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Cardiovascular Risk Prediction Test Dataset

Source: R/data_timeroc_docs.R
timeroc_cardiovascular_risk.Rd

Simulated cardiovascular risk prediction study with multiple biomarkers and clinical risk factors. Designed to test time-dependent ROC analysis in the context of cardiovascular event prediction.

Usage

timeroc_cardiovascular_risk

Format

A data frame with 400 observations and 12 variables:

patient_id

Character. Unique patient identifier (CV_0001 to CV_0400)

age

Integer. Patient age (30-85 years)

sex

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

diabetes

Integer. Diabetes status (1 = yes, 0 = no)

hypertension

Integer. Hypertension status (1 = yes, 0 = no)

smoking_status

Integer. Smoking status (1 = current smoker, 0 = not)

troponin_level

Numeric. Troponin biomarker level (log-normal distribution)

crp_level

Numeric. C-reactive protein level (log-normal distribution)

risk_score

Numeric. Composite cardiovascular risk score

follow_up_months

Numeric. Follow-up time in months (0-36)

cv_event

Integer. Cardiovascular event indicator (1 = event, 0 = censored)

event_type

Character. Type of cardiovascular event ("MI", "Stroke", "CHF", "Death", "None")

study_site

Character. Study recruitment site ("Site_A" to "Site_D")

Source

Simulated data generated using create_timeroc_test_data.R

Details

This dataset represents a prospective cardiovascular risk study with 36-month follow-up. The dataset includes traditional risk factors (age, sex, diabetes, hypertension, smoking) and novel biomarkers (troponin, CRP). The composite risk score combines all risk factors.

Key Features:

  • Multiple biomarker comparison capability

  • Traditional + novel risk factors

  • Realistic biomarker distributions (log-normal)

  • 375/400 events (93.8% event rate)

  • Multi-site study design

Recommended TimeROC Parameters:

  • Timepoints: 6, 18, 36 months

  • Markers: troponin_level, crp_level, risk_score

  • Event: cv_event

  • Time: follow_up_months

See also

timeroc, timeroc_datasets

Examples

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

# Compare multiple biomarkers
troponin_roc <- timeroc(
  data = timeroc_cardiovascular_risk,
  elapsedtime = "follow_up_months",
  outcome = "cv_event",
  marker = "troponin_level",
  timepoints = "6, 18, 36"
)

risk_score_roc <- timeroc(
  data = timeroc_cardiovascular_risk,
  elapsedtime = "follow_up_months", 
  outcome = "cv_event",
  marker = "risk_score",
  timepoints = "6, 18, 36"
)
} # }