ABdesign {designsize} | R Documentation |
Sample size determination for A + B escalation design without dose de-escalation
Description
Determination of sample size for each dose level using A + B escalation design without dose de-escalation
Usage
ABdesign(A, B, C, D, E, prop=c())
Arguments
A |
Number patients at the dose level i |
B |
Number of patients add at the dose level i when more than D number of patients have DLT |
C |
Predetermined number patients out of A. |
D |
Predetermined number patients out of A and D>=C |
E |
Predetermined number patients out of A+B and E>=D |
prop |
Vector of DLT rates at different dose level |
Details
Let there are "A" patients at the dose level "i" and also consider "C" and "D" as predetermined value where (D >= C).
If less than C patients have DLTs out of A patints then we escalate the dose at (i+1)th level and if more than D have the DLT's out of A then we consider the previous dose level (i-1)th as MTD(maximum dose level with toxicity rates occurring no more than a predetermined value).
If more than C and less than D patients have DLTs then we add B more patients at the ith dose level and then if more than E (E >= D) out of (A+B) patients have the DLTs then we consider the previous dose level as MTD.
Now we are going to determine the expected number of sample size at the jth dose level.
# prop = Vector of DLT rates at different dose level
# n = Total number of doses
# N = Vector of expected number of patients at different level of doses
Value
The expected number of patients at dose levels
Author(s)
Atanu Bhattacharjee, Rajashree Dey ,Soutik Halder and Akash Pawar
See Also
crt.match crt.unmatch phsize precsize
Examples
# This is A+B escalation design without dose de-escalation. Here A=3 , B=3 indicates the
# number of patients at the dose level i and taking C=D=E=1 the predetermined number of
# patients with DLT. Prop indicates the vector of the DLT rates at different dose level.
ABdesign(A = 3,B = 3,C = 1,D = 1,E = 1,prop= c(0.01,0.014,0.025,0.056,0.177,0.594,0.963))