calc_futime: Calculate follow-up time per case until end of follow-up...
In marianschmidt/msSPChelpR: Helper Functions for Second Primary Cancer Analyses

calc_futime

R Documentation

Calculate follow-up time per case until end of follow-up depending on pat_status - tidyverse version

Description

Calculate follow-up time per case until end of follow-up depending on pat_status - tidyverse version

Usage

calc_futime(
  wide_df,
  futime_var_new = "p_futimeyrs",
  fu_end,
  dattype = NULL,
  check = TRUE,
  time_unit = "years",
  status_var = "p_status",
  lifedat_var = NULL,
  fcdat_var = NULL,
  spcdat_var = NULL,
  quiet = FALSE
)

Arguments

`wide_df`	dataframe in wide format
`futime_var_new`	Name of the newly calculated variable for follow-up time. Default is p_futimeyrs.
`fu_end`	end of follow-up in time format YYYY-MM-DD.
`dattype`	can be "zfkd" or "seer" or NULL. Will set default variable names if dattype is "seer" or "zfkd". Default is NULL.
`check`	Check newly calculated variable p_status by printing frequency table. Default is TRUE.
`time_unit`	Unit of follow-up time (can be "days", "weeks", "months", "years"). Default is "years".
`status_var`	Name of the patient status variable that was previously created. Default is p_status.
`lifedat_var`	Name of variable containing Date of Death. Will override dattype preset.
`fcdat_var`	Name of variable containing Date of Primary Cancer diagnosis. Will override dattype preset.
`spcdat_var`	Name of variable containing Date of SPC diagnosis Will override dattype preset.
`quiet`	If TRUE, warnings and messages will be suppressed. Default is FALSE.

Value

wide_df

Examples

#load sample data
data("us_second_cancer")

#prep step - make wide data as this is the required format
usdata_wide <- us_second_cancer %>%
                    msSPChelpR::reshape_wide_tidyr(case_id_var = "fake_id", 
                    time_id_var = "SEQ_NUM", timevar_max = 10)
                    
#prep step - calculate p_spc variable
usdata_wide <- usdata_wide %>%
                 dplyr::mutate(p_spc = dplyr::case_when(is.na(t_site_icd.2)   ~ "No SPC",
                                                       !is.na(t_site_icd.2)   ~ "SPC developed",
                                                       TRUE ~ NA_character_)) %>%
                 dplyr::mutate(count_spc = dplyr::case_when(is.na(t_site_icd.2)   ~ 1,
                                                              TRUE ~ 0))
                                                              
#prep step - create patient status variable
usdata_wide <- usdata_wide %>%
                  msSPChelpR::pat_status(., fu_end = "2017-12-31", dattype = "seer",
                                         status_var = "p_status", life_var = "p_alive.1",
                                         birthdat_var = "datebirth.1", lifedat_var = "datedeath.1")
 
#now we can run the function
msSPChelpR::calc_futime(usdata_wide, 
                        futime_var_new = "p_futimeyrs", 
                        fu_end = "2017-12-31",
                        dattype = "seer", 
                        time_unit = "years",
                        status_var = "p_status",
                        lifedat_var = "datedeath.1", 
                        fcdat_var = "t_datediag.1", 
                        spcdat_var = "t_datediag.2")

marianschmidt/msSPChelpR documentation built on Feb. 1, 2024, 6:45 a.m.