Select model structures

Source: R/model-structures.R

Select the model structures to use in the IVI-RA individual patient simulation.

select_model_structures(tx_ihaq = "acr-haq", tx_iswitch = "acr-switch",
  cdmards_haq_model = "lcgm", ttd_cause = "all",
  ttd_dist = "exponential", utility_model = "mixture")

Arguments

tx_ihaq

Model structure relating treatment to HAQ during the first 6 months of treatment. Options, which are equivalent to H1-H3 in the documentation are:

  • acr-haq H1: Treatment -> ACR -> HAQ

  • acr-eular-haq H2: Treatment -> ACR -> EULAR -> HAQ

  • haq H3:Treatment -> HAQ
tx_iswitch

Model structure relating treatment to switching during the first 6 months of treatment. Options, which are equivalent to S1-S6 in the documentation are:

  • acr-switch S1: Treatment -> ACR -> Switch

  • acr-das28-switch S2: Treatment -> ACR -> DAS28 -> Switch

  • acr-sdai-switch S3: Treatment -> ACR -> SDAI -> Switch

  • acr-cdai-switch S4: Treatment -> ACR -> CDAI -> Switch

  • das28-switch S5: Treatment -> DAS28 -> Switch

  • acr-eular-switch S6: Treatment -> ACR -> EULAR -> Switch
cdmards_haq_model

Model used for long-term HAQ progression. Options are:

  • lcgm Latent class growth model

  • linear Constant linear HAQ progression

If lgcm is chosen, then a latent class growth model is used for cDMARDs and NBT but a constant annual rate is is assumed for all other therapies; otherwise a constant linear HAQ progression is assumed for all therapies including cDMARDs and NBT.
ttd_cause

Cause of treatment discontinuation. Options are:

  • all Treatment discontinuation due to any cause.

  • si Treatment discontinuation due to serious infections
ttd_dist

Distribution used to model time to treatment discontinuaton. Options are:

  • exponential Exponential

  • weibull Weibull

  • gompertz Gompertz

  • gamma Gamma

  • llogis Log-logistic

  • lnorm Lognormal

  • gengamma Generalized gamma
utility_model

Model used to estimate patient utility as a function of HAQ and patient characteristics. Options are:

  • mixture Hernandez Alava (2013) mixutre model

  • wailoo Wailoo 2006 logistc regression

Examples

mod.structs <- select_model_structures(tx_ihaq = c("acr-haq", "acr-eular-haq"),
                                      tx_iswitch = c("acr-switch", "acr-eular-switch"),
                                      cdmards_haq_model = c("lcgm", "linear"),
                                      ttd_cause = c("all", "si"),
                                      ttd_dist = c("gengamma", "exponential"),
                                      utility_model = c("mixture", "wailoo"))
print(mod.structs)
#>      tx_ihaq         tx_iswitch         cdmards_haq_model ttd_cause
#> [1,] "acr-haq"       "acr-switch"       "lcgm"            "all"    
#> [2,] "acr-eular-haq" "acr-eular-switch" "linear"          "si"     
#>      ttd_dist      utility_model
#> [1,] "gengamma"    "mixture"    
#> [2,] "exponential" "wailoo"     
#> attr(,"class")
#> [1] "model_structures"