Chapter 21 Randomization for Clinical Trials with R
There are a number of packages for doing key functions for clinical trials in R. You can find many of these on the CRAN Task View for Clinical Trials, at https://cran.r-project.org/web/views/ClinicalTrials.html.
This is a curated list of packages that anyone might find useful in designing, monitoring, or analyzing clinical trials, and is often a good place to start in looking for packages that might be relevant for clinical trials.
If you use Ctrl-F
to search the web page for “rand”, several packages address randomization, including
blockrand
randomizeR
pwr
experiment
clusterPower
CRTSize
cosa
PowerupR
Several of these are specifically for more complex designs, including cluster and multilevel randomization (clusterPower, cosa, CRTSize). For today, we will focus on the straightforward randomization packages including {blockrand} and {randomizer}. The {blockrand} package creates randomizations for clinical trials with can include stratified enrollment and permuted block randomization, and can produce a PDF file of randomization cards.
Let’s start with an example in {blockrand}.
Details on the package can be found at https://cran.r-project.org/web/packages/blockrand/blockrand.pdf
or by running help(blockrand)
in your Console.
You want to randomize 180 inpatients with severe ulcerative colitis to one of 3 arms: corticosteroids alone (control), corticosteroids + tofacitinib, or corticosteroids + upadacitinib. You want to stratify the participants by (1) prior biologic failure and (2) Albumin level above or below 3.0. To be prepared for dropouts and imbalanced enrollment, you want to have a randomization list with at least 60 assignments available for each arm and stratum. To avoid a recognizable pattern in the randomization, you want to have a permuted block design with blocks of sizes 3, 6, and 9.
Below, you will see how to do this for the biologic failure - low albumin stratum.
bfla <- blockrand(n = 60,
num.levels = 3, # three treatments
levels = c("CS", "CS/Tofa", "CS/Upa"), # arm names
stratum = "Bfail.LowAlb", # stratum name
id.prefix = "BfLA", # stratum abbrev
block.sizes = c(1,2,3), # times arms = 3,6,9
block.prefix = "BfLA") # stratum abbrev
bfla
## id stratum block.id block.size treatment
## 1 BfLA01 Bfail.LowAlb BfLA01 6 CS/Upa
## 2 BfLA02 Bfail.LowAlb BfLA01 6 CS/Tofa
## 3 BfLA03 Bfail.LowAlb BfLA01 6 CS
## 4 BfLA04 Bfail.LowAlb BfLA01 6 CS/Upa
## 5 BfLA05 Bfail.LowAlb BfLA01 6 CS
## 6 BfLA06 Bfail.LowAlb BfLA01 6 CS/Tofa
## 7 BfLA07 Bfail.LowAlb BfLA02 6 CS/Upa
## 8 BfLA08 Bfail.LowAlb BfLA02 6 CS/Tofa
## 9 BfLA09 Bfail.LowAlb BfLA02 6 CS/Tofa
## 10 BfLA10 Bfail.LowAlb BfLA02 6 CS/Upa
## 11 BfLA11 Bfail.LowAlb BfLA02 6 CS
## 12 BfLA12 Bfail.LowAlb BfLA02 6 CS
## 13 BfLA13 Bfail.LowAlb BfLA03 9 CS
## 14 BfLA14 Bfail.LowAlb BfLA03 9 CS/Upa
## 15 BfLA15 Bfail.LowAlb BfLA03 9 CS
## 16 BfLA16 Bfail.LowAlb BfLA03 9 CS/Tofa
## 17 BfLA17 Bfail.LowAlb BfLA03 9 CS
## 18 BfLA18 Bfail.LowAlb BfLA03 9 CS/Upa
## 19 BfLA19 Bfail.LowAlb BfLA03 9 CS/Upa
## 20 BfLA20 Bfail.LowAlb BfLA03 9 CS/Tofa
## 21 BfLA21 Bfail.LowAlb BfLA03 9 CS/Tofa
## 22 BfLA22 Bfail.LowAlb BfLA04 9 CS/Upa
## 23 BfLA23 Bfail.LowAlb BfLA04 9 CS/Upa
## 24 BfLA24 Bfail.LowAlb BfLA04 9 CS
## 25 BfLA25 Bfail.LowAlb BfLA04 9 CS/Tofa
## 26 BfLA26 Bfail.LowAlb BfLA04 9 CS/Tofa
## 27 BfLA27 Bfail.LowAlb BfLA04 9 CS
## 28 BfLA28 Bfail.LowAlb BfLA04 9 CS/Tofa
## 29 BfLA29 Bfail.LowAlb BfLA04 9 CS/Upa
## 30 BfLA30 Bfail.LowAlb BfLA04 9 CS
## 31 BfLA31 Bfail.LowAlb BfLA05 3 CS/Upa
## 32 BfLA32 Bfail.LowAlb BfLA05 3 CS
## 33 BfLA33 Bfail.LowAlb BfLA05 3 CS/Tofa
## 34 BfLA34 Bfail.LowAlb BfLA06 6 CS/Upa
## 35 BfLA35 Bfail.LowAlb BfLA06 6 CS/Tofa
## 36 BfLA36 Bfail.LowAlb BfLA06 6 CS
## 37 BfLA37 Bfail.LowAlb BfLA06 6 CS/Tofa
## 38 BfLA38 Bfail.LowAlb BfLA06 6 CS/Upa
## 39 BfLA39 Bfail.LowAlb BfLA06 6 CS
## 40 BfLA40 Bfail.LowAlb BfLA07 6 CS/Upa
## 41 BfLA41 Bfail.LowAlb BfLA07 6 CS/Upa
## 42 BfLA42 Bfail.LowAlb BfLA07 6 CS
## 43 BfLA43 Bfail.LowAlb BfLA07 6 CS/Tofa
## 44 BfLA44 Bfail.LowAlb BfLA07 6 CS/Tofa
## 45 BfLA45 Bfail.LowAlb BfLA07 6 CS
## 46 BfLA46 Bfail.LowAlb BfLA08 9 CS/Tofa
## 47 BfLA47 Bfail.LowAlb BfLA08 9 CS/Upa
## 48 BfLA48 Bfail.LowAlb BfLA08 9 CS/Upa
## 49 BfLA49 Bfail.LowAlb BfLA08 9 CS
## 50 BfLA50 Bfail.LowAlb BfLA08 9 CS/Tofa
## 51 BfLA51 Bfail.LowAlb BfLA08 9 CS
## 52 BfLA52 Bfail.LowAlb BfLA08 9 CS/Tofa
## 53 BfLA53 Bfail.LowAlb BfLA08 9 CS/Upa
## 54 BfLA54 Bfail.LowAlb BfLA08 9 CS
## 55 BfLA55 Bfail.LowAlb BfLA09 3 CS/Tofa
## 56 BfLA56 Bfail.LowAlb BfLA09 3 CS
## 57 BfLA57 Bfail.LowAlb BfLA09 3 CS/Upa
## 58 BfLA58 Bfail.LowAlb BfLA10 3 CS/Tofa
## 59 BfLA59 Bfail.LowAlb BfLA10 3 CS
## 60 BfLA60 Bfail.LowAlb BfLA10 3 CS/Upa
You can see the id
for each participant, their stratum
, the block.id
for their permuted block, the block.size
, and their assigned treatment
. You can imagine this as a randomization list, or as assignments that you could print out on cards and seal in security envelopes for the time of randomization. Of course, this is only one of our four strata. We should do the same for the 3 other strata.
bfha <- blockrand(n = 60,
num.levels = 3, # three treatments
levels = c("CS", "CS/Tofa", "CS/Upa"), # arm names
stratum = "Bfail.HiAlb", # stratum name
id.prefix = "BfHA", # stratum abbrev
block.sizes = c(1,2,3), # times arms = 3,6,9
block.prefix = "BfHA") # stratum abbrev
bfha
## id stratum block.id block.size treatment
## 1 BfHA01 Bfail.HiAlb BfHA1 9 CS/Tofa
## 2 BfHA02 Bfail.HiAlb BfHA1 9 CS/Upa
## 3 BfHA03 Bfail.HiAlb BfHA1 9 CS/Tofa
## 4 BfHA04 Bfail.HiAlb BfHA1 9 CS/Upa
## 5 BfHA05 Bfail.HiAlb BfHA1 9 CS
## 6 BfHA06 Bfail.HiAlb BfHA1 9 CS/Tofa
## 7 BfHA07 Bfail.HiAlb BfHA1 9 CS/Upa
## 8 BfHA08 Bfail.HiAlb BfHA1 9 CS
## 9 BfHA09 Bfail.HiAlb BfHA1 9 CS
## 10 BfHA10 Bfail.HiAlb BfHA2 3 CS/Upa
## 11 BfHA11 Bfail.HiAlb BfHA2 3 CS/Tofa
## 12 BfHA12 Bfail.HiAlb BfHA2 3 CS
## 13 BfHA13 Bfail.HiAlb BfHA3 6 CS/Tofa
## 14 BfHA14 Bfail.HiAlb BfHA3 6 CS/Tofa
## 15 BfHA15 Bfail.HiAlb BfHA3 6 CS
## 16 BfHA16 Bfail.HiAlb BfHA3 6 CS
## 17 BfHA17 Bfail.HiAlb BfHA3 6 CS/Upa
## 18 BfHA18 Bfail.HiAlb BfHA3 6 CS/Upa
## 19 BfHA19 Bfail.HiAlb BfHA4 6 CS
## 20 BfHA20 Bfail.HiAlb BfHA4 6 CS/Upa
## 21 BfHA21 Bfail.HiAlb BfHA4 6 CS/Tofa
## 22 BfHA22 Bfail.HiAlb BfHA4 6 CS/Tofa
## 23 BfHA23 Bfail.HiAlb BfHA4 6 CS
## 24 BfHA24 Bfail.HiAlb BfHA4 6 CS/Upa
## 25 BfHA25 Bfail.HiAlb BfHA5 6 CS/Upa
## 26 BfHA26 Bfail.HiAlb BfHA5 6 CS/Upa
## 27 BfHA27 Bfail.HiAlb BfHA5 6 CS/Tofa
## 28 BfHA28 Bfail.HiAlb BfHA5 6 CS
## 29 BfHA29 Bfail.HiAlb BfHA5 6 CS
## 30 BfHA30 Bfail.HiAlb BfHA5 6 CS/Tofa
## 31 BfHA31 Bfail.HiAlb BfHA6 9 CS/Upa
## 32 BfHA32 Bfail.HiAlb BfHA6 9 CS
## 33 BfHA33 Bfail.HiAlb BfHA6 9 CS/Tofa
## 34 BfHA34 Bfail.HiAlb BfHA6 9 CS/Tofa
## 35 BfHA35 Bfail.HiAlb BfHA6 9 CS/Upa
## 36 BfHA36 Bfail.HiAlb BfHA6 9 CS
## 37 BfHA37 Bfail.HiAlb BfHA6 9 CS/Upa
## 38 BfHA38 Bfail.HiAlb BfHA6 9 CS/Tofa
## 39 BfHA39 Bfail.HiAlb BfHA6 9 CS
## 40 BfHA40 Bfail.HiAlb BfHA7 6 CS/Tofa
## 41 BfHA41 Bfail.HiAlb BfHA7 6 CS/Tofa
## 42 BfHA42 Bfail.HiAlb BfHA7 6 CS/Upa
## 43 BfHA43 Bfail.HiAlb BfHA7 6 CS/Upa
## 44 BfHA44 Bfail.HiAlb BfHA7 6 CS
## 45 BfHA45 Bfail.HiAlb BfHA7 6 CS
## 46 BfHA46 Bfail.HiAlb BfHA8 9 CS/Tofa
## 47 BfHA47 Bfail.HiAlb BfHA8 9 CS
## 48 BfHA48 Bfail.HiAlb BfHA8 9 CS/Upa
## 49 BfHA49 Bfail.HiAlb BfHA8 9 CS/Upa
## 50 BfHA50 Bfail.HiAlb BfHA8 9 CS/Tofa
## 51 BfHA51 Bfail.HiAlb BfHA8 9 CS
## 52 BfHA52 Bfail.HiAlb BfHA8 9 CS
## 53 BfHA53 Bfail.HiAlb BfHA8 9 CS/Upa
## 54 BfHA54 Bfail.HiAlb BfHA8 9 CS/Tofa
## 55 BfHA55 Bfail.HiAlb BfHA9 9 CS/Tofa
## 56 BfHA56 Bfail.HiAlb BfHA9 9 CS/Upa
## 57 BfHA57 Bfail.HiAlb BfHA9 9 CS/Upa
## 58 BfHA58 Bfail.HiAlb BfHA9 9 CS/Tofa
## 59 BfHA59 Bfail.HiAlb BfHA9 9 CS/Tofa
## 60 BfHA60 Bfail.HiAlb BfHA9 9 CS
## 61 BfHA61 Bfail.HiAlb BfHA9 9 CS/Upa
## 62 BfHA62 Bfail.HiAlb BfHA9 9 CS
## 63 BfHA63 Bfail.HiAlb BfHA9 9 CS
bnha <- blockrand(n = 60,
num.levels = 3,
levels = c("CS", "CS/Tofa", "CS/Upa"),
stratum = "Bnaive.HiAlb",
id.prefix = "BnHA",
block.sizes = c(1,2,3, 4),
block.prefix = "BnHA")
bnha
## id stratum block.id block.size treatment
## 1 BnHA01 Bnaive.HiAlb BnHA01 9 CS/Upa
## 2 BnHA02 Bnaive.HiAlb BnHA01 9 CS/Upa
## 3 BnHA03 Bnaive.HiAlb BnHA01 9 CS
## 4 BnHA04 Bnaive.HiAlb BnHA01 9 CS
## 5 BnHA05 Bnaive.HiAlb BnHA01 9 CS
## 6 BnHA06 Bnaive.HiAlb BnHA01 9 CS/Tofa
## 7 BnHA07 Bnaive.HiAlb BnHA01 9 CS/Tofa
## 8 BnHA08 Bnaive.HiAlb BnHA01 9 CS/Tofa
## 9 BnHA09 Bnaive.HiAlb BnHA01 9 CS/Upa
## 10 BnHA10 Bnaive.HiAlb BnHA02 9 CS/Tofa
## 11 BnHA11 Bnaive.HiAlb BnHA02 9 CS/Tofa
## 12 BnHA12 Bnaive.HiAlb BnHA02 9 CS
## 13 BnHA13 Bnaive.HiAlb BnHA02 9 CS/Tofa
## 14 BnHA14 Bnaive.HiAlb BnHA02 9 CS/Upa
## 15 BnHA15 Bnaive.HiAlb BnHA02 9 CS/Upa
## 16 BnHA16 Bnaive.HiAlb BnHA02 9 CS/Upa
## 17 BnHA17 Bnaive.HiAlb BnHA02 9 CS
## 18 BnHA18 Bnaive.HiAlb BnHA02 9 CS
## 19 BnHA19 Bnaive.HiAlb BnHA03 3 CS
## 20 BnHA20 Bnaive.HiAlb BnHA03 3 CS/Upa
## 21 BnHA21 Bnaive.HiAlb BnHA03 3 CS/Tofa
## 22 BnHA22 Bnaive.HiAlb BnHA04 3 CS/Upa
## 23 BnHA23 Bnaive.HiAlb BnHA04 3 CS/Tofa
## 24 BnHA24 Bnaive.HiAlb BnHA04 3 CS
## 25 BnHA25 Bnaive.HiAlb BnHA05 3 CS/Tofa
## 26 BnHA26 Bnaive.HiAlb BnHA05 3 CS/Upa
## 27 BnHA27 Bnaive.HiAlb BnHA05 3 CS
## 28 BnHA28 Bnaive.HiAlb BnHA06 9 CS
## 29 BnHA29 Bnaive.HiAlb BnHA06 9 CS/Tofa
## 30 BnHA30 Bnaive.HiAlb BnHA06 9 CS/Upa
## 31 BnHA31 Bnaive.HiAlb BnHA06 9 CS
## 32 BnHA32 Bnaive.HiAlb BnHA06 9 CS/Tofa
## 33 BnHA33 Bnaive.HiAlb BnHA06 9 CS/Upa
## 34 BnHA34 Bnaive.HiAlb BnHA06 9 CS/Tofa
## 35 BnHA35 Bnaive.HiAlb BnHA06 9 CS/Upa
## 36 BnHA36 Bnaive.HiAlb BnHA06 9 CS
## 37 BnHA37 Bnaive.HiAlb BnHA07 6 CS
## 38 BnHA38 Bnaive.HiAlb BnHA07 6 CS/Tofa
## 39 BnHA39 Bnaive.HiAlb BnHA07 6 CS/Tofa
## 40 BnHA40 Bnaive.HiAlb BnHA07 6 CS
## 41 BnHA41 Bnaive.HiAlb BnHA07 6 CS/Upa
## 42 BnHA42 Bnaive.HiAlb BnHA07 6 CS/Upa
## 43 BnHA43 Bnaive.HiAlb BnHA08 6 CS/Tofa
## 44 BnHA44 Bnaive.HiAlb BnHA08 6 CS/Upa
## 45 BnHA45 Bnaive.HiAlb BnHA08 6 CS/Upa
## 46 BnHA46 Bnaive.HiAlb BnHA08 6 CS
## 47 BnHA47 Bnaive.HiAlb BnHA08 6 CS
## 48 BnHA48 Bnaive.HiAlb BnHA08 6 CS/Tofa
## 49 BnHA49 Bnaive.HiAlb BnHA09 3 CS
## 50 BnHA50 Bnaive.HiAlb BnHA09 3 CS/Upa
## 51 BnHA51 Bnaive.HiAlb BnHA09 3 CS/Tofa
## 52 BnHA52 Bnaive.HiAlb BnHA10 12 CS/Upa
## 53 BnHA53 Bnaive.HiAlb BnHA10 12 CS/Tofa
## 54 BnHA54 Bnaive.HiAlb BnHA10 12 CS
## 55 BnHA55 Bnaive.HiAlb BnHA10 12 CS/Upa
## 56 BnHA56 Bnaive.HiAlb BnHA10 12 CS/Tofa
## 57 BnHA57 Bnaive.HiAlb BnHA10 12 CS
## 58 BnHA58 Bnaive.HiAlb BnHA10 12 CS/Tofa
## 59 BnHA59 Bnaive.HiAlb BnHA10 12 CS
## 60 BnHA60 Bnaive.HiAlb BnHA10 12 CS/Upa
## 61 BnHA61 Bnaive.HiAlb BnHA10 12 CS/Tofa
## 62 BnHA62 Bnaive.HiAlb BnHA10 12 CS
## 63 BnHA63 Bnaive.HiAlb BnHA10 12 CS/Upa
bnla <- blockrand(n = 60,
num.levels = 3,
levels = c("CS", "CS/Tofa", "CS/Upa"),
stratum = "Bnaive.LoAlb",
id.prefix = "BnLA",
block.sizes = c(1,2,3),
block.prefix = "BnLA")
bnla
## id stratum block.id block.size treatment
## 1 BnLA01 Bnaive.LoAlb BnLA01 3 CS/Tofa
## 2 BnLA02 Bnaive.LoAlb BnLA01 3 CS
## 3 BnLA03 Bnaive.LoAlb BnLA01 3 CS/Upa
## 4 BnLA04 Bnaive.LoAlb BnLA02 6 CS/Upa
## 5 BnLA05 Bnaive.LoAlb BnLA02 6 CS/Tofa
## 6 BnLA06 Bnaive.LoAlb BnLA02 6 CS
## 7 BnLA07 Bnaive.LoAlb BnLA02 6 CS/Upa
## 8 BnLA08 Bnaive.LoAlb BnLA02 6 CS/Tofa
## 9 BnLA09 Bnaive.LoAlb BnLA02 6 CS
## 10 BnLA10 Bnaive.LoAlb BnLA03 3 CS
## 11 BnLA11 Bnaive.LoAlb BnLA03 3 CS/Tofa
## 12 BnLA12 Bnaive.LoAlb BnLA03 3 CS/Upa
## 13 BnLA13 Bnaive.LoAlb BnLA04 6 CS/Upa
## 14 BnLA14 Bnaive.LoAlb BnLA04 6 CS/Upa
## 15 BnLA15 Bnaive.LoAlb BnLA04 6 CS/Tofa
## 16 BnLA16 Bnaive.LoAlb BnLA04 6 CS
## 17 BnLA17 Bnaive.LoAlb BnLA04 6 CS/Tofa
## 18 BnLA18 Bnaive.LoAlb BnLA04 6 CS
## 19 BnLA19 Bnaive.LoAlb BnLA05 6 CS/Upa
## 20 BnLA20 Bnaive.LoAlb BnLA05 6 CS
## 21 BnLA21 Bnaive.LoAlb BnLA05 6 CS/Tofa
## 22 BnLA22 Bnaive.LoAlb BnLA05 6 CS
## 23 BnLA23 Bnaive.LoAlb BnLA05 6 CS/Upa
## 24 BnLA24 Bnaive.LoAlb BnLA05 6 CS/Tofa
## 25 BnLA25 Bnaive.LoAlb BnLA06 6 CS
## 26 BnLA26 Bnaive.LoAlb BnLA06 6 CS/Tofa
## 27 BnLA27 Bnaive.LoAlb BnLA06 6 CS/Tofa
## 28 BnLA28 Bnaive.LoAlb BnLA06 6 CS/Upa
## 29 BnLA29 Bnaive.LoAlb BnLA06 6 CS
## 30 BnLA30 Bnaive.LoAlb BnLA06 6 CS/Upa
## 31 BnLA31 Bnaive.LoAlb BnLA07 9 CS/Upa
## 32 BnLA32 Bnaive.LoAlb BnLA07 9 CS
## 33 BnLA33 Bnaive.LoAlb BnLA07 9 CS/Tofa
## 34 BnLA34 Bnaive.LoAlb BnLA07 9 CS/Upa
## 35 BnLA35 Bnaive.LoAlb BnLA07 9 CS/Tofa
## 36 BnLA36 Bnaive.LoAlb BnLA07 9 CS
## 37 BnLA37 Bnaive.LoAlb BnLA07 9 CS/Upa
## 38 BnLA38 Bnaive.LoAlb BnLA07 9 CS/Tofa
## 39 BnLA39 Bnaive.LoAlb BnLA07 9 CS
## 40 BnLA40 Bnaive.LoAlb BnLA08 6 CS/Tofa
## 41 BnLA41 Bnaive.LoAlb BnLA08 6 CS
## 42 BnLA42 Bnaive.LoAlb BnLA08 6 CS/Upa
## 43 BnLA43 Bnaive.LoAlb BnLA08 6 CS/Upa
## 44 BnLA44 Bnaive.LoAlb BnLA08 6 CS
## 45 BnLA45 Bnaive.LoAlb BnLA08 6 CS/Tofa
## 46 BnLA46 Bnaive.LoAlb BnLA09 6 CS
## 47 BnLA47 Bnaive.LoAlb BnLA09 6 CS/Tofa
## 48 BnLA48 Bnaive.LoAlb BnLA09 6 CS
## 49 BnLA49 Bnaive.LoAlb BnLA09 6 CS/Tofa
## 50 BnLA50 Bnaive.LoAlb BnLA09 6 CS/Upa
## 51 BnLA51 Bnaive.LoAlb BnLA09 6 CS/Upa
## 52 BnLA52 Bnaive.LoAlb BnLA10 9 CS/Upa
## 53 BnLA53 Bnaive.LoAlb BnLA10 9 CS/Upa
## 54 BnLA54 Bnaive.LoAlb BnLA10 9 CS/Tofa
## 55 BnLA55 Bnaive.LoAlb BnLA10 9 CS/Tofa
## 56 BnLA56 Bnaive.LoAlb BnLA10 9 CS
## 57 BnLA57 Bnaive.LoAlb BnLA10 9 CS
## 58 BnLA58 Bnaive.LoAlb BnLA10 9 CS
## 59 BnLA59 Bnaive.LoAlb BnLA10 9 CS/Upa
## 60 BnLA60 Bnaive.LoAlb BnLA10 9 CS/Tofa
21.1 Printing these on Cards
Ideally, you will print out each randomization on a card, and seal it in a security envelope, with the outside of the envelope labeled with the id. You can do this with the plotblockrand() function. This function creates a pdf file of randomization cards for printing. These are designed so that the middle text will show in a standard letter sized envelope with a window, and the top text (the assignment) can be folded over to increase security (against anyone trying to peek through the security envelope to guess the assignment).
uc_study <- bind_rows(bfha, bfla, bnha, bnla) # bind together the four strata into one dataframe
blockrand::plotblockrand(uc_study, # input dataframe
file = "uc_study.pdf", # output pdf
# top hidden text with assignment
top=list(text=c('My Study','Patient: %ID%','Treatment: %TREAT%'),
col=c('black','black','red'),font=c(1,1,4)),
# middle text to show through window of # 10 envelope
middle=list(text=c("My Study","Stratum: %STRAT%","Patient: %ID%"),
col=c('black','blue','orange'),font=c(1,2,3)),
# bottom text- any instructions to study coordinator
bottom="Call 123-4567 to report patient entry",
cut.marks=TRUE) # add cut marks - 4 per page
Open up the file uc_study.pdf
in your Files tab to see the output pdf file, with assorted fonts and colors.
Just for fun, change (and then re-run) the
text “My Study” to something more interesting
change “Patient” to “Participant”
change “Treatment” to “Arm” or “Assignment”
change some of the colors to standard R colors
change some of the fonts (within 1-4)
Sometimes with equal blocks, and clear treatment effects or side effects, nurses or study coordinators can guess the randomization pattern. If you want to get fancy, and make it even harder to guess treatment assignments, you can add one of the unequal blocks options, to make it hard to find patterns in treatment or in side effects. Set uneq.beg = TRUE
for an unequal block in the beginning, or uneq.mid = TRUE
for an unequal block in the middle.
21.2 Now, try this yourself
You want to randomize 80 outpatients with Crohn’s disease to one of 8 arms, as part of a 2^3 factorial design to increase patient activation. These arms involve using (A,B, C) or not using (a,b,c) 3 intervention components. The 8 arms then become:
abc
abC
aBc
aBC
Abc
AbC
ABc
ABC
Then we want to stratify the participants by baseline PAM score (a measure of patient activation) with levels of low, medium, and high PAM.
To be prepared for dropouts and imbalanced enrollment, you want to have a randomization list with at least 32 assignments available for each arm and stratum. To avoid a recognizable pattern in the randomization, you want to have a permuted block design with blocks of sizes 8 and 16.
You can hover over top right corner of the code chunk below, and a copy icon will appear - click this to copy the code to your clipboard. You can then paste it into your local version of RStudio, edit it, and run it.
In the code block below, fill in the blanks to complete the code to make a dataframe for the low_pam
stratum.
low_pam <- blockrand(n = __,
num.levels = __, #eight treatments
levels = c("abc", "abC", "aBc", "aBC",
"Abc", "AbC", "ABc", "ABC"), # arm names
stratum = "__", # stratum name
id.prefix = "lp", # stratum abbrev
block.sizes = c(1,2,3), # times arms
block.prefix = "LP") # stratum abbrev
low_pam
Now that you have one stratum sorted, edit the code block below to create the med_pam
and high_pam
strata.
med_pam <- blockrand(n = __,
num.levels = __, #eight treatments
levels = c("abc", "abC", "aBc", "aBC",
"Abc", "AbC", "ABc", "ABC"), # arm names
stratum = "__", # stratum name
id.prefix = "__", # stratum abbrev
block.sizes = c(__), # times arms
block.prefix = "__") # stratum abbrev
med_pam
high_pam <- blockrand(n = __,
num.levels = __, #eight treatments
levels = c("abc", "abC", "aBc", "aBC",
"Abc", "AbC", "ABc", "ABC"), # arm names
stratum = "__", # stratum name
id.prefix = "__", # stratum abbrev
block.sizes = c(__), # times arms
block.prefix = "__") # stratum abbrev
high_pam
Great!
Now try to
bind these 3 strata into one dataframe
print these as cards to a pdf file
Edit the code chunk below to produce the pdf file
cd_study <- bind_rows(__,__,__) # bind together the 3 strata into one dataframe
blockrand::plotblockrand(__, # input dataframe
file = "cd_study.pdf", # output pdf
# top hidden text with assignment
top=list(text=c('CD Study','Patient: %ID%','Treatment: %__%'),
col=c('orange','blue','red'),font=c(1,1,4)),
# middle text to show through window of # 10 envelope
middle=list(text=c("CD Study","Stratum: %STRAT%","Patient: %__%"),
col=c('black','red','cadetblue'),font=c(1,2,3)),
# bottom text- any instructions to study coordinator
bottom="Call 123-4567 to report patient entry",
cut.marks=TRUE) # add cut marks - 4 per page
21.3 Now Freestyle
Your turn. Create randomization tables and a pdf file of cards for a study of 2 microbiome interventions to reduce the formation of colon adenomas.
your 3 study arms will be - placebo, Streptococcus thermophilus, and S.thermo plus lactose (a preferred sugar for S.t, making this arm a synbiotic, while arm 2 is a probiotic) - aka 3 arms called: pbo, probiotic, synbiotic.
Your stratifications will be by
prior polyps being MSI_hi or MSI_lo (for microsatellite instability mutations)
BMI above or below 35. BMI_hi, BMI_low
block sizes of 4,8,12,16
160 per arm
Edit the code block below for the first stratum
mhbh <- blockrand(n = __, # treatment arms
num.levels = __, # of treatments
levels = c("placebo", "probiotic", "synbiotic"), # arm names
stratum = "__,__", # stratum name
id.prefix = "mhbh", # stratum abbrev
block.sizes = c(__,__,__,__), # times arms
block.prefix = "__") # stratum abbrev
mhbh
Edit the code block below for the remaining strata
mhbl <- blockrand(n = __, # treatment arms
num.levels = 3, # of treatments
levels = c("placebo", "probiotic", "__"), # arm names
stratum = "msi_hi.bmi_lo", # stratum name
id.prefix = "__", # stratum abbrev
block.sizes = c(1,2,__,__), # times arms
block.prefix = "MHBL") # stratum abbrev
mhbl
mlbl <- blockrand(n = 160, # treatment arms
num.levels = __, # of treatments
levels = c("placebo", "__", "synbiotic"), # arm names
stratum = "__", # stratum name
id.prefix = "mlbl", # stratum abbrev
block.sizes = c(__,__,3,4), # times arms
block.prefix = "MLBL") # stratum abbrev
mlbl
mlbh <- blockrand(n = __, # treatment arms
num.levels = 3, # of treatments
levels = c("__", "probiotic", "synbiotic"), # arm names
stratum = "msi_lo.bmi_hi", # stratum name
id.prefix = "__", # stratum abbrev
block.sizes = c(1,2,3,4), # times arms
block.prefix = "MLBH") # stratum abbrev
mlbh
Edit the code block below to bind the strata together and print the cards
adenoma_study <- bind_rows(mlbl, mlbh, mhbh, mhbl) # bind together the strata into one dataframe
blockrand::plotblockrand(__, # input dataframe
file = "adenoma_cards.pdf", # output pdf
# top hidden text with assignment
top=list(text=c('Adenoma Study','Patient: %__%','Treatment: %TREAT%'),
col=c('orange','blue','red'),font=c(1,1,4)),
# middle text to show through window of # 10 envelope
middle=list(text=c("Adenoma Study","Stratum: %__%","Patient: %ID%"),
col=c('black','red','cadetblue'),font=c(1,2,3)),
# bottom text- any instructions to study coordinator
bottom="Call 123-4567 to report patient entry. \nInstruct participant to avoid antibiotics and stop aspirin",
cut.marks=TRUE) # add cut marks - 4 per page