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Landmark Biomarker Analysis Test Dataset

Source: R/data_timeroc_docs.R
timeroc_landmark_biomarker.Rd

Specialized dataset for landmark time-dependent ROC analysis where biomarker values change over time. All patients survive to a landmark time (6 months) and subsequent analysis is conditional on landmark survival.

Usage

timeroc_landmark_biomarker

Format

A data frame with 200 observations and 10 variables:

patient_id

Character. Unique patient identifier (LM_001 to LM_200)

age

Integer. Patient age

baseline_biomarker

Numeric. Biomarker level at study entry

month6_biomarker

Numeric. Biomarker level at 6-month landmark

biomarker_change

Numeric. Log-ratio change from baseline to 6 months

total_follow_up_months

Numeric. Total follow-up time from baseline (6-60 months)

landmark_eligible

Logical. All TRUE (all patients survived to landmark)

post_landmark_event

Integer. Event after landmark time (1 = event, 0 = censored)

response_status

Character. Treatment response ("Complete", "Partial", "Stable", "Progressive")

treatment_arm

Character. Treatment assignment ("Experimental", "Standard")

Source

Simulated data generated using create_timeroc_test_data.R

Details

This dataset supports landmark analysis methodology where time-dependent biomarker values are assessed at a fixed landmark time (6 months) and used to predict subsequent events. This approach is common in oncology and transplantation studies.

Key Features:

  • All patients survive to landmark time (6 months)

  • Time-varying biomarker measurements

  • Biomarker change calculations (log-ratio)

  • Treatment response classifications

  • 48/200 post-landmark events (24% event rate)

  • Randomized treatment arms

Recommended TimeROC Parameters:

  • Timepoints: 12, 24, 36 months (from baseline)

  • Markers: month6_biomarker, biomarker_change

  • Event: post_landmark_event

  • Time: total_follow_up_months

See also

timeroc, timeroc_datasets

Examples

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

# Landmark analysis using 6-month biomarker value
landmark_roc <- timeroc(
  data = timeroc_landmark_biomarker,
  elapsedtime = "total_follow_up_months",
  outcome = "post_landmark_event", 
  marker = "month6_biomarker",
  timepoints = "12, 24, 36"
)

# Analysis of biomarker change
change_roc <- timeroc(
  data = timeroc_landmark_biomarker,
  elapsedtime = "total_follow_up_months",
  outcome = "post_landmark_event",
  marker = "biomarker_change", 
  timepoints = "12, 24, 36"
)
} # }