumptions, the overall type I error may not be inflated at the end of the study. In scenarios where the assumptions may not hold, we present a general framework to control the multiplicity. The flexibility and efficacy of the proposed design are highlighted through an extensive simulation study and illustrated in a case study in multiple myeloma. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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17. Incorporating external real-world data (RWD) in confirmatory adaptive design.
- Author
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Lin, Junjing and Lin, Jianchang
- Abstract
Adaptive designs, such as group sequential designs (and the ones with additional adaptive features) or adaptive platform trials, have been quintessential efficient design strategies in trials of unmet medical needs, especially for generating evidence from global regions. Such designs allow interim decision making and making adjustment to study design when necessary, meanwhile maintaining study integrity and operating characteristics. However, driven by the heightened competitive landscape and the desire to bring effective treatment to patients faster, innovation in the already functional designs is still germane to further propel drug development to a more efficient path. One way to achieve this is by leveraging external real-world data (RWD) in the adaptive designs to support interim or final decision making. In this paper, we propose a novel framework of incorporating external RWD in adaptive design to improve interim and/or final analysis decision making. Within this framework, researchers can prespecify the decision process and choose the timing and amount of borrowing while maintaining objectivity and controlling of type I error. Simulation studies in various scenarios are provided to describe power, type I error, and other performance metrics for interim/final decision making. A case study in non-small cell lung cancer is used for illustration on proposed design framework. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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18. DOD-Combo: Bayesian dose finding design in combination trials with meta-analytic-predictive prior.
- Author
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Chen, Kai, Zhao, Yunqi, Liu, Meizi, Lin, Jianchang, and Liu, Rachael
- Abstract
Combination therapy, a treatment modality that involves multiple treatment agents, has become imperative for improving treatment effectiveness and addressing resistance in the field of oncology. However, determining the most effective dose for these combinations, particularly when dealing with intricate drug interactions and diverse toxicity patterns, presents a substantial challenge. This paper introduces a novel Bayesian
do se-findingd esign forcomb inatio n therapies with information borrowing, named the DOD-Combo design. Leveraging historical single-agent trials and the meta-analytic-predictive (MAP) power prior, our approach utilizes a copula-type model to connect individual drug priors with joint toxicity probabilities in combination treatments. The MAP power prior allows the integration of information from multiple historical trials, constructing informative priors for each agent. Extensive simulations confirm our method’s superior performance compared to combination designs with no information borrowing. By adaptively incorporating historical data, our approach reduces sample sizes and enhances efficiency in selecting the maximum tolerated dose (MTD), effectively addressing the intricate challenges presented by combination trials. [ABSTRACT FROM AUTHOR]- Published
- 2024
- Full Text
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19. Propensity score‐incorporated adaptive design approaches when incorporating real‐world data.
- Author
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Lu, Nelson, Chen, Wei‐Chen, Li, Heng, Song, Changhong, Tiwari, Ram, Wang, Chenguang, Xu, Yunling, and Yue, Lilly Q.
- Subjects
- *
SAMPLE size (Statistics) - Abstract
The propensity score‐integrated composite likelihood (PSCL) method is one method that can be utilized to design and analyze an application when real‐world data (RWD) are leveraged to augment a prospectively designed clinical study. In the PSCL, strata are formed based on propensity scores (PS) such that similar subjects in terms of the baseline covariates from both the current study and RWD sources are placed in the same stratum, and then composite likelihood method is applied to down‐weight the information from the RWD. While PSCL was originally proposed for a fixed design, it can be extended to be applied under an adaptive design framework with the purpose to either potentially claim an early success or to re‐estimate the sample size. In this paper, a general strategy is proposed due to the feature of PSCL. For the possibility of claiming early success, Fisher's combination test is utilized. When the purpose is to re‐estimate the sample size, the proposed procedure is based on the test proposed by Cui, Hung, and Wang. The implementation of these two procedures is demonstrated via an example. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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- View/download PDF
20. Can Appended Auxiliary Data be Used to Tailor the Offered Response Mode in Cross-Sectional Studies? Evidence from An Address-Based Sample.
- Author
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Jackson, Michael T, Medway, Rebecca L, and Megra, Mahi W
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CROSS-sectional method , *ANTILOCK brake systems in automobiles , *TAILORS , *HOUSEHOLD surveys - Abstract
In theory, offering each sample member the mode sequence that maximizes their response propensity should increase the response rate and/or reduce the amount of nonresponse follow-up relative to a design that offers all sample members the same mode sequence. However, for this sort of tailoring to be feasible in a cross-sectional survey, it must be possible to use data available prior to data collection (e.g. on the sampling frame) to predict sample members' "mode-sensitivity"—the effect of the offered mode sequence on response propensity. Using data from randomized experiments incorporated into the 2016 and 2019 cycles of the National Household Education Survey, we evaluate whether data appended to an address-based sampling (ABS) frame can accurately predict the sensitivity of household-level response behavior to the initial offer of a paper questionnaire instead of a web instrument and whether a modeled-mode design that tailors the offered mode sequence (web-push vs. paper-only) based on the resulting predictions improves household-level data collection outcomes relative to a uniform web-push design. We find that several characteristics available on the ABS frame show statistically significant interactions with the offered mode sequence in determining the probability of response to initial survey mailings. Consequently, relative to a uniform web-push design, the modeled-mode design increased the response rate to early mailings and reduced the number of mailings required per response. However, the modeled-mode design did not meaningfully increase the final response rate, nor did it lead to a substantial reduction in indicators of nonresponse bias. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
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21. Adaptive Bayesian Approach to Clinical Trial Renal Impairment Biomarker Signal from Urea and Creatinine
- Author
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Gordon F. Kapke, Jean-Marc Leroux, and Pierre-Edouard Sottas
- Subjects
Databases, Factual ,Pharmacology ,Applied Microbiology and Biotechnology ,chemistry.chemical_compound ,Reference Values ,Medicine ,Urea ,Renal Insufficiency ,media_common ,renal toxicity ,Aged, 80 and over ,education.field_of_study ,Clinical Trials as Topic ,Middle Aged ,biomarker signal ,Creatinine ,Toxicity ,Biomarker (medicine) ,Research Paper ,Drug ,Adult ,medicine.medical_specialty ,Drug-Related Side Effects and Adverse Reactions ,media_common.quotation_subject ,Population ,Bayesian probability ,Urology ,Statistics, Nonparametric ,adaptive design ,Humans ,biologic variation ,Computer Simulation ,education ,Molecular Biology ,Bayesian inference ,Ecology, Evolution, Behavior and Systematics ,Aged ,Retrospective Studies ,individual reference ranges ,Dose-Response Relationship, Drug ,business.industry ,Bayes Theorem ,Cell Biology ,Clinical trial ,chemistry ,Drug Evaluation ,business ,Biomarkers ,Developmental Biology - Abstract
A major concern with the identification of renal toxicity using the traditional biomarkers, urea and creatinine, is that toxicity signal definitions are not sensitive to medically important changes in these biomarkers. Traditional renal signal definitions for urea and creatinine have not adequately identified drugs that have generated important medical issues later in development. Here, two clinical trial databases with a posteriori known drug induced renal impairment were analyzed for the presence of a renal impairment biomarker signal from urea (590 patients; age 26-92, median 65) and creatinine (532 patients; age 26-97, median 65). Data was analyzed retrospectively using multiple definitions for the biomarker signal to include values outside stratified reference intervals, values exceeding twofold increases from baseline, values classified by the 2009 NIAID renal toxicity table, change from baseline represented as a Z-score based on intra-individual biological variations, and an adaptive Bayesian methodology that generalizes population- with individual-based methods for evaluating a biomarker signal. The data demonstrated that the adaptive Bayesian methodology generated a prominent drug induced signal for renal impairment at the first visit after drug administration. The signal was directly related to dose and time of drug administration. All other data analysis methods produced none or significantly weaker signals than the adaptive Bayesian approach. Interestingly, serum creatinine and urea are able to detect early kidney dysfunction when the biomarker signal is personalized.
- Published
- 2013
22. Automated HMI design as a custom feature in industrial SCADA systems.
- Author
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Šverko, Mladen and Grbac, Tihana Galinac
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SUPERVISORY control & data acquisition systems ,INDUSTRIALISM ,CUSTOM design ,MANUFACTURING processes ,SITUATIONAL awareness - Abstract
The adoption of emerging technologies under the Industry 4.0 paradigm has resulted in an increased quantity of data projected on the human-machine interface (HMI). This complexity is imposed in combination with users' limited cognitive capabilities to interpret such data quantity. We foresee this limitation fails to address the human-centric approach of the Industry 5.0 paradigm. To overcome this challenge, an automated approach is proposed to enable user-guided ad hoc visualization forms, which ultimately increases users' situational awareness of supervised industrial processes. In this paper, we present a framework for introducing automated HMI design as a custom feature of standard SCADA-based HMI functionality and showcase an example of how open technology may be used for such purposes, thus opening new avenues for rapid innovation on SCADA HMI. The framework enables integration of the user-initiated additions for loosely coupled visualization components configurable and integrated into the standard HMI runtime layer to meet changing user needs. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
23. Optimizing dose-schedule regimens with bayesian adaptive designs: opportunities and challenges.
- Author
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Xin Chen, Ruyue He, Xinyi Chen, Liyun Jiang, and Fei Wang
- Subjects
CLINICAL trials ,SAMPLE size (Statistics) - Abstract
Due to the small sample sizes in early-phase clinical trials, the toxicity and efficacy profiles of the dose-schedule regimens determined for subsequent trials may not be well established. The recent development of novel anti-tumor treatments and combination therapies further complicates the problem. Therefore, there is an increasing recognition of the essential place of optimizing dose-schedule regimens, and new strategies are now urgently needed. Bayesian adaptive designs provide a potentially effective way to evaluate several doses and schedules simultaneously in a single clinical trial with higher efficiency, but real-world implementation examples of such adaptive designs are still few. In this paper, we cover the critical factors associated with dose-schedule optimization and review the related innovative Bayesian adaptive designs. The assumptions, characteristics, limitations, and application scenarios of those designs are introduced. The review also summarizes some unresolved issues and future research opportunities for dose-schedule optimization. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
24. The Effects of a Targeted "Early Bird" Incentive Strategy on Response Rates, Fieldwork Effort, and Costs in a National Panel Study.
- Author
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McGonagle, Katherine A, Sastry, Narayan, and Freedman, Vicki A
- Subjects
- *
PANEL analysis , *INCENTIVE (Psychology) , *MONETARY incentives , *FIELD research , *COST control - Abstract
Adaptive survey designs are increasingly used by survey practitioners to counteract ongoing declines in household survey response rates and manage rising fieldwork costs. This paper reports findings from an evaluation of an early-bird incentive (EBI) experiment targeting high-effort respondents who participate in the 2019 wave of the US Panel Study of Income Dynamics. We identified a subgroup of high-effort respondents at risk of nonresponse based on their prior wave fieldwork effort and randomized them to a treatment offering an extra time-delimited monetary incentive for completing their interview within the first month of data collection (treatment group; N = 800) or the standard study incentive (control group; N = 400). In recent waves, we have found that the costs of the protracted fieldwork needed to complete interviews with high-effort cases in the form of interviewer contact attempts plus an increased incentive near the close of data collection are extremely high. By incentivizing early participation and reducing the number of interviewer contact attempts and fieldwork days to complete the interview, our goal was to manage both nonresponse and survey costs. We found that the EBI treatment increased response rates and reduced fieldwork effort and costs compared to a control group. We review several key findings and limitations, discuss their implications, and identify the next steps for future research. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
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25. Estimation of conditional power in the presence of auxiliary data.
- Author
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Li, Xin, Yung, Godwin, Lin, Jianchang, and Zhu, Jian
- Subjects
- *
TREATMENT effectiveness , *CLINICAL trials - Abstract
Conditional power (CP) is a commonly used tool to inform interim decision‐making in clinical trials, but the conventional approach using only primary endpoint data to calculate CP may not perform well when the primary endpoint requires a long follow‐up period, or the treatment effect size changes during the trial. Several methods have been proposed to use additional short term auxiliary data observed at the interim analysis to improve the CP estimation in these situations, however, they may rely on strong assumptions, have limited applications, or use ad hoc choices of information fraction. In this paper we propose a general framework where the true CP formula is first derived in the presence of auxiliary data, and CP estimation is obtained by substituting the unknown parameters with consistent estimators. We conducted extensive simulations to examine the performance of both proposed and conventional approaches using the true CP as the benchmark. As the proposed approach is based on the true underlying CP, the simulations confirmed its superiority over the conventional approach in terms of efficiency and accuracy, especially if observed auxiliary data reflect the change of treatment effect size. The simulations also indicate that the magnitude of improvement in CP estimation is associated with the correlation between auxiliary and primary endpoints and/or the magnitude of the effect size change during the trial. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
26. Sample Size Re-estimation with the Com-Nougue Method to Evaluate Treatment Effect.
- Author
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Wang, Jin
- Abstract
The binary endpoint and the time-to-event (TTE) endpoint are the main staple for clinical evaluation. The TTE endpoint is typically utilized when the follow-up is long, and the attrition rate is substantial. In the latter case, if the constant hazard ratio condition is approximately accurate, typically the Cox regression is applied to all available information by accommodating early terminations. However, if the treatment effect is fluctuating over time to such a degree that the proportional hazard ratio assumption is seriously violated, alternative approaches need to be considered, including in the setting of adaptive trial design. Due to the lack of literature focusing on application of the Com-Nougue method in the adaptive trial design, this paper is to highlight the unique features of sample size re-estimation under the Com-Nougue approach in contrast to some typical statistical techniques, with some representative simulations. In most scenarios of the simulations, including both superiority and non-inferiority (NI) tests, constant and piecewise hazard ratio under the exponential distribution, the Com-Nougue method performs well with the adaptive design. Cox regression excels in the proportional hazard ratio setting due to the use of all available data. This paper illustrates the utility of the Com-Nougue method in adaptive clinical trial design. It also provides a simple and convenient approach to calculate the conditional power and sample size under arbitrary underlying true parameter assumptions. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
27. Adaptive treatment allocation and selection in multi-arm clinical trials: a Bayesian perspective.
- Author
-
Arjas, Elja and Gasbarra, Dario
- Subjects
- *
STATISTICAL hypothesis testing , *CLINICAL trials , *FALSE positive error , *VACCINE trials , *OPTIMAL stopping (Mathematical statistics) - Abstract
Background: Adaptive designs offer added flexibility in the execution of clinical trials, including the possibilities of allocating more patients to the treatments that turned out more successful, and early stopping due to either declared success or futility. Commonly applied adaptive designs, such as group sequential methods, are based on the frequentist paradigm and on ideas from statistical significance testing. Interim checks during the trial will have the effect of inflating the Type 1 error rate, or, if this rate is controlled and kept fixed, lowering the power.Results: The purpose of the paper is to demonstrate the usefulness of the Bayesian approach in the design and in the actual running of randomized clinical trials during phase II and III. This approach is based on comparing the performance of the different treatment arms in terms of the respective joint posterior probabilities evaluated sequentially from the accruing outcome data, and then taking a control action if such posterior probabilities fall below a pre-specified critical threshold value. Two types of actions are considered: treatment allocation, putting on hold at least temporarily further accrual of patients to a treatment arm, and treatment selection, removing an arm from the trial permanently. The main development in the paper is in terms of binary outcomes, but extensions for handling time-to-event data, including data from vaccine trials, are also discussed. The performance of the proposed methodology is tested in extensive simulation experiments, with numerical results and graphical illustrations documented in a Supplement to the main text. As a companion to this paper, an implementation of the methods is provided in the form of a freely available R package 'barts'.Conclusion: The proposed methods for trial design provide an attractive alternative to their frequentist counterparts. [ABSTRACT FROM AUTHOR]- Published
- 2022
- Full Text
- View/download PDF
28. Climate Adaptation in Urban Regeneration: A Cross-Scale Digital Design Workflow
- Author
-
Morganti, Michele, Ricci, Diletta, Angelidou, Margarita, Editorial Board Member, Farnaz Arefian, Fatemeh, Editorial Board Member, Batty, Michael, Editorial Board Member, Davoudi, Simin, Editorial Board Member, DeVerteuil, Geoffrey, Editorial Board Member, González Pérez, Jesús M., Editorial Board Member, Hess, Daniel B., Editorial Board Member, Jones, Paul, Editorial Board Member, Karvonen, Andrew, Editorial Board Member, Kirby, Andrew, Editorial Board Member, Kropf, Karl, Editorial Board Member, Lucas, Karen, Editorial Board Member, Maretto, Marco, Editorial Board Member, Modarres, Ali, Editorial Board Member, Neuhaus, Fabian, Editorial Board Member, Nijhuis, Steffen, Editorial Board Member, Aráujo de Oliveira, Vitor Manuel, Editorial Board Member, Silver, Christopher, Editorial Board Member, Strappa, Giuseppe, Editorial Board Member, Vojnovic, Igor, Editorial Board Member, Yamu, Claudia, Editorial Board Member, Zhao, Qunshan, Editorial Board Member, Arbizzani, Eugenio, editor, Cangelli, Eliana, editor, Clemente, Carola, editor, Cumo, Fabrizio, editor, Giofrè, Francesca, editor, Giovenale, Anna Maria, editor, Palme, Massimo, editor, and Paris, Spartaco, editor
- Published
- 2023
- Full Text
- View/download PDF
29. Pattern and Form Language as Constituents of the Mosque Architecture
- Author
-
Samir, Haitham, Amir, Ghaidaa, Hamza, Jouanah, Alshoaibi, Lian, Pisello, Anna Laura, Editorial Board Member, Hawkes, Dean, Editorial Board Member, Bougdah, Hocine, Editorial Board Member, Rosso, Federica, Editorial Board Member, Abdalla, Hassan, Editorial Board Member, Boemi, Sofia-Natalia, Editorial Board Member, Mohareb, Nabil, Editorial Board Member, Mesbah Elkaffas, Saleh, Editorial Board Member, Bozonnet, Emmanuel, Editorial Board Member, Pignatta, Gloria, Editorial Board Member, Mahgoub, Yasser, Editorial Board Member, De Bonis, Luciano, Editorial Board Member, Kostopoulou, Stella, Editorial Board Member, Pradhan, Biswajeet, Editorial Board Member, Abdul Mannan, Md., Editorial Board Member, Alalouch, Chaham, Editorial Board Member, O. Gawad, Iman, Editorial Board Member, Nayyar, Anand, Editorial Board Member, Amer, Mourad, Series Editor, Fekry, Mohammed, editor, Mohamed, Mady A.A., editor, Visvizi, Anna, editor, Ibrahim, Asmaa, editor, and Ghamri, Lamiaa F., editor
- Published
- 2023
- Full Text
- View/download PDF
30. Evolution of Phase II Oncology Trial Design: from Single Arm to Master Protocol.
- Author
-
Yu, Ziji, Wu, Liwen, Bunn, Veronica, Li, Qing, and Lin, Jianchang
- Subjects
EXPERIMENTAL design ,CLINICAL trials ,MEDICAL protocols ,PHYSIOLOGICAL adaptation ,RADIATION doses ,INTERPROFESSIONAL relations ,TUMORS ,DRUG development - Abstract
The recent development of novel anticancer treatments with diverse mechanisms of action has accelerated the detection of treatment candidates tremendously. The rapidly changing drug development landscapes and the high failure rates in Phase III trials both underscore the importance of more efficient and robust phase II designs. The goals of phase II oncology studies are to explore the preliminary efficacy and toxicity of the investigational product and to inform future drug development strategies such as go/no-go decisions for phase III development, or dose/indication selection. These complex purposes of phase II oncology designs call for efficient, flexible, and easy-to-implement clinical trial designs. Therefore, innovative adaptive study designs with the potential of improving the efficiency of the study, protecting patients, and improving the quality of information gained from trials have been commonly used in Phase II oncology studies. Although the value of adaptive clinical trial methods in early phase drug development is generally well accepted, there is no comprehensive review and guidance on adaptive design methods and their best practice for phase II oncology trials. In this paper, we review the recent development and evolution of phase II oncology design, including frequentist multistage design, Bayesian continuous monitoring, master protocol design, and innovative design methods for randomized phase II studies. The practical considerations and the implementation of these complex design methods are also discussed. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
31. Vaccine clinical trials with dynamic borrowing of historical controls: Two retrospective studies.
- Author
-
Callegaro, Andrea, Karkada, Naveen, Aris, Emmanuel, and Zahaf, Toufik
- Subjects
- *
VACCINE trials , *VACCINE development , *HUMAN papillomavirus vaccines , *VACCINE effectiveness , *FALSE positive error - Abstract
Traditional vaccine efficacy trials usually use fixed designs with fairly large sample sizes. Recruiting a large number of subjects requires longer time and higher costs. Furthermore, vaccine developers are more than ever facing the need to accelerate vaccine development to fulfill the public's medical needs. A possible approach to accelerate development is to use the method of dynamic borrowing of historical controls in clinical trials. In this paper, we evaluate the feasibility and the performance of this approach in vaccine development by retrospectively analyzing two real vaccine studies: a relatively small immunological trial (typical early phase study) and a large vaccine efficacy trial (typical Phase 3 study) assessing prophylactic human papillomavirus vaccine. Results are promising, particularly for early development immunological studies, where the adaptive design is feasible, and control of type I error is less relevant. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
32. Incorporating historical information to improve dose optimization design with toxicity and efficacy endpoints: iBOIN‐ET.
- Author
-
Zhao, Yunqi, Liu, Rachael, and Takeda, Kentaro
- Subjects
- *
ERROR probability , *DRUG development , *CELLULAR therapy , *ANTINEOPLASTIC agents , *INFORMATION design - Abstract
In modern oncology drug development, adaptive designs have been proposed to identify the recommended phase 2 dose. The conventional dose finding designs focus on the identification of maximum tolerated dose (MTD). However, designs ignoring efficacy could put patients under risk by pushing to the MTD. Especially in immuno‐oncology and cell therapy, the complex dose‐toxicity and dose‐efficacy relationships make such MTD driven designs more questionable. Additionally, it is not uncommon to have data available from other studies that target on similar mechanism of action and patient population. Due to the high variability from phase I trial, it is beneficial to borrow historical study information into the design when available. This will help to increase the model efficiency and accuracy and provide dose specific recommendation rules to avoid toxic dose level and increase the chance of patient allocation at potential efficacious dose levels. In this paper, we propose iBOIN‐ET design that uses prior distribution extracted from historical studies to minimize the probability of decision error. The proposed design utilizes the concept of skeleton from both toxicity and efficacy data, coupled with prior effective sample size to control the amount of historical information to be incorporated. Extensive simulation studies across a variety of realistic settings are reported including a comparison of iBOIN‐ET design to other model based and assisted approaches. The proposed novel design demonstrates the superior performances in percentage of selecting the correct optimal dose (OD), average number of patients allocated to the correct OD, and overdosing control during dose escalation process. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
33. An Augmented Reality Book for Training a Child with Austism Spectrum Disorders: Towards an Inclusive Primary School Education.
- Author
-
Tokarskaya, Ludmila, Bystrova, Tatiana, and Aguilera, Guillermo Rodrigez
- Subjects
AUGMENTED reality ,AUTISM spectrum disorders in children ,PRIMARY schools ,INCLUSIVE education ,EDUCATIONAL technology - Abstract
The focal point of the paper is the draft results of a training book describing the topic "Space" and applications in augmented and virtual reality-based on this book. The paper also describes the test results of studying with the book obtained during an experiment in two groups of 30 students with autism spectrum disorders in Russia and Brazil. These two countries were selected as the most accessible, because the study was carried out without financial support from any foundation. And the authors of the article live in Russia and Brazil. The choice of subjects with ASD was made due to the fact that this work continues a series of studies devoted to this category of persons [Bystrova et al., 2016; Bystrova et al., 2017 etc.]. The studying with the book showed an increase in the efficiency of mastering the proposed topic, as well as motivation growth among students and a high level of interest among teachers using such technologies. We suppose the approach could be useful not only for children with ASD but for children with other disabilities, and without them. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
34. Improving the statistical power of economic experiments using adaptive designs.
- Author
-
Jobjörnsson, Sebastian, Schaak, Henning, Musshoff, Oliver, and Friede, Tim
- Subjects
STATISTICAL power analysis ,FALSE positive error ,ERROR probability ,EXPERIMENTAL design - Abstract
An important issue for many economic experiments is how the experimenter can ensure sufficient power in order to reject one or more hypotheses. The paper illustrates how methods for testing multiple hypotheses simultaneously in adaptive, two-stage designs can be used to improve the power of economic experiments. We provide a concise overview of the relevant theory and illustrate the method in three different applications. These include a simulation study of a hypothetical experimental design, as well as illustrations using two data sets from previous experiments. The simulation results highlight the potential for sample size reductions, maintaining the power to reject at least one hypothesis while ensuring strong control of the overall Type I error probability. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
35. Sample size re‐estimation in Phase 2 dose‐finding: Conditional power versus Bayesian predictive power.
- Author
-
Liu, Qingyang, Hu, Guanyu, Ye, Binqi, Wang, Susan, and Wu, Yaoshi
- Subjects
- *
SAMPLE size (Statistics) , *FALSE positive error , *CLINICAL trials - Abstract
Unblinded sample size re‐estimation (SSR) is often planned in a clinical trial when there is large uncertainty about the true treatment effect. For Proof‐of Concept (PoC) in a Phase II dose finding study, contrast test can be adopted to leverage information from all treatment groups. In this article, we propose two‐stage SSR designs using frequentist conditional power (CP) and Bayesian predictive power (PP) for both single and multiple contrast tests. The Bayesian SSR can be implemented under a wide range of prior settings to incorporate different prior knowledge. Taking the adaptivity into account, all type I errors of final analysis in this paper are rigorously protected. Simulation studies are carried out to demonstrate the advantages of unblinded SSR in multi‐arm trials. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
36. Optimal unplanned design modification in adaptive two‐stage trials.
- Author
-
Pilz, Maximilian, Herrmann, Carolin, Rauch, Geraldine, and Kieser, Meinhard
- Subjects
- *
FALSE positive error , *ERROR rates - Abstract
Adaptive planning of clinical trials allows modifying the entire trial design at any time point mid‐course. In this paper, we consider the case when a trial‐external update of the planning assumptions during the ongoing trial makes an unforeseen design adaptation necessary. We take up the idea to construct adaptive designs with defined features by solving an optimization problem and apply it to the situation of unplanned design reassessment. By using the conditional error principle, we present an approach on how to optimally modify the trial design at an unplanned interim analysis while at the same time strictly protecting the type I error rate. This linking of optimal design planning and the conditional error principle allows sound reactions to unforeseen events that make a design reassessment necessary. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
37. Adaptive treatment allocation and selection in multi-arm clinical trials: a Bayesian perspective
- Author
-
Elja Arjas and Dario Gasbarra
- Subjects
Superiority trial ,Phase II ,Phase III ,Adaptive design ,Likelihood principle ,Posterior inference ,Medicine (General) ,R5-920 - Abstract
Abstract Background Adaptive designs offer added flexibility in the execution of clinical trials, including the possibilities of allocating more patients to the treatments that turned out more successful, and early stopping due to either declared success or futility. Commonly applied adaptive designs, such as group sequential methods, are based on the frequentist paradigm and on ideas from statistical significance testing. Interim checks during the trial will have the effect of inflating the Type 1 error rate, or, if this rate is controlled and kept fixed, lowering the power. Results The purpose of the paper is to demonstrate the usefulness of the Bayesian approach in the design and in the actual running of randomized clinical trials during phase II and III. This approach is based on comparing the performance of the different treatment arms in terms of the respective joint posterior probabilities evaluated sequentially from the accruing outcome data, and then taking a control action if such posterior probabilities fall below a pre-specified critical threshold value. Two types of actions are considered: treatment allocation, putting on hold at least temporarily further accrual of patients to a treatment arm, and treatment selection, removing an arm from the trial permanently. The main development in the paper is in terms of binary outcomes, but extensions for handling time-to-event data, including data from vaccine trials, are also discussed. The performance of the proposed methodology is tested in extensive simulation experiments, with numerical results and graphical illustrations documented in a Supplement to the main text. As a companion to this paper, an implementation of the methods is provided in the form of a freely available R package ’barts’. Conclusion The proposed methods for trial design provide an attractive alternative to their frequentist counterparts.
- Published
- 2022
- Full Text
- View/download PDF
38. A dose-finding design for phase I clinical trials based on Bayesian stochastic approximation.
- Author
-
Xu, Jin, Zhang, Dapeng, and Mu, Rongji
- Subjects
- *
EXPERIMENTAL design , *COMPUTER simulation , *RESEARCH , *DRUG dosage , *CLINICAL trials , *RESEARCH methodology , *EVALUATION research , *COMPARATIVE studies , *DOSE-effect relationship in pharmacology , *TUMORS , *PROBABILITY theory , *DRUG toxicity - Abstract
Background: Current dose-finding designs for phase I clinical trials can correctly select the MTD in a range of 30-80% depending on various conditions based on a sample of 30 subjects. However, there is still an unmet need for efficiency and cost saving.Methods: We propose a novel dose-finding design based on Bayesian stochastic approximation. The design features utilization of dose level information through local adaptive modelling and free assumption of toxicity probabilities and hyper-parameters. It allows a flexible target toxicity rate and varying cohort size. And we extend it to accommodate historical information via prior effective sample size. We compare the proposed design to some commonly used methods in terms of accuracy and safety by simulation.Results: On average, our design can improve the percentage of correct selection to about 60% when the MTD resides at a early or middle position in the search domain and perform comparably to other competitive methods otherwise. A free online software package is provided to facilitate the application, where a simple decision tree for the design can be pre-printed beforehand.Conclusion: The paper proposes a novel dose-finding design for phase I clinical trials. Applying the design to future cancer trials can greatly improve the efficiency, consequently save cost and shorten the development period. [ABSTRACT FROM AUTHOR]- Published
- 2022
- Full Text
- View/download PDF
39. SCI: A Bayesian adaptive phase I/II dose‐finding design accounting for semi‐competing risks outcomes for immunotherapy trials.
- Author
-
Zhang, Yifei, Guo, Beibei, Cao, Sha, Zhang, Chi, and Zang, Yong
- Subjects
- *
IMMUNOTHERAPY , *PROGRESSION-free survival , *TREATMENT effectiveness , *DATA augmentation , *DISEASE progression - Abstract
An immunotherapy trial often uses the phase I/II design to identify the optimal biological dose, which monitors the efficacy and toxicity outcomes simultaneously in a single trial. The progression‐free survival rate is often used as the efficacy outcome in phase I/II immunotherapy trials. As a result, patients developing disease progression in phase I/II immunotherapy trials are generally seriously ill and are often treated off the trial for ethical consideration. Consequently, the happening of disease progression will terminate the toxicity event but not vice versa, so the issue of the semi‐competing risks arises. Moreover, this issue can become more intractable with the late‐onset outcomes, which happens when a relatively long follow‐up time is required to ascertain progression‐free survival. This paper proposes a novel Bayesian adaptive phase I/II design accounting for semi‐competing risks outcomes for immunotherapy trials, referred to as the dose‐finding design accounting for semi‐competing risks outcomes for immunotherapy trials (SCI) design. To tackle the issue of the semi‐competing risks in the presence of late‐onset outcomes, we re‐construct the likelihood function based on each patient's actual follow‐up time and develop a data augmentation method to efficiently draw posterior samples from a series of Beta‐binomial distributions. We propose a concise curve‐free dose‐finding algorithm to adaptively identify the optimal biological dose using accumulated data without making any parametric dose–response assumptions. Numerical studies show that the proposed SCI design yields good operating characteristics in dose selection, patient allocation, and trial duration. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
40. Optimization of adaptive designs with respect to a performance score.
- Author
-
Herrmann, Carolin, Kieser, Meinhard, Rauch, Geraldine, and Pilz, Maximilian
- Abstract
Adaptive designs are an increasingly popular method for the adaptation of design aspects in clinical trials, such as the sample size. Scoring different adaptive designs helps to make an appropriate choice among the numerous existing adaptive design methods. Several scores have been proposed to evaluate adaptive designs. Moreover, it is possible to determine optimal two‐stage adaptive designs with respect to a customized objective score by solving a constrained optimization problem. In this paper, we use the conditional performance score by Herrmann et al. (2020) as the optimization criterion to derive optimal adaptive two‐stage designs. We investigate variations of the original performance score, for example, by assigning different weights to the score components and by incorporating prior assumptions on the effect size. We further investigate a setting where the optimization framework is extended by a global power constraint, and additional optimization of the critical value function next to the stage‐two sample size is performed. Those evaluations with respect to the sample size curves and the resulting design's performance can contribute to facilitate the score's usage in practice. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
41. Revitalizing Traditional Villages Through Adaptive Design Strategies: Selected Case Studies of Chinese and French Traditional Villages
- Author
-
Zhou, Mo, Bonenberg, Wojciech, Wei, Xia, Qi, Ling, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Charytonowicz, Jerzy, editor, Maciejko, Alicja, editor, and Falcão, Christianne S., editor
- Published
- 2021
- Full Text
- View/download PDF
42. Adaptive Design for Children with Disabilities and the Educational Environment
- Author
-
Bystrova, Tatiana Yu., Tokarskaja, Liydmila V., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Bylieva, Daria, editor, Nordmann, Alfred, editor, Shipunova, Olga, editor, and Volkova, Violetta, editor
- Published
- 2021
- Full Text
- View/download PDF
43. Bayesian design methods for improving the effectiveness of ecosystem monitoring
- Author
-
Thilan, A. W. L. Pubudu, Peterson, Erin, Menéndez, Patricia, Caley, Julian, Drovandi, Christopher, Mellin, Camille, and McGree, James
- Published
- 2024
- Full Text
- View/download PDF
44. A data-driven adaptive design for achieving sustainable product.
- Author
-
Sun, Hui, Guo, Wei, Wang, Lei, and Lin, Mao
- Abstract
Compared with the traditional sustainable design that optimizes physical materials and components to extend product life-cycle time period, adaptive design aims at creating a dynamic design process to satisfy changes of product requirements in life-cycle time periods. In this paper, we discuss the key features of sustainable adaptive design to optimize the product design process. An adaptive design method is proposed to analyze the ever-changing requirements to reduce resource consumption and waste. Accordingly, two appropriate mechanisms are proposed to achieve product improvement in sustainability, (1) an approach of product requirements classification is used to dynamically identify and classify customer perceptions, and (2) a mapping between functions and requirements is introduced to represent the ability of existing design to adapt to the changing requirements. A case study of vehicle is conducted to show the effectiveness of the introduced method. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
45. Fault Analysis and Adaptive Design of Wind Turbine Lubrication System.
- Author
-
Haitang Cen, Tianfang Zhang, Wenliang Tian, and Yongdong Zheng
- Subjects
WIND turbines ,TURBINE lubrication ,FAULT trees (Reliability engineering) ,LUBRICATION systems ,FAILURE analysis - Abstract
Wind turbines work in harsh environments and have changeable loads. The reliability and service life of the wind turbine gearbox has become an important factor for maintaining its safe, stable, and reliable economic operation. The production practice shows that the failure of the wind turbine gearbox is closely related to the structure and performance of the lubrication system. In this paper, the fault tree of the wind turbine gearbox lubrication system is established. It is pointed out that the temperature, state, and lubrication intensity of the lubricating oil are not well adapted to the working condition of the gear box, which leads to frequent gearbox breakdowns until its failure. The heat dissipation power consumption of the lubrication system is determined by calculating the heat balance of the lubrication system. By introducing the AI control method, the adaptive lubrication system framework of the wind turbine gear box is constructed from the aspects of oil temperature, oil pressure, oil level, and oil quality, which can automatically adjust the lubrication intensity according to the working condition of the wind turbine, so as to improve the lubrication effect of the wind turbine gear box. The research work in this paper plays an important role in optimizing the performance of the lubrication system, reducing the failure of the lubrication system, and reducing the operation and maintenance cost of wind turbines. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
46. THE BIOPHYSICAL STRUSTURE OF ROADSIDE GREEN SPACES: THE IMPACT ON ECOLOGICAL CONDITIONS IN THE URBAN ENVIRONMENT.
- Author
-
Stojanovic, Nadezda, Vasiljevic, Nevena, Veselinovic, Milorad, Radie, Boris, Skocajic, Dejan, Galecic, Nevenka, Tesic, Mirjana, and Lisica, Aleksandar
- Abstract
Automobile traffic, which is considered one of the permanent major sources of various types of pollution in the urban environment, gives a special contribution to urban ecological problems. The establishment of roadside green spaces can greatly reduce the negative ecological consequences that urban traffic produces. In the process of planning and management of urban green spaces, information on the types of biophysical structures of the green spaces and their characteristics in relation to the degree of modification of unfavorable ecological factors are of great importance. This paper investigates the impact of the type of biophysical structure of green roadside spaces in the area of Belgrade on the ecological factors with the highest impact on people's quality of life in the city, including air temperature, air humidity, the urban noise level and wind speed. The results and conclusions of this paper are part of a research of the adaptive design, which provides guidelines for the planning of urban landscape development in the conditions of unpredictable climate change. [ABSTRACT FROM AUTHOR]
- Published
- 2018
47. Distribution theory following blinded and unblinded sample size re-estimation under parametric models.
- Author
-
Tarima, Sergey and Flournoy, Nancy
- Subjects
- *
SAMPLE size (Statistics) , *MONTE Carlo method , *PARAMETRIC modeling , *ASYMPTOTIC distribution , *MAXIMUM likelihood statistics - Abstract
Asymptotic distribution theory for maximum likelihood estimators under fixed alternative hypotheses is reported in the literature even though the power of any realistic test converges to one under fixed alternatives. Under fixed alternatives, authors have established that nuisance parameter estimates are inconsistent when sample size re-estimation (SSR) follows blinded randomization. These results have helped to inhibit the use of SSR. In this paper, we argue for local alternatives to be used instead of fixed alternatives. We treat unavailable treatment assignments in blinded experiments as missing data and rely on single imputation from marginal distributions to fill in for missing data. With local alternatives, it is sufficient to proceed only with the first step of the EM algorithm mimicking imputation under the null hypothesis. Then, we show that blinded and unblinded estimates of the nuisance parameter σ θ 2 are consistent, and re-estimated sample sizes converge to their locally asymptotically optimal values. This theoretical finding is confirmed through Monte-Carlo simulation studies. Practical utility is illustrated through a multiple logistic regression example. We conclude that, for hypothesis testing with a predetermined minimally clinically relevant local effect size, both blinded and unblinded SSR procedures lead to similar sample sizes and power. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
48. A note on the shape of sample size functions of optimal adaptive two-stage designs.
- Author
-
Pilz, Maximilian, Kilian, Samuel, and Kieser, Meinhard
- Subjects
- *
SAMPLE size (Statistics) , *FALSE positive error , *EXPERIMENTAL design - Abstract
Adaptive two-stage designs for clinical trials are well understood from a statistical perspective. However, there is still few research on how the stage-two sample size looks like when it is regarded as a function of the first-stage test statistic. In this paper, a formal proof on the concavity of the sample size function is provided if the design's second stage is optimized such that it minimizes the expected sample size under the alternative under constraints on maximal type I error rate and minimal power. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
49. The Shapes of Adaptive Ground Design: A New Taxonomy Between Spatial Quality and Ecological Performance
- Author
-
Porfiri, Simone, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Marucci, Alessandro, editor, Zullo, Francesco, editor, Fiorini, Lorena, editor, and Saganeiti, Lucia, editor
- Published
- 2024
- Full Text
- View/download PDF
50. Adaptation and Enhancement of Small Historic Centres: A Multidimensional Mapping Model
- Author
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Scolaro, Antonello Monsù, Cappello, Cheren, Hensel, Michael U., Series Editor, Binder, Claudia R., Series Editor, Sunguroğlu Hensel, Defne, Series Editor, Battisti, Alessandra, editor, and Baiani, Serena, editor
- Published
- 2024
- Full Text
- View/download PDF
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