# getN2: Calculates the number of patients which should be enrolled in... In OneArmPhaseTwoStudy: Planning, Conducting, and Analysing Single-Arm Phase II Studies

## Description

Calculates the number of patients which should be enrolled in the second stage if the conditional power should be altert to "cp".

## Usage

 `1` ```getN2(cp, p1, design, k, mode = 0, alpha = 0.05) ```

## Arguments

 `cp` conditional power to which the number of patients for the second stage should be adjusted. `p1` response probability under the alternative hypothesis. `design` a dataframe containing all critical values for a Simon's two-stage design defined by the colums r1, n1, r, n and p0. r1 = critical value for the first stage (more than r1 responses needed to proceed to the second stage). n1 = number of patients enrolled in the first stage. r = critical value for the whole trial (more than r responses needed at the end of the study to reject the null hypothesis). n = number of patients enrolled in the whole trial. p0 = response probability under the null hypothesis. `k` number of responses observed at the interim analysis. `mode` a value out of {0,1,2,3} dedicating the methode spending the "rest alpha" (difference between nominal alpha level and actual alpha level for the given design). 0 = "rest alpha" is not used. 1 = "rest alpha" is spent proportionally. 2 = "rest alpha" is spent equally. 3 = "rest alpha" is spent only to the worst case scenario (minimal number of responses at the interim analysis so that the study can proceed to the second stage). `alpha` overall significance level the trial was planned for.

## References

Englert S., Kieser M. (2012): Adaptive designs for single-arm phase II trials in oncology. Pharmaceutical Statistics 11,241-249.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```#Calculate a Simon's two-stage design design <- getSolutions()\$Solutions[3,] #minimax-design for the default values. #Assume we only observed 3 responses in the interim analysis. #Therefore the conditional power is only about 0.55. #In order to raise the conditional power to 0.8 "n2" has to be increased. #set k to 3 (only 3 responses observed so far) k = 3 # Assume we spent the "rest alpha" proportionally in the planning phase # there for we set "mode = 1". n2 <- getN2(cp = 0.8, design\$p1, design, k, mode = 1, alpha = 0.05) n2 ```

OneArmPhaseTwoStudy documentation built on May 2, 2019, 9:28 a.m.