Create a model for simulating health state transitions with a continuous time state transition model (CTSTM).
create_transmod(params, data)
| params | A "params_surv" object returned from
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|---|---|
| data | A data table of class "expanded_hesim_data" returned from
|
An object of class "IndivCtstmTrans" from the hesim package.
# Treatment sequences txseq1 <- txseq(first = "erlotinib", second = c("osimertinib", "PBDC"), second_plus = c("PBDC + bevacizumab", "PBDC + bevacizumab")) txseq2 <- txseq(first = "gefitinib", second = c("osimertinib", "PBDC"), second_plus = c("PBDC + bevacizumab", "PBDC + bevacizumab")) txseqs <- txseq_list(seq1 = txseq1, seq2 = txseq2) # Patient population pats <- create_patients(n = 2) # Model structure struct <- model_structure(txseqs, dist = "weibull") tmat <- create_trans_mat(struct) # Data for state transition model transmod_data <- create_transmod_data(struct, tmat, pats) head(transmod_data)#> strategy_id patient_id transition_id female age mutation tx_abb tx_hist #> 1: 1 1 1 0 54.03749 1 erl <NA> #> 2: 1 1 2 0 54.03749 1 erl <NA> #> 3: 1 1 3 0 54.03749 1 osi erl #> 4: 1 1 4 0 54.03749 1 osi erl #> 5: 1 1 5 0 54.03749 1 osi erl #> 6: 1 2 1 0 73.37210 1 erl <NA> #> gef_s1p1_a0 gef_s1d_a0 d_erl_s1p1_a0 d_erl_s1d_a0 osi_s2p2_a0 osi_s2d_a0 #> 1: 1 0 1 0 0 0 #> 2: 0 1 0 1 0 0 #> 3: 0 0 0 0 1 0 #> 4: 0 0 0 0 0 1 #> 5: 0 0 0 0 0 0 #> 6: 1 0 1 0 0 0 #> osi_p2d_a0 pbdc_s2p2_a0 pbdc_s2d_a0 pbdc_p2d_a0 gef_s1p1_a1 gef_s1d_a1 #> 1: 0 0 0 0 1 0 #> 2: 0 0 0 0 0 1 #> 3: 0 0 0 0 0 0 #> 4: 0 0 0 0 0 0 #> 5: 1 0 0 0 0 0 #> 6: 0 0 0 0 1 0 #> d_erl_s1p1_a1 d_erl_s1d_a1 osi_s2p2_a1 osi_s2d_a1 osi_p2d_a1 pbdc_s2p2_a1 #> 1: 1 0 0 0 0 0 #> 2: 0 1 0 0 0 0 #> 3: 0 0 1 0 0 0 #> 4: 0 0 0 1 0 0 #> 5: 0 0 0 0 1 0 #> 6: 1 0 0 0 0 0 #> pbdc_s2d_a1 pbdc_p2d_a1 #> 1: 0 0 #> 2: 0 0 #> 3: 0 0 #> 4: 0 0 #> 5: 0 0 #> 6: 0 0# Parameters for state transition model transmod_params <- create_transmod_params(n = 2, transmod_data) print(transmod_params)#> $coefs #> $coefs$a0 #> d_erl_s1p1_a0 d_erl_s1d_a0 gef_s1p1_a0 gef_s1d_a0 osi_s2p2_a0 osi_s2d_a0 #> [1,] -0.1695568 0 -3.850149 -9.513523 -2.657322 -12.071691 #> [2,] -0.3158846 0 -3.873477 -6.987298 -3.223167 -6.953787 #> osi_p2d_a0 pbdc_s2p2_a0 pbdc_s2d_a0 pbdc_p2d_a0 #> [1,] -4.661446 -2.357226 -9.544715 -2.363616 #> [2,] -4.404432 -2.387992 -10.769347 -2.011830 #> #> $coefs$a1 #> d_erl_s1p1_a1 d_erl_s1d_a1 gef_s1p1_a1 gef_s1d_a1 osi_s2p2_a1 osi_s2d_a1 #> [1,] -0.2123671 0 0.7227243 0 0.1572655 0 #> [2,] -0.3730880 0 0.6407160 0 0.4505773 0 #> osi_p2d_a1 pbdc_s2p2_a1 pbdc_s2d_a1 pbdc_p2d_a1 #> [1,] 0.4244667 0.4645846 0 -0.1588428 #> [2,] 0.3126212 0.3641004 0 -0.3788891 #> #> #> $dist #> [1] "weibullNMA" #> #> $n_samples #> [1] 2 #> #> attr(,"class") #> [1] "params_surv"# State transition model transmod <- create_transmod(transmod_params, transmod_data)