SOFTWARE FOR DESIGN OF CLINICAL TRIALS

临床试验设计软件

• 批准号: 2283894
• 负责人: Janet T. Wittes
• 金额: $ 25.66万
• 依托单位: STATISTICS COLLABORATIVE
• 依托单位国家: 美国
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-04-01 至 1996-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2283894
• 关键词: clinical trials; computer assisted medical decision making; computer human interaction; handbook; health science research analysis /evaluation; longitudinal human study; method development; statistics /biometry

Designing a randomized clinical trial (RCT) that incorporates flexible approaches to sample size calculation, data monitoring, early stopping, multiple endpoints, and changing sample size during the trial all while still preserving the stated a-level is computational difficult. Therefore, a computerized approach to the design of an RCT has important commercial application to pharmaceutical companies, both domestic and foreign, and other organizations that perform clinical trials. Phase I of this SBIR studied a new class of designs for an RCT. The new design designates a portion of the main clinical trial as an internal pilot (IP) study. The sample size is recalculated o the basis of data from the IP. Phase II will continue the work of Phase I in investigating the operating characteristics of IPs for the normal, the binomial, and the log-rank statistics. It will develop a computer program that implements IP studies incorporating the Lakatos method of sample size calculation, the Lan-DeMets a-spending approach to data monitoring, stochastic curtailing, and Bonferroni correction for multiple endpoints. The research component of Phase II will focus on statistical methods for combining the approaches while still maintaining control over alpha and power.

设计合并灵活的随机临床试验（RCT） 样本量计算，数据监视，早期停止的方法， 多个端点，并且在试用期间改变样本量 仍然保留说明A级的计算困难。 因此，用于设计RCT设计的计算机化方法很重要 用于国内和国内制药公司的商业应用 外国和其他进行临床试验的组织。 该SBIR的第一阶段研究了RCT的新设计。 新的 设计将主要临床试验的一部分指定为内部试验 飞行员（IP）研究。 重新计算样本量o数据的基础 从IP。 第二阶段将继续工作 第一阶段在研究IPS的运营特征时 正常，二项式和对数级统计。 它将发展一个 实施IP研究的计算机程序包含了Lakatos 样本量计算的方法，lan-demets a支出方法 数据监视，随机限制和Bonferroni校正 多个终点。 第二阶段的研究组成部分将重点放在 合并方法的统计方法，同时仍保持 控制Alpha和Power。