This is a supplementary document for the file “Exposure-Adjusted
Adverse Event Summary (Updated)”. We first provide an explanation for
the calculation of the exposure adjusted event rate (EAER) of adverse
events, and then briefly summarize the programming steps of this
calculation.
The exposure factor (exp factor) will be adjusted depending on the
adjustment unit defined by users. For instance, when the adjustment unit
is ‘100 person-month’, EAER will be computed as follows:
EAER for different types of AEs
As an example, below are the EAER definitions for three types of AEs
using three treatment groups (PBO, Low Dose, High Dose).
ANY AE adj rate
Serious AE adj rate
REL AE adj rate
Programming steps of EAER
- Data preprocessing: At the end of this step,
adae
is
created.
- Build a metadata object: At the end of this step,
meta
is created.
- Call the function
prepare_ae_summary()
and
extend_ae_summary_eaer()
. This extend function has the
following arguments: outdata
, duration_var
,
and adj_unit
. The output will be a list:
## List of 17
## $ meta :List of 7
## $ population : chr "apat"
## $ observation : chr "wk12"
## $ parameter : chr "any;rel;ser"
## $ n :'data.frame': 5 obs. of 4 variables:
## $ order : num [1:5] 1 100 200 300 400
## $ group : chr [1:4] "Placebo" "Low Dose" "High Dose" "Total"
## $ reference_group: num 1
## $ prop :'data.frame': 5 obs. of 4 variables:
## $ diff :'data.frame': 5 obs. of 2 variables:
## $ n_pop :'data.frame': 1 obs. of 4 variables:
## $ name : chr [1:5] "Participants in population" "with one or more adverse events" "with no adverse events" "with drug-related{^a} adverse events" ...
## $ prepare_call : language prepare_ae_summary(meta = meta, population = "apat", observation = "wk12", parameter = "any;rel;ser", )
## $ total_exp :'data.frame': 1 obs. of 4 variables:
## $ event_num :'data.frame': 3 obs. of 4 variables:
## $ eaer :'data.frame': 3 obs. of 4 variables:
## $ adj_unit : chr "month"
Run x$eaer
to get the EAER:
## Placebo Low Dose High Dose Total
## 1 71.46214 159.1724513 165.8725416 122.9359029
## 2 31.57630 106.8467949 101.7108552 72.6674019
## 3 0.00000 0.3659137 0.7291101 0.3096622