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R package to create tables and plots for analysing adverse event data in clinical trials

How to install

You can install aeplots with:

# install.packages("devtools")
devtools::install_github("https://github.com/txx4986/aeplots.git")

Please refer to the devtools documentation for instructions on how to set up a working development environment and install devtools depending on your platform.

Adverse Event Data

Functions available in the package:

  • aetable: Plots a table of AE summary by body system class
  • aeseverity: Plots a table of AE summary by severity and body system class
  • aedot: Plots a dot plot with proportions alongside treatment effect estimates with accompanying 95% confidence interval
  • aestacked: Plots a stacked bar chart to present the proportions of participants with each event by arm and by maximum severity
  • aebar: Plots a bar chart to present the number of events reported per participant
  • aevolcano: Plots a volcano plot of treatment effect estimate against -log10(p-value)
  • aemcf: Plots the mean cumulative function of AE with risk table

To see more detailed documentation of each function:

help(aetable)

or

?aetable

Sample dataset

id arm adverse_event body_system_class severity date_rand date_ae last_visit variable1 variable2
2001 Placebo Cold Respiratory Moderate 2015-10-28 2016-04-24 2016-08-31 2 910.785
2001 Placebo Anemia Blood and lymphatic Severe 2015-10-28 2015-11-11 2016-08-31 2 910.785
2001 Placebo Anemia Blood and lymphatic Moderate 2015-10-28 2016-05-10 2016-08-31 2 910.785
2001 Placebo Leukocytosis Blood and lymphatic Severe 2015-10-28 2016-08-29 2016-08-31 2 910.785
2001 Placebo Nausea Gastrointestinal Severe 2015-10-28 2016-02-23 2016-08-31 2 910.785
2002 Intervention Other Blood and lymphatic Moderate 2015-08-18 2015-11-17 2016-07-29 2 736.752
2002 Intervention Toothache Other Moderate 2015-08-18 2016-04-30 2016-07-29 2 736.752
2002 Intervention Accident Other Moderate 2015-08-18 2016-03-02 2016-07-29 2 736.752
2004 Placebo Cystitis Renal and urinary Mild 2015-04-26 2015-07-06 2016-08-11 1 307.814
2004 Placebo Vomiting Gastrointestinal Severe 2015-04-26 2016-06-20 2016-08-11 1 307.814
2004 Placebo Vomiting Gastrointestinal Mild 2015-04-26 2016-03-19 2016-08-11 1 307.814
2004 Placebo Vomiting Gastrointestinal Mild 2015-04-26 2015-08-21 2016-08-11 1 307.814
2004 Placebo Anemia Blood and lymphatic Moderate 2015-04-26 2016-07-26 2016-08-11 1 307.814
2004 Placebo Dry skin Dermatological Moderate 2015-04-26 2016-03-26 2016-08-11 1 307.814
2008 Intervention Other Blood and lymphatic Moderate 2015-12-04 2016-01-07 2016-04-28 4 380.890
2008 Intervention Anemia Blood and lymphatic Mild 2015-12-04 2016-02-11 2016-04-28 4 380.890
2008 Intervention Anemia Blood and lymphatic Mild 2015-12-04 2016-02-05 2016-04-28 4 380.890
2008 Intervention Nausea Gastrointestinal Moderate 2015-12-04 2016-04-19 2016-04-28 4 380.890
2014 Intervention Headache Neuruological Mild 2015-10-16 2016-01-18 2016-01-19 3 389.012
2014 Intervention Headache Neuruological Mild 2015-10-16 2015-12-27 2016-01-19 3 389.012

Note that for each participant who did not experience any adverse events, a row should be included in the input dataset stating his/her id, arm, date_rand, last_visit and variables to be included in the model. adverse_event, body_system_class, severity and date_ae column should be specified as NA. For example:

id arm adverse_event body_system_class severity date_rand date_ae last_visit variable1 variable2
2032 Intervention NA NA NA 2015-05-22 NA 2016-04-22 2 1500
2033 Placebo NA NA NA 2015-04-20 NA 2016-03-20 1 777

Variable description for sample dataset

Variable name Variable description Variable type
id Participant ID Factor/Character/Numeric
arm Treatment arm of participant (2, 3 or 4 arms) Factor/Character/Numeric
adverse_event Adverse event preferred term Character
body_system_class Body system class of adverse event Factor
severity Severity of adverse event (2, 3, 4 or 5 severity levels) Factor
date_rand Randomisation date Date
date_ae Date of adverse event Date
last_visit Date of last visit Date
variable Variables to be included in model for estimation of treatment effect estimates and 95% CIs Factor/Character/Numeric

Laboratory Data

Functions available in the package:

  • labtable: Plots a table that summarises laboratory values with continuous outcomes for baseline and each post-baseline timepoint by treatment arm

To see more detailed documentation of each function:

help(labtable)

or

?labtable

Sample dataset

id arm visit lab_test base aval lower upper region strat time
1 Placebo Week 0 Lymphocytes (GI/L) 2.57 2.57 0.85 4.1 Europe < 1 year 0
1 Placebo Week 4 Lymphocytes (GI/L) 2.57 1.87 0.85 4.1 Europe < 1 year 4
1 Placebo Week 8 Lymphocytes (GI/L) 2.57 3.14 0.85 4.1 Europe < 1 year 8
1 Placebo Week 0 Potassium (mmol/L) 3.89 3.89 3.50 5.3 Europe < 1 year 0
1 Placebo Week 4 Potassium (mmol/L) 3.89 3.90 3.50 5.3 Europe < 1 year 4
1 Placebo Week 8 Potassium (mmol/L) 3.89 3.89 3.50 5.3 Europe < 1 year 8
2 Intervention Week 0 Lymphocytes (GI/L) 2.31 2.31 0.85 4.1 Other >=1 year 0
2 Intervention Week 4 Lymphocytes (GI/L) 2.31 2.54 0.85 4.1 Other >=1 year 4
2 Intervention Week 8 Lymphocytes (GI/L) 2.31 1.07 0.85 4.1 Other >=1 year 8
2 Intervention Week 0 Potassium (mmol/L) 4.08 4.08 3.50 5.3 Other >=1 year 0
2 Intervention Week 4 Potassium (mmol/L) 4.08 3.97 3.50 5.3 Other >=1 year 4
2 Intervention Week 8 Potassium (mmol/L) 4.08 3.92 3.50 5.3 Other >=1 year 8
3 Placebo Week 0 Lymphocytes (GI/L) 2.50 2.50 0.85 4.1 Other >=1 year 0
3 Placebo Week 4 Lymphocytes (GI/L) 2.50 3.25 0.85 4.1 Other >=1 year 4
3 Placebo Week 8 Lymphocytes (GI/L) 2.50 3.17 0.85 4.1 Other >=1 year 8
3 Placebo Week 0 Potassium (mmol/L) 4.08 4.08 3.50 5.3 Other >=1 year 0
3 Placebo Week 4 Potassium (mmol/L) 4.08 4.12 3.50 5.3 Other >=1 year 4
3 Placebo Week 8 Potassium (mmol/L) 4.08 4.38 3.50 5.3 Other >=1 year 8

Variable description for sample dataset

Variable name Variable description Variable type
id Participant ID Factor/Character/Numeric
arm Treatment arm of participant (2, 3 or 4 arms) Factor/Character/Numeric
visit Timepoint of laboratory test taken Ordered factor
lab_test Laboratory test Factor/Character
base Baseline laboratory measurement value Numeric
aval Laboratory measurement value Numeric
lower Lower limit of normal range Numeric
upper Upper limit of normal range Numeric
base / strat / region / time Variables to be included in model for estimation of treatment effect estimates and 95% CIs Factor/Character/Numeric