tabletools: Helpful Tools to Make html Tables

Documented in compare_mgfr_plot compare_mgfr_summary

#' Compare Iohexol mGFR results using available methods
#'
#' Two functions are provided to to summarize available options and analyze
#' outlier or inconsistent results. Most variation occurs due to poor fitting or
#' variability in early timepoints (<90min), although the late time points
#' account for ~90% of the measured AUC used in calculation of creatinine
#' clearance. Further discussion and details regarding methods of fitting the
#' 2-compartment models can be found at
#' \href{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8101203/}{Pottel et al.}
#' The summary provides estimates of kinetic parameters (k10, k21, k12) which
#' can be used in ODE models, but is not implemented here.
#'
#' @inheritParams calculate_mgfr_2c
#' @param mfr Plot layout. defaults to c(2,3) for 2 rows, 3 columns
#' @param ... Inherits from named `calculate_mgfr_2c` paramaters. Any arguments
#'   can be added, but must be named (eg `ioh_inj_vol = 5.1`).
#' @rdname compare_mgfr_summary
#' @importFrom purrr pmap_df
#'
#' @return `compare_mgfr_summary()` Returns a table of mGFR summary parameters,
#'   and `compare_mgfr_plot()` returns a panel of plots using a combination of available methods.
#'   The single sample method result is not included but can be called
#'   separately using `calculate_mgfr_ss`. '
#' @export compare_mgfr_summary
#' @examples
#' library(tabletools)
#' # PUBLISHED IOHEXOL DATA ----
#' # data available in package by calling
#' ## ├ Schwartz Data ----
#' # Data extracted from Schwartz Fig1 https://pubmed.ncbi.nlm.nih.gov/16612328/
#' # Iohexol 5mL IV injection (Omnipaque 300, 5mL ~3235mg Iohexol)
#' # sampling at 10, 20, 30, 60, 120, 240, 300, 360 min
#' # time (minutes)
#' # Iohexol (ug/ml)
#' # age, height, weight not known for the example
#' dat_schwartz
#'
#' ## ├ Pottel data ----
#' # from Supplemental document in https://pubmed.ncbi.nlm.nih.gov/33952185/
#' dat10
#' dat17
#'
#' ## ├ Tondel data ----
#' # full example data provided by Tondel in Table 2: https://pubmed.ncbi.nlm.nih.gov/29134449/
#' dat_tondel
#'
#' compare_mgfr_summary(dat_tondel$time, dat_tondel$iohexol, ioh_inj_vol = 2.08, weight = 13, height = 0.9)
#' compare_mgfr_plot(dat_tondel$time, dat_tondel$iohexol, ioh_inj_vol = 2.08, weight = 13, height = 0.9, id="dat_tondel")
#'
#' # Comparisons of available methods: published studies
#' # Schwartz data in kids; note don't have subject details (height, weight, inj_vol)
#' compare_mgfr_summary(dat_schwartz$time, dat_schwartz$iohexol_ug_ml, height = 0.8, weight = 13, ioh_inj_vol = 2.08)
#' compare_mgfr_plot(dat_schwartz$time, dat_schwartz$iohexol_ug_ml, height = 0.8, weight = 13, ioh_inj_vol = 2.08, id="dat_schwartz")
#'
#' # Pottel ID#10 Difficult fit
#' # Negative value using unconstrained parameters (NLLS-base-unweighted)
#' # caused by early outlier data points (t=60 most likely)
#' compare_mgfr_summary(dat10$time, dat10$iohexol, height = 1.67, weight = 70)
#' compare_mgfr_plot(dat10$time, dat10$iohexol, height = 1.67, weight = 70, id="dat10")
#'
#' # Pottel ID#17 Difficult fit
#' compare_mgfr_summary(dat17$time, dat17$iohexol, height = 1.67, weight = 70, id="dat17")
#' compare_mgfr_plot(dat17$time, dat17$iohexol, height = 1.67, weight = 70, id="dat17")
#'
#' # ODE MODEL FOR COMPARISON;
#' # Example only to verify ODE parameter estimates, not required for GFR calculation
#' # This model uses solution from the nls model to get the kinetic parameters
#' library(deSolve)
#' m2c <- function(Time, State, Pars) {
#'   with(as.list(c(State, Pars)), {
#'     dIohexol <- -k10*Iohexol - k12*Iohexol + k21*C2 # Central Conc
#'     dC2 <-  k12*Iohexol - k21*C2                    # Peripheral Conc
#'     return(list(c(dIohexol, dC2)))
#'   })
#' }
#' # get parameters from nls model
#' ioh_nlfit <- calculate_mgfr_2c(dat_schwartz$time, dat_schwartz$iohexol_ug_ml, height = 1.67, weight = 70, ioh_inj_vol = 5)
#' pars  <- c(k10 = ioh_nlfit$k10, k21 = ioh_nlfit$k21, k12 = ioh_nlfit$k12)
#' # plug into the ODE model solution
#' yini  <- c(Iohexol = ioh_nlfit$A+ioh_nlfit$B, C2=0)
#' times <- seq(0, 360, by = 1)
#' out   <- ode(yini, times, m2c, pars)
#' out_df <- as.data.frame(out)
#' # Plot to verfiy kinetic parameters vs nls model
#' calculate_mgfr_2c(dat_schwartz$time, dat_schwartz$iohexol_ug_ml, height = 1.67, weight = 70, ioh_inj_vol = 5, output="plot")
#' lines(out_df$time, out_df$Iohexol, lty=2)
#' 
compare_mgfr_summary  <- function(time, iohexol_conc, t_early=100, t_late=120,...) {
  nls_vs = list(nls_v       = c("gslnls", "gslnls","base", "base","SI", "SI",  "msp"),
                nls_weights = c(       T,        F,     T,      F,   F,    F,     F),
                t_early     = c(t_early, t_early, t_early, t_early, t_early, t_late, t_early),
                t_late      = rep(t_late, 7))
  # nls_vs = list(nls_v       = c("SI", "SI", "gslnls", "base", "gslnls", "base", "msp"),
  #               nls_weights = c(  T,   T,        T,      T,        F,      F,    F),
  #               t_early     = c(t_early, t_late, t_early, t_early, t_early, t_early, t_early),
  #               t_late      = rep(t_late, 7))
  pmap_df(nls_vs, calculate_mgfr_2c, time=time, iohexol_conc=iohexol_conc, output="summary",...) 
}

#' @rdname compare_mgfr_summary 
#' @inheritParams calculate_mgfr_2c
#' @export compare_mgfr_plot
compare_mgfr_plot  <- function(time, iohexol_conc, t_early=100, t_late=120, mfr=c(2,3),...) {
  nls_vs = list(nls_v       = c("gslnls", "gslnls","base", "base","SI", "msp"),
                nls_weights = c(       T,        F,     T,      F,   F,    F),
                t_early     = c(t_early, t_early, t_early, t_early, t_early, t_early),
                t_late      = rep(t_late, 6))
  old.mfrow = par("mfrow")
  par(mfrow = mfr)
  pmap(nls_vs, calculate_mgfr_2c, time=time, iohexol_conc=iohexol_conc, output="plot",...) 
  par("mfrow"=old.mfrow) 
}