Phase II Clinical Trial

Introduction: The main goal of Phase II clinical trials is to identify the therapeutic efficacy of new treatments. They are usually single-arm studies, but may take the form of multiple-arm trials. Multiple-arm trials can be randomized or non-randomized with or without control arms.

Phase II clinical trials are generally single-arm studies aimed at estimating the activity of a new treatment. These “pilot” studies are commonly applied to anticancer drugs to assess the therapeutic efficacy and toxicity of new treatment regimens. Phase II trials decide whether the new treatment is promising and warrants further investigation in a large-scale randomized Phase III clinical trial based on an observed response rate that appears to be an improvement over the standard treatment or other experimental treatments. Because the sample size is small (generally less than 50 patients), Phase II clinical trials are only able to detect a large treatment improvement, e.g. greater than 10%. To detect a small difference in treatment, e.g. less than 5%, one would require a much larger sample size, which is not possible in Phase II studies due to the limited number of subjects eligible for the study and the large number of treatments awaiting study.  Phase II studies are prominent in cancer therapeutics because new treatments frequently arise from combinations of existing therapies or by varying dose or radiation schedules.

There are three main objectives in treating patients in Phase II clinical trials. The primary objective is to test whether the therapeutic intervention benefits the patient. The second objective is to screen the experimental treatment for the response activity in a given type of cancer. The final objective is to extend our knowledge of the toxicology and pharmacology of the treatment.

An important characteristic of some Phase II trial designs is the use of early stopping rules. If there is sufficient evidence that one of the treatments under study has a positive treatment effect, then patient accrual is terminated and this treatment is declared promising. Also, if a treatment is sufficiently shown not to have a desirable effect, then patient accrual is terminated and this treatment is declared not promising.

This program helps users to determine sample sizes or decision rules for a Phase II clinical trial so that the sample size needed for a standard Phase II clinical trial can be reduced.

If you don’t know which program to use, please feel free to check : User guidance, definition and terminology


Means

 

Proportions

Survival Analysis

Phase II Clinical Trials

Epidemiological Studies

Confidence Intervals

Others

Phase II Clinical Trials

       1.     Fleming's Phase II Procedure

       2.     Bayesian Phase II Design

   3.     Simon’s Randomized Phase II Design

 

 

Further Information:

Difference between Fleming’s procedure and Bayesian design of Phase II clinical trials

This section describes both the hypotheses and design for Fleming’s and the Bayesian approach to single-arm Phase II clinical trials. Both designs are used for Phase II clinical trials with binary outcomes and continuous monitoring. The fundamental difference between the two designs is the frequentist basis for Fleming’s procedure only depends on the observed results whereas the Bayesian approach uses prior information. The testing procedure for Fleming’s procedure is based on the normal approximation to the binomial distribution of the observed number of treatment responses. The resulting decision boundaries, rg and ag, are solved analytically. The Bayesian design incorporates prior information about the treatment being investigated with the observed results to yield revised beliefs about the treatment. The testing procedure is based on the posterior probability of the experimental treatment given the observed data. The posterior probability is a conditional probability computed from a beta distribution which results in the upper and lower decision boundaries, Un and Ln, which are evaluated using numerical integration, namely “Simpson’s Composite Algorithm”.  Another difference between the two designs is that Fleming’s procedure has only two outcomes at the final recruitment stage, reject or accept H0, whereas the Bayesian design traditionally allows for an inconclusive trial at the final stage.