Statistical Methods and Issues for Implementing Adaptive Phase I Trials

实施适应性 I 期试验的统计方法和问题

• 批准号: 8403988
• 负责人: Thomas M Braun
• 金额: $ 25.65万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-02-08 至 2014-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8403988
• 关键词: Accounting; Address; Clinical; Clinical Research; Clinical Trials; Clinical Trials Design; Computer software; Data; Dose; Dose-Limiting; Drug Formulations; Enrollment; Event; Future; Goals; Grant; Health; Heterogeneity; Housing; Journals; Literature; Logistic Regressions; Malignant Neoplasms; Methodology; Methods; Mission; Modeling; New Agents; Patients; Pattern; Phase; Phase I Clinical Trials; Process; Publishing; Recording of previous events; Research; Research Personnel; Statistical Methods; Tail; Time; Toxic effect; Uncertainty; United States National Institutes of Health; Work; cancer therapy; clinical practice; computer program; design; drug discovery; experience; improved; insight; meetings; novel; oncology; phase 1 study; programs; skills; software development; success; user friendly software

PROJECT SUMMARY/ABSTRACT The six aims in this proposal are motivated by important and relevant issues in the design of adaptive Phase I trials where focused research is needed. The investigators in this proposal bring a uniquely strong combination of statistical methodology, applied clinical trial experience, and computer programming skills to impact the future of oncology clinical trials. Successful completion of the proposed research will substantially augment existing Phase I methodology and provide new insight into novel adaptive Phase I trials approaches that will be important to both methodologic and applied statisticians. Most important, our findings will be relevant to the NIH mission of making important discoveries that improve peoples health and save lives. Aim 1 concerns fundamental issues in model construction for the Continual Reassessment Method (CRM) that are ignored in published literature but have a direct impact on the success of the trial. Aims 2, 3, and 4 share an underlying theme of improving the efficiency of Phase I trials by incorporating additional patient information into the dose-finding process. This information relates to both the prior history of the patient as well as the treatment of their cancer during the trial, data that are routinely collected for general clinical purposes that could impart additional information about the toxicity profile of an agent, but that are often ignored in Phase I studies. Aim 2 proposes four modeling approaches to incorporate patient heterogeneity in adaptive designs, Aim 3 investigates two approaches for incorporating non-dose-limiting toxicities into the estimation of the MTD, while Aim 4 examines approaches to incorporate non-monotonic efficacy patterns. Aim 5 proposes methods for inference about the DLT rate for each dose after a Phase I trial has completed enrollment, information that is rarely considered once a trial is completed and the recommended MTD is found, but provides information for the uncertainty surrounding the selected MTD and its neighboring doses. The lack of freely available and modifiable software remains the major barrier to the implementation of adaptive Phase I trial designs into routine clinical practice. Therefore, this proposal contains a final, sixth aim, spanning all four years of the proposal, focused solely on the programming, in both SAS and R, of all methods described in this proposal, as well as existing methods that have yet to be housed in a single software package. Through this final aim, we will provide a suite of software packages that meet the general needs of researchers working on Phase I design methodology and the specific day-to-day needs of those who administer actual Phase I trials, with the eventual goal of making adaptive Phase I trial designs commonplace in oncology trials published in the coming decade.

项目总结/文摘

项目成果

A Phase I/II trial design when response is unobserved in subjects with dose-limiting toxicity.

当剂量限制性毒性受试者中未观察到反应时的 I/II 期试验设计。

• DOI: 10.1177/0962280212464541
• 发表时间: 2016
• 期刊: Statistical methods in medical research
• 影响因子: 2.3
• 作者: Braun,ThomasM;Kang,Shan;Taylor,JeremyMg
• 通讯作者: Taylor,JeremyMg

A Phase I Bayesian Adaptive Design to Simultaneously Optimize Dose and Schedule Assignments Both Between and Within Patients.

• DOI: 10.1080/01621459.2013.806927
• 发表时间: 2013-01-01
• 期刊: Journal of the American Statistical Association
• 影响因子: 3.7
• 作者: Zhang J;Braun TM
• 通讯作者: Braun TM

Multivariate Markov models for the conditional probability of toxicity in phase II trials.

II 期试验中毒性条件概率的多变量马尔可夫模型。

• DOI: 10.1002/bimj.201400047
• 发表时间: 2016
• 期刊: Biometrical journal. Biometrische Zeitschrift
• 作者: Fernandes,LauraL;Murray,Susan;Taylor,JeremyMG
• 通讯作者: Taylor,JeremyMG

Adaptive prior variance calibration in the Bayesian continual reassessment method.

贝叶斯连续重评估方法中的自适应先验方差校准。

• DOI: 10.1002/sim.5621
• 发表时间: 2013
• 期刊: Statistics in medicine
• 影响因子: 2
• 作者: Zhang,Jin;Braun,ThomasM;Taylor,JeremyMG
• 通讯作者: Taylor,JeremyMG