Usage
pathologycomposition(
data,
outcome_variable,
component1,
component2,
component3,
component4,
composition_analysis = TRUE,
optimal_composition = TRUE,
trend_test = TRUE,
confidence_level = 0.95,
low_risk_threshold = 0.05,
high_risk_threshold = 0.2,
min_group_size = 10,
quantitative_categories = "gastric_cancer",
composition_plot = TRUE
)Arguments
- data
the data as a data frame
- outcome_variable
Clinical outcome variable for composition analysis
- component1
First histologic component (proportion or category)
- component2
Second histologic component (proportion or category)
- component3
Third histologic component (proportion or category)
- component4
Fourth histologic component (proportion or category)
- composition_analysis
Analyze risk based on component composition patterns
- optimal_composition
Identify optimal low-risk and high-risk composition patterns
- trend_test
Perform trend tests for dose-response relationships
- confidence_level
Confidence level for risk estimates and intervals
- low_risk_threshold
Maximum risk probability for low-risk classification (5\
high_risk_thresholdMinimum risk probability for high-risk classification (20\min_group_sizeMinimum number of cases required for composition pattern analysisquantitative_categoriesSemi-quantitative categorization system for componentscomposition_plotGenerate scatter plot of component composition vs risk A results object containing:
Tables can be converted to data frames withresults$instructionsa html results$componentanalysisa table results$compositionriska table results$optimalcompositionsa table results$compositionplotan image results$interpretationa html asDForas.data.frame. For example:results$componentanalysis$asDFas.data.frame(results$componentanalysis)Semi-quantitative analysis of histologic components and their association with clinical outcomes. Based on advanced pathology research methodologies, particularly gastric cancer composition analysis. Performs component risk assessment, composition pattern analysis, and optimal threshold identification. data('pathology_data')pathologycomposition(data = pathology_data, outcome_variable = lymph_node_metastasis, component1 = signet_ring_cells, component2 = poorly_differentiated, composition_analysis = TRUE)