Introduction

The toxAUC() function gives the user a set of tools to assess incremental AUC (iAUC) adjusted for baseline symptoms. The accumulated area of the symptomatic AE profile above baseline can be interpreted as symptom worsening driven by treatment. Arm-level iAUCs can be compared statistically using the function parameters.

library(ProAE)
require(knitr)

data(tox_acute)

In the example below, we will use the provided ProAE::tox_acute data frame. This data was simulated to demonstrate a common symptomatic AE profile where the drug group experiences acute toxicity followed by symptom abatement over the course of treatment.

In order to use the toxAUC() function the data frame needs to be in long format (multiple rows per patient). Additionally, the cycle variable needs to be numeric.

Example 1 - Calculate and compare baseline adjusted incremental area under the curve by arm

acute <- tox_acute

str(acute)

'data.frame':   1400 obs. of  7 variables:
 $ id             : int  1 1 1 1 1 1 1 1 1 1 ...
 $ Cycle          : int  1 2 3 4 5 6 7 8 9 10 ...
 $ arm            : chr  "Drug" "Drug" "Drug" "Drug" ...
 $ PROCTCAE_9A_SCL: num  0 2 4 0 0 0 0 0 0 0 ...
 $ PROCTCAE_9B_SCL: num  0 2 3 3 0 1 0 0 0 0 ...
 $ PROCTCAE_9_COMP: num  0 2 3 0 0 0 0 0 0 0 ...
 $ time           : chr  "Cycle 1" "Cycle 2" "Cycle 3" "Cycle 4" ...

Below is the call for the toxAUC() function which will graph the the iAUC above baseline for two arms over the course of the trial. It will also perform a permutation test and provide a two-sided p value comparing the iAUC between the two arms.

AUC = toxAUC(dsn = acute,
             id_var = "id",
             cycle_var = "Cycle",
             arm_var = "arm",
             baseline_val = 1,
             permute_tests = TRUE)

  index      short_label
1     1 Nausea Frequency
2     2  Nausea Severity
3     3 Nausea Composite

Using the specified index from the table we can examine the table for the composite score for Nausea

AUC[[3]][2]

[[1]]