Targeted Therapy Safety Profile Dataset

Simulated targeted therapy clinical trial adverse event dataset featuring characteristic targeted therapy toxicities, early onset patterns, and class-specific effects. Designed to test targeted therapy safety analysis, mechanism-based toxicity profiling, and kinase inhibitor safety monitoring typical in precision oncology.

Usage

toxicityprofile_targeted_therapy

Format

A data frame with 1,142 adverse events from 200 patients and 8 variables:

patient_id

Character. Unique patient identifier (TRG_001 to TRG_200)

treatment_group

Factor. Treatment regimen ("Monotherapy", "Combination")

adverse_event

Factor. Targeted therapy-specific adverse events (24 unique events)

toxicity_grade

Integer. CTCAE grade with targeted therapy-specific patterns

system_organ_class

Factor. MedDRA SOC emphasizing targeted therapy effects

time_to_event

Integer. Days to AE onset (typically early, 1-365 days)

patient_age

Integer. Patient age at enrollment

patient_sex

Factor. Patient sex ("Male", "Female")

Source

Simulated data generated using create_toxicityprofile_test_data.R

Details

This dataset simulates targeted therapy safety data with characteristic class effects, early onset patterns, and mechanism-based toxicity profiles. It reflects real-world targeted therapy safety experience including kinase inhibitor effects, EGFR inhibitor toxicities, and angiogenesis inhibitor-related events.

Clinical Context:

• Targeted therapy trial comparing monotherapy vs combination

• 200 patients with targeted therapy-specific toxicity focus

• 24 mechanism-based adverse events

• Early onset patterns typical of targeted agents

• Class-specific toxicity distributions

Targeted Therapy-Specific Adverse Events:

• Gastrointestinal: Diarrhea, Mucositis, Nausea, Vomiting

• Dermatologic: Rash, Acneiform rash, Paronychia, Dry skin, Hand-foot syndrome

• Constitutional: Fatigue, Decreased appetite

• Cardiovascular: Hypertension, QT prolongation

• Vascular: Bleeding, Thrombosis, Proteinuria

• Hepatic: Elevated transaminases, Hyperbilirubinemia

• Pulmonary: Pneumonitis, Interstitial lung disease

• Other: Peripheral edema, Pleural effusion, Muscle spasms, Arthralgia

Key Features:

• Early onset patterns characteristic of targeted agents

• Higher frequency of dermatologic and GI toxicities

• Cardiovascular effects typical of angiogenesis inhibitors

• Appropriate grade distributions for each toxicity class

• Realistic incidence rates based on clinical experience

Recommended Analysis Scenarios:

• Targeted therapy toxicity profiling

• Class effect identification and analysis

• Early vs late onset toxicity patterns

• Dermatologic toxicity monitoring

• Cardiovascular safety assessment

• Dose modification analysis

See also

toxicityprofile, toxicityprofile_datasets

Examples

if (FALSE) { # \dontrun{
# Load the dataset
data(toxicityprofile_targeted_therapy)

# Targeted therapy toxicity profile
result <- toxicityprofile(
  data = toxicityprofile_targeted_therapy,
  patientID = "patient_id",
  adverseEvent = "adverse_event",
  grade = "toxicity_grade",
  treatment = "treatment_group",
  plotType = "stacked_bar",
  sortBy = "frequency"
)

# Dermatologic toxicity focus
dermatologic_data <- subset(toxicityprofile_targeted_therapy, 
                           system_organ_class == "Skin and subcutaneous tissue disorders")
result_derm <- toxicityprofile(
  data = dermatologic_data,
  patientID = "patient_id",
  adverseEvent = "adverse_event",
  grade = "toxicity_grade",
  plotType = "dot_plot",
  showConfidenceIntervals = TRUE
)

# Early onset pattern analysis
result_timing <- toxicityprofile(
  data = toxicityprofile_targeted_therapy,
  patientID = "patient_id",
  adverseEvent = "adverse_event",
  grade = "toxicity_grade",
  timeToEvent = "time_to_event",
  plotType = "time_to_event"
)
} # }