CLINICAL TRIAL METHODOLOGY IN PSYCHOPHARMACOLOGY

精神药理学临床试验方法

• 批准号: 2245627
• 负责人: EUGENE M LASKA
• 金额: $ 13.34万
• 依托单位: NATHAN S. KLINE INSTITUTE FOR PSYCH RES
• 依托单位国家: 美国
• 财政年份: 1988
• 资助国家: 美国
• 起止时间: 1988-08-01 至 1999-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2245627
• 关键词: bioassay; clinical trials; combination chemotherapy; data collection methodology /evaluation; drug interactions; drug screening /evaluation; mathematical model; mental disorder chemotherapy; pharmacokinetics; statistics /biometry

This project continues the development of clinical trial design and statistical analysis methodology for psychopharmacological and other treatments used in the care of the mentally ill. The specific aims are to: (1) develop design and statistical analysis strategies for dose-response and bioassay studies to characterize a test treatment relative to a standard treatment. Based on models that include patients who are unresponsive at any dose, who respond at any dose or who respond depending on whether their dose is adequate, we will develop methods to analyze "doctor's choice" study designs. Recursive partitioning approaches for identifying variables that share a common relative potency will be studied. (2) develop clinical trial designs and methods of analysis resulting in clinically informative measures. We will develop an inference framework for optimal scaling techniques for the general linear model and for two-way tables when the data arise from ordered categories. We will develop efficient designs and nonparametric and parametric models and estimators of parameters that are clinically informative. (3) develop simple designs and statistical methods for testing whether each component of a combination therapy contributes to its effect and whether the combination is antagonistic, additive or synergistic. In the multivariate combination problem, we will study new hypothesis formulations that further characterize the requirement that each component "contributes" to the combination's effects. Alternatives that are more demanding than admissible but less demanding than uniformly best will be developed. We will study the problem of finding a simple experimental design to test for dose additivity, synergy or antagonism when there are two or more doses of the combination, single and multiple endpoints and combinations with two or more drugs. (4) develop robust and optimal crossover and response adaptive clinical trial designs for estimation of treatment and carryover effects. We shall seek optimal crossover designs for an arbitrary number of treatments and periods when there are carryover effects. We will develop response adaptive designs to allocate treatments to patients so as to increase power for hypotheses testing situations involving a min statistic and in the optimal crossover design problem.

该项目继续开发临床试验设计， 精神药理学和其他方面统计分析方法 精神病患者的治疗方法。 具体目标是： (1)制定剂量反应的设计和统计分析策略 和生物测定研究，以表征测试处理相对于 标准治疗。 基于包括患者的模型， 在任何剂量下无反应，在任何剂量下有反应或根据 关于他们的剂量是否足够，我们将开发方法来分析 “医生的选择”研究设计。 递归分区方法 将研究确定具有共同相对效力的变量。 (2)开发临床试验设计和分析方法， 临床信息测量。 我们将建立一个推理框架 对于一般线性模型和双向模型的最佳缩放技术， 当数据来自有序类别时，请使用表格。 我们将开发 有效设计、非参数和参数模型以及 具有临床信息的参数。 (3)开发简单的设计和统计方法来测试每个 联合治疗的一个组成部分有助于其效果， 该组合是拮抗的、相加的或协同的。 在 多变量组合问题，我们将研究新的假设公式 进一步描述了每个组件“贡献” 结合的效果。 替代品的要求比 可接受的，但要求低于均匀最佳将开发。 我们 将研究如何找到一个简单的实验设计来测试 当存在两个或更多个剂量的 组合、单个和多个端点以及具有两个或多个端点的组合， 更多的毒品。 (4)开发稳健和最佳的交叉和响应自适应临床 用于估计治疗和残留效应的试验设计。 我们将 为任意数量的治疗寻求最佳交叉设计， 存在结转效应的时期。 我们将制定应对措施 适应性设计，将治疗分配给患者，以增加功率 对于涉及最小统计量的假设检验情况， 最优交叉设计问题