標題: Titlebook: Bayesian Adaptive Design for Immunotherapy and Targeted Therapy; Haitao Pan,Ying Yuan Book 2023 Springer Nature Singapore Pte Ltd. 2023 Ad [打印本頁] 作者: IU421 時間: 2025-3-21 18:34
書目名稱Bayesian Adaptive Design for Immunotherapy and Targeted Therapy影響因子(影響力)
書目名稱Bayesian Adaptive Design for Immunotherapy and Targeted Therapy影響因子(影響力)學科排名
書目名稱Bayesian Adaptive Design for Immunotherapy and Targeted Therapy網絡公開度
書目名稱Bayesian Adaptive Design for Immunotherapy and Targeted Therapy網絡公開度學科排名
書目名稱Bayesian Adaptive Design for Immunotherapy and Targeted Therapy被引頻次
書目名稱Bayesian Adaptive Design for Immunotherapy and Targeted Therapy被引頻次學科排名
書目名稱Bayesian Adaptive Design for Immunotherapy and Targeted Therapy年度引用
書目名稱Bayesian Adaptive Design for Immunotherapy and Targeted Therapy年度引用學科排名
書目名稱Bayesian Adaptive Design for Immunotherapy and Targeted Therapy讀者反饋
書目名稱Bayesian Adaptive Design for Immunotherapy and Targeted Therapy讀者反饋學科排名
作者: Meander 時間: 2025-3-21 23:31
Bayesian Adaptive Design for Immunotherapy and Targeted Therapy978-981-19-8176-0作者: 考博 時間: 2025-3-22 03:39
https://doi.org/10.1007/978-981-19-8176-0Adaptive clinical trial design; Delayed outcomes; Late-onset outcomes; Markov Chain Monte Carlo (MCMC) 作者: Acetaldehyde 時間: 2025-3-22 06:03 作者: Connotation 時間: 2025-3-22 09:09 作者: forecast 時間: 2025-3-22 12:53 作者: Incorruptible 時間: 2025-3-22 17:38 作者: AGATE 時間: 2025-3-23 01:07
Human Autonomy in Cross-Cultural Contextal., 2014), a Bayesian phase I/II design for immunotherapy (Liu et al., 2018), and an isotonic design (Zang et al., 2014). These designs assume a dose-toxicity and dose-efficacy model, and continuously update the estimate of the model in a way similar to the continual reassessment method (CRM). The 作者: 土坯 時間: 2025-3-23 02:23
https://doi.org/10.1007/978-3-031-05871-4e challenging to implement in practice. This chapter introduces two model-assisted phase I/II designs, BOIN12 and U-BOIN, to find the optimal biological dose (OBD). These two designs simultaneously consider toxicity and efficacy, and use the utility to quantify the risk-benefit tradeoff. Based on th作者: sed-rate 時間: 2025-3-23 08:54
https://doi.org/10.1007/978-981-15-2109-6III trials, using small sample sizes. This chapter first presents Simon’s two-stage design; and then introduces several novel Bayesian designs, including posterior probability (PrP) and predictive probability (PreP) approaches, and Bayesian optimal Phase II design (BOP2) and its extensions. Bayesian作者: AWE 時間: 2025-3-23 12:32 作者: 驚呼 時間: 2025-3-23 15:14
https://doi.org/10.1007/978-3-319-11839-0ch to evaluating treatment effects of targeted therapies and immunotherapies. Under the basket trial, patients with the same genetic or molecular aberrations, regardless of their cancer types, are enrolled in the trial for evaluating the effect of a targeted agent. The basket trial allows for the in作者: Acumen 時間: 2025-3-23 20:32
https://doi.org/10.1007/978-3-319-11839-0dous advances in biomedical research, a number of candidate drugs are produced and discovered at an unprecedented speed. This makes the traditional one-treatment-at-a-time phase II trial paradigm cumbersome and grossly inefficient. Platform trials, also known as multi-arm multi-stage trials, provide作者: 安撫 時間: 2025-3-23 22:42 作者: 環(huán)形 時間: 2025-3-24 04:45
http://image.papertrans.cn/b/image/181820.jpg作者: modish 時間: 2025-3-24 06:40 作者: 600 時間: 2025-3-24 10:42
Introduction to?Phase I Dose-Finding Clinical Trialsnvestigated in subsequent phases of development. This chapter review several novel phase I designs for oncology, including the continual reassessment method (CRM), modified toxicity probability interval design (mTPI), Keyboard design, and Bayesian optimal interval design (BOIN). Characteristics of t作者: Gyrate 時間: 2025-3-24 18:48
Phase I Designs for?Late-Onset Toxicityexisting phase I designs, which require that toxicity can be observed quickly to inform the dose assignment for the next new cohort of patients. This chapter introduces three model-based designs, including the time-to-event CRM (TITE-CRM), fractional CRM (fCRM), data augmentation CRM (DA-CRM), and a作者: Decibel 時間: 2025-3-24 19:36 作者: 賞錢 時間: 2025-3-25 01:45
Model-Based Designs for?Identification of?Optimal Biological Doseal., 2014), a Bayesian phase I/II design for immunotherapy (Liu et al., 2018), and an isotonic design (Zang et al., 2014). These designs assume a dose-toxicity and dose-efficacy model, and continuously update the estimate of the model in a way similar to the continual reassessment method (CRM). The 作者: Iniquitous 時間: 2025-3-25 04:45 作者: Indent 時間: 2025-3-25 09:08 作者: Mobile 時間: 2025-3-25 14:51 作者: 違反 時間: 2025-3-25 16:36 作者: AORTA 時間: 2025-3-25 21:39 作者: Iniquitous 時間: 2025-3-26 03:43 作者: 親愛 時間: 2025-3-26 04:33
Randomized Phase II Designs efficiency to handle the complexity of immunotherapies and targeted therapies that may involve binary, survival, ordinal, co-primary and multiple endpoints. A two-stage screened selection design (SSD) for randomized trials but without the control treatment is also introduced. Software to implement these designs are described.作者: 妨礙議事 時間: 2025-3-26 10:32
Introduction to?Basket Trialscorporation of precision medicine into clinical trials. This chapter introduces several frequentist and Bayesian designs for basket trials, with a special focus on borrowing information across cancer types using Bayesian hierarchical model approaches. Software for some designs are described.作者: mortgage 時間: 2025-3-26 16:24
lation study, proof-of-concept trials, and confirmatory studies with registrational. The book includes real-life examples and software to facilitate practitioners to learn and use the designs in practice..978-981-19-8467-9978-981-19-8176-0作者: 魯莽 時間: 2025-3-26 18:33
ive designs, such as model-assisted designs.Including many r.This book provides a comprehensive review of novel adaptive trial designs for targeted therapies and immunotherapies. This book covers a wide range of novel statistical designs for various clinical settings, including early phase dose-esca作者: 值得 時間: 2025-3-26 23:53
https://doi.org/10.1007/978-90-481-9667-8method (CRM), modified toxicity probability interval design (mTPI), Keyboard design, and Bayesian optimal interval design (BOIN). Characteristics of these designs are explained and contrasted. Unique challenges of using phase I trials for immunotherapies and targeted therapies are described.作者: 尾巴 時間: 2025-3-27 03:07 作者: Confirm 時間: 2025-3-27 07:40 作者: Scintillations 時間: 2025-3-27 10:28 作者: FID 時間: 2025-3-27 16:45 作者: 嫌惡 時間: 2025-3-27 20:43
Phase I Designs for?Late-Onset Toxicitychapter introduces three model-based designs, including the time-to-event CRM (TITE-CRM), fractional CRM (fCRM), data augmentation CRM (DA-CRM), and a model-assisted design, i.e., time-to-event BOIN (TITE-BOIN), to deal with late-onset toxicity. Trial examples and software are provided to demonstrate the implementation of designs.作者: 表狀態(tài) 時間: 2025-3-27 22:09
Optimal Biological Dose and?Phase I/II Trials appropriate to identify the optimal biological dose (OBD) that optimizes the risk-benefit tradeoff of the treatment, rather than the maximum tolerated dose (MTD). This chapter reviews basic concepts of the OBD and the phase I/II design paradigm to find the OBD.作者: Hallmark 時間: 2025-3-28 05:17
Model-Based Designs for?Identification of?Optimal Biological Dose-toxicity and dose-efficacy model, and continuously update the estimate of the model in a way similar to the continual reassessment method (CRM). The model estimate is then used to guide dose escalation/de-escalation. Herein, the software of these designs is introduced.作者: BACLE 時間: 2025-3-28 09:34
https://doi.org/10.1007/978-3-031-05871-4 U-BOIN have the advantages of being simple to implement and meanwhile yielding competitive performances. Conducting the trial does not require complicated model estimation. The decision of dose transition can be easily made by looking up the pre-generated decision table. Examples and software are provided to illustrate BOIN12 and U-BOIN.作者: 強所 時間: 2025-3-28 10:35 作者: 人充滿活力 時間: 2025-3-28 17:33
Model-Assisted Designs for?Identifying the?Optimal Biological Dose U-BOIN have the advantages of being simple to implement and meanwhile yielding competitive performances. Conducting the trial does not require complicated model estimation. The decision of dose transition can be easily made by looking up the pre-generated decision table. Examples and software are provided to illustrate BOIN12 and U-BOIN.
