fillPatientTables: Load dataframes from four patient data files generated in the...

In jbindman/prostate-project: Prostate Cancer Outcome Predictor

Description

Load dataframes from four patient data files generated in the course of Active Surveillance in order to create a list of formatted patient dataframes for analysis. See vignette for required variable names and format.

Usage

fillPatientTables(demo.data, psa.data, bx.data, surg.data, IOP = TRUE)

Arguments

demo.data	Patient-level data. This dataframe should contain one record (row) per patient. Variables (columns) must include a unique identifier (ID) and valid date of birth for each patient.
psa.data	PSA data. This dataframe should contain one record per PSA test (per patient). Variables must include patient ID, date of test, and total PSA observed.
bx.data	Biopsy data. This dataframe should contain one record per biopsy (per patient). Variables must include patient ID, date of biopsy, indicator of grade reclassication, and prostate volume (if assessed).
surg.data	Surgery data. This dataframe should contain one record per surgery performed. Variables must include patient ID, surgery date, and Gleason score (GS) assessed on entire specimen.
IOP	TRUE if biopsy and surgery occurences are informative of the underlying GS, FALSE if non-informative.

Value

List of three dataframes for analysis: pt.data, psa.data, bx.full. See vignette for examples.

jbindman/prostate-project documentation built on May 18, 2019, 5:59 p.m.