Description

Hormone Sensitive

Treatment and biomarkers

3 active treatments: ARSi, Taxane_CT, PARPi
5 biomarker signatures: all, TP53-, TP53+, HRD+, TEfus+
8 biomarker subgroup combinations: —, –+, -+-, -++, +–, +-+, ++-, +++


Prevelance of subgroup combinations

HRD TP53 TEfus subtypes prev all TP53- TP53+ HRD+ TEfus+
0 0 0 — 0.30 1 1 0 0 0
0 0 1 –+ 0.09 1 1 0 0 1
0 1 0 -+- 0.19 1 0 1 0 0
0 1 1 -++ 0.14 1 0 1 0 1
1 0 0 +– 0.08 1 1 0 1 0
1 0 1 +-+ 0.08 1 1 0 1 1
1 1 0 ++- 0.06 1 0 1 1 0
1 1 1 +++ 0.06 1 0 1 1 1


Prevelance of biomarker signatures
signatures — –+ -+- -++ +– +-+ ++- +++ prev
all X X X X X X X X 1
TP53- X X X X 0.55
TP53+ X X X X 0.45
HRD+ X X X X 0.28
TEfus+ X X X X 0.37 


NULL


Enrollment parameters

Enrollment and evaluation period: 60 months
Accrual rate: 30 patients/month
Standard-of-care (% treatment received): Other = 0.3; ARSi = 0.35; Taxane_CT = 0.35


Initial randomization probabilities:
Control ARSi Taxane_CT PARPi
— 0.37 0.37 0.25 0.00
–+ 0.38 0.19 0.38 0.06
-+- 0.41 0.18 0.41 0.00
-++ 0.41 0.12 0.41 0.06
+– 0.50 0.00 0.00 0.50
+-+ 0.50 0.00 0.00 0.50
++- 0.50 0.00 0.00 0.50
+++ 0.50 0.00 0.00 0.50
Control ARSi Taxane_CT PARPi
all 0.45 0.11 0.18 0.27
TP53- 0.44 0.14 0.16 0.27
TP53+ 0.46 0.07 0.21 0.26
HRD+ 0.50 0.00 0.00 0.50
TEfus+ 0.45 0.08 0.20 0.28


Stopping rules

label value type description
nupdate 50.00 Evaluation Number of patients that need to be enrolled in the active arms before updating randomization probabilities
nval 50.00 Evaluation Number of patients in a biomarker signature that need to be randomized to a treatment before if it gets evaluated for graduation
nmin 10.00 Evaluation Same as before but for futility
nmin2 10.00 Evaluation Minimum number of patients in the subgroup combinations for evaluation (otherwise manual inspection from DSMB)
nmax 300.00 Stop nmax Maximum number of patients for treatment-signature combination
pU 0.85 Graduation Threshold for probability of superiority (graduation) in a treatment-signature combination
pU2 0.70 Graduation Threshold for probability of superiority (graduation) in a treatment-subgroup combination
pU2n 0.60 Graduation Same as before, if treatment-subgroup combinations have lower sample size (nmin2)
pU2all 0.55 Graduation Threshold for treatment-subgroup combinations (graduation) in the signature all
pL 0.30 Futility Threshold for probability of superiority (futility) in a treatment-signature combination
pL2 0.50 Futility Threshold for probability of superiority (futility) in a treatment-subgroup combination
pL2n 0.50 Futility Same as before, if treatment-subgroup combinations have lower sample size (nmin2)
pU2all 0.55 Futility Threshold for treatment-subgroup combinations (futility) in the signature all


Priors and hyperparameters

  • PFS is assumed to follow a Weibull distribution (shape, scale);

  • PFS times were simulated from a Weibull distribution with shape = 1.3 and different possible values for the scale parameter (assumed treatment effect in the simulation scenarios);

  • The survival models are parametrized as accelerated failure time models;

  • The scale parameters are assumed to be linearly dependent on the treatment covariates;

  • The following priors are adopted:

    • treatment covariates: normal (0, 0.5)
    • intercept term: normal (4, 1)
    • shape parameter: exponential (1)

  • MCMC algorithm were implemented with 1 chain, 1000 of which 200 were used as warm-up.

Castration Resistent

Treatment and biomarkers

4 active treatments: ARSi, Taxane_CT, Platinum_CT, PARPi
5 biomarker signatures: all, TP53- & AR-, TP53+, HRD+, TEfus+
16 biomarker subgroup combinations: —-, —+, –+-, –++, -+–, -+-+, -++-, -+++, +—, +–+, +-+-, +-++, ++–, ++-+, +++-, ++++


Prevelance of subgroup combinations

ARA HRD TP53 TEfus subtypes prev all TP53- & AR- TP53+ HRD+ TEfus+
0 0 0 0 —- 0.25 1 1 0 0 0
0 0 0 1 —+ 0.05 1 1 0 0 1
0 0 1 0 –+- 0.15 1 0 1 0 0
0 0 1 1 –++ 0.10 1 0 1 0 1
0 1 0 0 -+– 0.05 1 1 0 1 0
0 1 0 1 -+-+ 0.05 1 1 0 1 1
0 1 1 0 -++- 0.03 1 0 1 1 0
0 1 1 1 -+++ 0.03 1 0 1 1 1
1 0 0 0 +— 0.05 1 0 0 0 0
1 0 0 1 +–+ 0.04 1 0 0 0 1
1 0 1 0 +-+- 0.04 1 0 1 0 0
1 0 1 1 +-++ 0.04 1 0 1 0 1
1 1 0 0 ++– 0.03 1 0 0 1 0
1 1 0 1 ++-+ 0.03 1 0 0 1 1
1 1 1 0 +++- 0.03 1 0 1 1 0
1 1 1 1 ++++ 0.03 1 0 1 1 1


Prevelance of biomarker signatures
signatures —- —+ –+- –++ -+– -+-+ -++- -+++ +— +–+ +-+- +-++ ++– ++-+ +++- ++++ prev
all X X X X X X X X X X X X X X X X 1
TP53- & AR- X X X X 0.4
TP53+ X X X X X X X X 0.45
HRD+ X X X X X X X X 0.28
TEfus+ X X X X X X X X 0.37 


NULL


Enrollment parameters

Enrollment and evaluation period: 36 months
Accrual rate: 30 patients/month
Standard-of-care (% treatment received): Other = 0.25; ARSi = 0.4; Taxane_CT = 0.35


Initial randomization probabilities:
Control ARSi Taxane_CT Platinum_CT PARPi
—- 0.44 0.44 0.11 0.00 0.00
—+ 0.35 0.35 0.29 0.00 0.00
–+- 0.33 0.33 0.17 0.08 0.08
–++ 0.41 0.18 0.41 0.00 0.00
-+– 0.33 0.00 0.00 0.33 0.33
-+-+ 0.33 0.00 0.00 0.33 0.33
-++- 0.33 0.00 0.00 0.33 0.33
-+++ 0.33 0.00 0.00 0.33 0.33
+— 0.41 0.18 0.41 0.00 0.00
+–+ 0.41 0.18 0.41 0.00 0.00
+-+- 0.37 0.12 0.37 0.06 0.06
+-++ 0.37 0.12 0.37 0.06 0.06
++– 0.33 0.00 0.00 0.33 0.33
++-+ 0.33 0.00 0.00 0.33 0.33
+++- 0.33 0.00 0.00 0.33 0.33
++++ 0.33 0.00 0.00 0.33 0.33
Control ARSi Taxane_CT Platinum_CT PARPi
all 0.36 0.12 0.16 0.18 0.18
TP53- & AR- 0.37 0.20 0.10 0.17 0.17
TP53+ 0.35 0.09 0.17 0.19 0.19
HRD+ 0.33 0.00 0.00 0.33 0.33
TEfus+ 0.36 0.10 0.19 0.17 0.17


Stopping rules

label value type description
nupdate 50.00 Evaluation Number of patients that need to be enrolled in the active arms before updating randomization probabilities
nval 25.00 Evaluation Number of patients in a biomarker signature that need to be randomized to a treatment before if it gets evaluated for graduation
nmin 5.00 Evaluation Same as before but for futility
nmin2 5.00 Evaluation Minimum number of patients in the subgroup combinations for evaluation (otherwise manual inspection from DSMB)
nmax 150.00 Stop nmax Maximum number of patients for treatment-signature combination
pU 0.85 Graduation Threshold for probability of superiority (graduation) in a treatment-signature combination
pU2 0.70 Graduation Threshold for probability of superiority (graduation) in a treatment-subgroup combination
pU2n 0.50 Graduation Same as before, if treatment-subgroup combinations have lower sample size (nmin2)
pU2all 0.50 Graduation Threshold for treatment-subgroup combinations (graduation) in the signature all
pL 0.30 Futility Threshold for probability of superiority (futility) in a treatment-signature combination
pL2 0.50 Futility Threshold for probability of superiority (futility) in a treatment-subgroup combination
pL2n 0.50 Futility Same as before, if treatment-subgroup combinations have lower sample size (nmin2)
pU2all 0.50 Futility Threshold for treatment-subgroup combinations (futility) in the signature all


Priors and hyperparameters

  • PFS is assumed to follow a Weibull distribution (shape, scale);

  • PFS times were simulated from a Weibull distribution with shape = 1.05 and different possible values for the scale parameter (assumed treatment effect in the simulation scenarios);

  • The survival models are parametrized as accelerated failure time models;

  • The scale parameters are assumed to be linearly dependent on the treatment covariates;

  • The following priors are adopted:

    • treatment covariates: normal (0, 0.5)
    • intercept term: normal (3, 1)
    • shape parameter: exponential (1)

  • MCMC algorithm were implemented with 1 chain, 1000 of which 200 were used as warm-up.