Survival analysis and prognostic clustering using IHC markers. Designed for prognostic biomarker discovery and risk stratification.
Usage
ihcsurvival(
data,
markers,
survivalTime,
survivalEvent,
id = NULL,
prognosticClustering = TRUE,
multiRegionAnalysis = FALSE,
centralRegion,
invasiveRegion,
riskStratification = "tertiles",
coxRegression = TRUE,
multivariateAdjustment,
kaplanMeierPlots = TRUE,
landmarkAnalysis = FALSE,
landmarkTime = 60,
landmarkTimePoints = "12,24,36,48,60",
confidenceLevel = 0.95
)Arguments
- data
the data as a data frame
- markers
IHC marker variables for prognostic analysis
- survivalTime
Time to event variable (months, years, days)
- survivalEvent
Event indicator (1=event, 0=censored)
- id
Case identifier for tracking
- prognosticClustering
Perform clustering optimized for survival outcomes
- multiRegionAnalysis
Compare central vs invasive tumor regions
- centralRegion
IHC markers from central tumor region
- invasiveRegion
IHC markers from invasive tumor region
- riskStratification
Method for creating prognostic risk groups
- coxRegression
Perform Cox proportional hazards regression
- multivariateAdjustment
Clinical variables for multivariate adjustment
- kaplanMeierPlots
Generate survival curves for risk groups
- landmarkAnalysis
Perform landmark survival analysis at specific time points
- landmarkTime
Time point for landmark analysis (same units as survival time)
- landmarkTimePoints
Comma-separated time points for landmark survival analysis (e.g., "12,24,36")
- confidenceLevel
Confidence level for survival estimates and hazard ratios
Value
A results object containing:
results$instructions | a html | ||||
results$assumptions | a html | ||||
results$reportSentence | a html | ||||
results$prognosticGroups | a table | ||||
results$coxResults | a table | ||||
results$multivariateResults | a table | ||||
results$regionalComparison | a table | ||||
results$landmarkResults | a table | ||||
results$modelFit | a table | ||||
results$kaplanMeierPlot | an image | ||||
results$hazardPlot | an image | ||||
results$riskScorePlot | an image |
Tables can be converted to data frames with asDF or as.data.frame. For example:
results$prognosticGroups$asDF
as.data.frame(results$prognosticGroups)