連續型變數之貝氏二階段第二期臨床試驗設計

Abstract

製藥發展是需要長時間和花費的一個過程，而許多機構在執行藥物臨床測試時，藥物在相對較晚的程序中才宣告失敗停止，因此基於在偵測藥物效能上使用較快且可靠的方法並且減少受試者人數和試驗所需時間，研發出新式臨床策略或方法設計，其中的設計是更加有效率不論是在執行上或是花費上在偵測有可能性的藥物，而新設計在製藥發展中有著迫切的需要。在臨床試驗第二階段(phase II clinical trials)，其中兩階段(two-stage)或是多階段(multiple-stage) 無對照組試驗設計多採用frequentist的統計方法，另一方面，相對於frequentist另有貝氏(Bayesian) 統計方法，貝氏方法可將相關的先前資訊納入臨床結果分析之中，可使之更加符合直覺並且對試驗更有幫助。在此篇論文當中，針對連續型變數提出兩種貝氏二階段藥物效用監控設計，並針對此二設計提出數值範例來示範此二貝氏設計並且與frequentist的統計方法做出比較。

Pharmaceutical development is a lengthy and expensive process and many of these agents fail relatively late in that process. Hence, there is an urgent need of new strategies and methodology for efficient and cost-effective designs to screen potential candidates based on the idea of the proof of the concept for efficacy in a rapid and reliable manner to minimize the total sample size and hence to shorten the duration of the trials. In phase II clinical trials, two-stage or multiple-stage designs with no control group have been proposed based on frequentist statistical approaches. Alternatively, Bayesian methods incorporating relevant prior information into the analysis of the trial results may be more intuitive and helpful. In this thesis, two Bayesian two-stage screening designs based on continuous efficacy endpoints are proposed. Numerical example is presented to illustrate the Bayesian approach. Comparisons with other frequentist approaches are also made.