PatientSample: A sample of patients to use in simulations.

In escalation: A Modular Approach to Dose-Finding Clinical Trials

A sample of patients to use in simulations.

Description

Class to house the latent random variables that govern toxicity and efficacy events in patients. Instances of this class can be used in simulation-like tasks to effectively use the same simulated individuals in different designs, thus supporting reduced Monte Carlo error and more efficient comparison.

Public fields

num_patients

('integer(1)')

tox_u

('numeric(num_patients)')

time_to_tox_func

('function')

tox_time

('numeric(num_patients)')

eff_u

('numeric(num_patients)')

time_to_eff_func

('function')

eff_time

('numeric(num_patients)')

can_grow

('logical(1)')

Methods

Public methods

• PatientSample$new()

• PatientSample$set_eff_and_tox()

• PatientSample$expand_to()

• PatientSample$get_tox_u()

• PatientSample$get_patient_tox()

• PatientSample$get_eff_u()

• PatientSample$get_patient_eff()

• PatientSample$clone()

---

Method new()

Creator.

Usage

PatientSample$new(
  num_patients = 0,
  time_to_tox_func = function() runif(n = 1),
  time_to_eff_func = function() runif(n = 1)
)

Arguments

num_patients

('integer(1)') Number of patients.

time_to_tox_func

('function') function taking no args that returns a single time of toxicity, given that toxicity occurs.

time_to_eff_func

('function') function taking no args that returns a single time of efficacy, given that efficacy occurs.

Returns

[PatientSample].

---

Method set_eff_and_tox()

Set the toxicity and efficacy latent variables that govern occurrence of toxicity and efficacy events. By default, instances of this class automatically grow these latent variables to accommodate arbitrarily high sample sizes. However, when you set these latent variables manually via this function, you override the ability of the class to self-manage, so its ability to grow is turned off by setting the internal variable self$can_grow <- FALSE.

Usage

PatientSample$set_eff_and_tox(
  tox_u,
  eff_u,
  tox_time = rep(0, length(tox_u)),
  eff_time = rep(0, length(eff_u))
)

Arguments

tox_u

('numeric()') Patient-level toxicity propensities.

eff_u

('numeric()') Patient-level efficacy propensities.

tox_time

('numeric()') Patient-level toxicity times, given that toxicity occurs.

eff_time

('numeric()') Patient-level efficacy times, given that efficacy occurs.

---

Method expand_to()

Expand sample to size at least num_patients

Usage

PatientSample$expand_to(num_patients)

Arguments

num_patients

('integer(1)').

---

Method get_tox_u()

Get toxicity latent variable for patient i

Usage

PatientSample$get_tox_u(i)

Arguments

i

('integer(1)') patient index

---

Method get_patient_tox()

Get 0 or 1 event marker for whether toxicity occurred in patient i

Usage

PatientSample$get_patient_tox(i, prob_tox, time = Inf)

Arguments

i

('integer(1)') patient index

prob_tox

('numeric(1)') probability of toxicity

time

('numeric(1)') at time

---

Method get_eff_u()

Get efficacy latent variable for patient i

Usage

PatientSample$get_eff_u(i)

Arguments

i

('integer(1)') patient index

---

Method get_patient_eff()

Get 0 or 1 event marker for whether efficacy occurred in patient i

Usage

PatientSample$get_patient_eff(i, prob_eff, time = Inf)

Arguments

i

('integer(1)') patient index

prob_eff

('numeric(1)') probability of efficacy

time

('numeric(1)') at time

---

Method clone()

The objects of this class are cloneable with this method.

Usage

PatientSample$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Sweeting, M., Slade, D., Jackson, D., & Brock, K. (2024). Potential outcome simulation for efficient head-to-head comparison of adaptive dose-finding designs. arXiv preprint arXiv:2402.15460

escalation documentation built on June 27, 2024, 5:09 p.m.