fit_ends_mods_spl {psm3mkv}

Fit multiple spline regressions to the multiple required endpoints

Description

Fits multiple survival regressions, according to the distributions stipulated, to the multiple endpoints required in fitting partitioned survival analysis, clock forward and clock reset semi-markov models.

Usage

fit_ends_mods_spl(
  simdat,
  knot_set = 1:3,
  scale_set = c("hazard", "odds", "normal"),
  expvar = NA
)

Arguments

simdat

Dataset of patient level data. Must be a tibble with columns named:

• ptid: patient identifier

• pfs.durn: duration of PFS from baseline

• pfs.flag: event flag for PFS (=1 if progression or death occurred, 0 for censoring)

• os.durn: duration of OS from baseline

• os.flag: event flag for OS (=1 if death occurred, 0 for censoring)

• ttp.durn: duration of TTP from baseline (usually should be equal to pfs.durn)

• ttp.flag: event flag for TTP (=1 if progression occurred, 0 for censoring).

Survival data for all other endpoints (time to progression, pre-progression death, post-progression survival) are derived from PFS and OS.

knot_set

is a vector of the numbers of knots to consider, following flexsurv::flexsurvspline()).

scale_set

is a vector of the spline scales to consider, following flexsurv::flexsurvspline()).

expvar

Explanatory variable for modeling of PPS

Value

A list by endpoint, then distribution, each containing two components:

• result: A list of class flexsurv::flexsurvspline containing information about the fitted model.

• error: Any error message returned on fitting the regression (NULL indicates no error). Also, the given cuttime.

See Also

Parametric modeling is handled by fit_ends_mods_par()

Examples

# Create dataset in suitable form using bos dataset from the flexsurv package
bosonc <- create_dummydata("flexbosms")
fit_ends_mods_spl(bosonc, expvar=bosonc$ttp.durn)