## ---- echo=FALSE, include=FALSE------------------------------------------
library(heRomod)
## ------------------------------------------------------------------------
param <- define_parameters(
rr = .509,
p_AA_mono = .721,
p_AB_mono = .202,
p_AC_mono = .067,
p_AD_mono = .010,
p_BC_mono = .407,
p_BD_mono = .012,
p_CD_mono = .250,
p_AB_comb = p_AB_mono * rr,
p_AC_comb = p_AC_mono * rr,
p_AD_comb = p_AD_mono * rr,
p_BC_comb = p_BC_mono * rr,
p_BD_comb = p_BD_mono * rr,
p_CD_comb = p_CD_mono * rr,
p_AA_comb = 1 - (p_AB_comb + p_AC_comb + p_AD_comb),
cost_zido = 2278,
cost_lami = 2086,
cost_A = 2756,
cost_B = 3052,
cost_C = 9007
)
## ------------------------------------------------------------------------
mat_trans_mono <- define_transition(
p_AA_mono, p_AB_mono, p_AC_mono, p_AD_mono,
0, C, p_BC_mono, p_BD_mono,
0, 0, C, p_CD_mono,
0, 0, 0, 1
)
mat_trans_comb <- define_transition(
p_AA_comb, p_AB_comb, p_AC_comb, p_AD_comb,
0, C, p_BC_comb, p_BD_comb,
0, 0, C, p_CD_comb,
0, 0, 0, 1
)
## ------------------------------------------------------------------------
state_A <- define_state(
cost_health = 2756,
cost_drugs = dispatch_strategy(
mono = cost_zido,
comb = cost_zido + cost_lami
),
cost_total = discount(cost_health + cost_drugs, .06),
life_year = 1
)
state_B <- define_state(
cost_health = 3052,
cost_drugs = dispatch_strategy(
mono = cost_zido,
comb = cost_zido + cost_lami
),
cost_total = discount(cost_health + cost_drugs, .06),
life_year = 1
)
state_C <- define_state(
cost_health = 9007,
cost_drugs = dispatch_strategy(
mono = cost_zido,
comb = cost_zido + cost_lami
),
cost_total = discount(cost_health + cost_drugs, .06),
life_year = 1
)
state_D <- define_state(
cost_health = 0,
cost_drugs = 0,
cost_total = discount(cost_health + cost_drugs, .06),
life_year = 0
)
## ------------------------------------------------------------------------
strat_mono <- define_strategy(
transition = mat_trans_mono,
state_A,
state_B,
state_C,
state_D
)
strat_comb <- define_strategy(
transition = mat_trans_comb,
state_A,
state_B,
state_C,
state_D
)
res_mod <- run_model(
mono = strat_mono,
comb = strat_comb,
parameters = param,
cycles = 50,
cost = cost_total,
effect = life_year
)
## ------------------------------------------------------------------------
rsp <- define_psa(
rr ~ lognormal(mean = .509, sdlog = .173),
cost_A ~ gamma(mean = 2756, sd = sqrt(2756)),
cost_B ~ gamma(mean = 3052, sd = sqrt(3052)),
cost_C ~ gamma(mean = 9007, sd = sqrt(9007)),
p_CD_mono ~ binomial(prob = .25, size = 40)
)
## ------------------------------------------------------------------------
pm <- run_psa(
model = res_mod,
psa = rsp,
N = 100
)
## ------------------------------------------------------------------------
summary(
pm,
threshold = c(1000, 5000, 6000, 1e4))
## ---- fig.width = 6, fig.height=4, fig.align='center'--------------------
plot(pm, type = "ce")
## ---- fig.width = 6, fig.align='center'----------------------------------
plot(pm, type = "ac", max_wtp = 10000, log_scale = FALSE)
plot(pm, type = "evpi", max_wtp = 10000, log_scale = FALSE)
## ---- fig.width = 6, fig.height = 4, fig.align='center'------------------
plot(pm, type = "cov")
## ---- fig.width = 4, fig.height = 4, fig.align='center'------------------
plot(pm, type = "cov", diff = TRUE, threshold = 5000)
## ---- fig.align='center', fig.height=4, fig.width=6, message=FALSE-------
library(ggplot2)
plot(pm, type = "ce") +
xlab("Life-years gained") +
ylab("Additional cost") +
scale_color_brewer(
name = "Strategy",
palette = "Set1"
) +
theme_minimal()
## ---- fig.height=6, fig.width=6------------------------------------------
bcea <- run_bcea(pm, plot = TRUE, Kmax = 10000)
summary(bcea)
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