Statistical Methods and Software for More Efficient, Ethical, and Affordable Clin

统计方法和软件使临床更加高效、合乎道德且经济实惠

• 批准号: 8677795
• 负责人: Bradley P Carlin
• 金额: $ 30.92万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8677795
• 关键词: Address; Advisory Committees; Alcohols; Area; Bayesian Method; Bayesian Modeling; Behavior; Berry; Biometry; Books; Cancer Center; Characteristics; Clinic; Clinical; Clinical Investigator; Clinical Trials; Clinical Trials Design; Collection; Computer software; Conflict (Psychology); Control Groups; Cost Analysis; Data; Data Set; Data Sources; Databases; Development; Devices; Doctor of Medicine; Drops; Enrollment; Ethics; Event; Expert Opinion; Florida; Goals; Inferior; Institution; Institutional Review Boards; Intervention Studies; Investigational Drugs; Knowledge; Language; Lead; Letters; Malignant Neoplasms; Methodology; Methods; Minnesota; Modeling; Monitor; National Cancer Institute; Nature; New Device Approvals; New Drug Approvals; Patients; Pharmaceutical Preparations; Phase; Phase I/II Trial; Process; Protocols documentation; Public Health; Publishing; Radiologic Health; Randomized; Reporting; Research Personnel; Review Committee; Sample Size; Software Tools; Source; Statistical Methods; Statistical Models; Text; Time; Universities; Ursidae Family; Work; base; computer code; cost; design; hazard; improved; member; novel; simulation; software repository; theories; user friendly software; user-friendly; web page; web site

DESCRIPTION (provided by applicant): Clinical trials are becoming increasingly expensive, and patients are more and more reluctant to enroll and to persist with the protocol, further increasing costs. We propose to develop Bayesian statistical methods and software for more efficient, ethical, and affordable clinical trials. These methods incorporate all sources of knowledge (structural constraints, expert opinion, and both historical and experimental data), thus reducing sample size and typically leading to increases in statistical power and reductions in cost and ethical hazard, since fewer patients need be exposed to the inferior treatment. The methods are also better able to adapt to unanticipated changes that inevitably arise as the trial progresses. In Aim 1 we will develop novel methods to exploit available historical data. In Aim 2 we look at the more general problem of combining inference across related subpopulations, when the subpopulations are not exchangeable. Here our approach is based on random clustering of subpopulations. Finally, Aim 3 is concerned with the development of user-friendly computer code that can be publicly distributed. The end result will be clinical trials that come to conclusions more quickly with fewer patients randomized to inferior treatments. Our methods and software should have immediate impact on practice not only for early phase studies, but for large confirmatory trials as well. In the longer term, improvements in trial compliance and accrual should also obtain.

描述（由申请人提供）：临床试验变得越来越昂贵，患者越来越不愿意参加并坚持该方案，进一步增加了成本。我们建议开发贝叶斯统计方法和软件，以实现更高效、更符合伦理和更经济的临床试验。这些方法结合了所有的知识来源（结构约束、专家意见以及历史和实验数据），从而减少了样本量，并且通常导致统计功效的增加以及成本和伦理风险的降低，因为需要暴露于较差治疗的患者较少。这些方法还能够更好地适应随着试验进展不可避免地出现的意外变化。在目标1中，我们将开发新的方法来利用现有的历史数据。在目标2中，我们研究了当子群体不可交换时，在相关子群体之间组合推理的更一般问题。在这里，我们的方法是基于随机聚类的亚群。最后，目标3涉及开发可公开分发的方便用户的计算机代码。最终的结果将是临床试验更快地得出结论，更少的患者随机接受较差的治疗。我们的方法和软件不仅对早期研究，而且对大型验证性试验都有直接的影响。从长远来看，还应改善试验依从性和应计费用。

项目成果

Combining Non-randomized and Randomized Data in Clinical Trials Using Commensurate Priors.

使用相应的先验在临床试验中结合非随机和随机数据。

• DOI: 10.1007/s10742-016-0155-7
• 发表时间: 2016
• 期刊: Health services & outcomes research methodology
• 影响因子: 1.5
• 作者: Zhao,Hong;Hobbs,BrianP;Ma,Haijun;Jiang,Qi;Carlin,BradleyP
• 通讯作者: Carlin,BradleyP

Pharmacokinetic/pharmacodynamic data extrapolation models for improved pediatric efficacy and toxicity estimation, with application to secondary hyperparathyroidism.

药代动力学/药效学数据外推模型，用于改善儿科疗效和毒性估计，并应用于继发性甲状旁腺功能亢进症。

• DOI: 10.1002/pst.2043
• 发表时间: 2020
• 期刊: Pharmaceutical statistics
• 影响因子: 1.5
• 作者: Basu,Cynthia;Ma,Xiaoye;Mo,May;Xia,HongAmy;Brundage,Richard;Al-Kofahi,Mahmoud;Carlin,BradleyP
• 通讯作者: Carlin,BradleyP

Bayesian adaptive design for device surveillance.

• DOI: 10.1177/1740774512464725
• 发表时间: 2013-02
• 期刊: Clinical trials (London, England)
• 作者: Murray TA;Carlin BP;Lystig TC
• 通讯作者: Lystig TC

A hierarchical Bayesian approach for combining pharmacokinetic/pharmacodynamic modeling and Phase IIa trial design in orphan drugs: Treating adrenoleukodystrophy with Lorenzo's oil.

一种将孤儿药物的药代动力学/药效学模型与 IIa 期试验设计相结合的分层贝叶斯方法：用洛伦佐油治疗肾上腺脑白质营养不良。

• DOI: 10.1080/10543406.2016.1226326
• 发表时间: 2016
• 期刊: Journal of biopharmaceutical statistics
• 影响因子: 1.1
• 作者: Basu,Cynthia;Ahmed,MariamA;Kartha,ReenaV;Brundage,RichardC;Raymond,GeraldV;Cloyd,JamesC;Carlin,BradleyP
• 通讯作者: Carlin,BradleyP

Multiplicity-adjusted semiparametric benefiting subgroup identification in clinical trials.

• DOI: 10.1177/1740774517729167
• 发表时间: 2018-03
• 期刊: Clinical trials (London, England)
• 作者: Schnell PM;Müller P;Tang Q;Carlin BP
• 通讯作者: Carlin BP