escalation-package: The 'escalation' package.
In escalation: A Modular Approach to Dose-Finding Clinical Trials
escalation-package R Documentation
The 'escalation' package.
Description
escalation provides methods for working with dose-finding clinical trials.
We provide implementations of many dose-finding clinical trial designs,
ncluding the continual reassessment method (CRM) by O'Quigley et al. (1990)
<doi:10.2307/2531628>, the toxicity probability interval (TPI) design by Ji
et al. (2007) <doi:10.1177/1740774507079442>, the modified TPI (mTPI) design
by Ji et al. (2010) <doi:10.1177/1740774510382799>, the Bayesian optimal
interval design (BOIN) by Liu & Yuan (2015) <doi:10.1111/rssc.12089>, EffTox
by Thall & Cook (2004) <doi:10.1111/j.0006-341X.2004.00218.x>; the design of
Wages & Tait (2015) <doi:10.1080/10543406.2014.920873>, and the 3+3
described by Korn et al. (1994) <doi:10.1002/sim.4780131802>. All designs
are implemented with a common interface. We also offer optional additional
classes to tailor the behaviour of all designs, including avoiding skipping
doses, stopping after n patients have been treated at the recommended dose,
stopping when a toxicity condition is met, or demanding that n patients are
treated before stopping is allowed. By daisy-chaining together these classes
using the pipe operator from 'magrittr', it is simple to tailor the
behaviour of a dose-finding design so it behaves how the trialist wants.
Having provided a flexible interface for specifying designs, we then provide
functions to run simulations and calculate dose-paths for future cohorts of
patients.
escalation documentation built on June 27, 2024, 5:09 p.m.
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| escalation-package | R Documentation |
The 'escalation' package.
Description
escalation provides methods for working with dose-finding clinical trials. We provide implementations of many dose-finding clinical trial designs, ncluding the continual reassessment method (CRM) by O'Quigley et al. (1990) <doi:10.2307/2531628>, the toxicity probability interval (TPI) design by Ji et al. (2007) <doi:10.1177/1740774507079442>, the modified TPI (mTPI) design by Ji et al. (2010) <doi:10.1177/1740774510382799>, the Bayesian optimal interval design (BOIN) by Liu & Yuan (2015) <doi:10.1111/rssc.12089>, EffTox by Thall & Cook (2004) <doi:10.1111/j.0006-341X.2004.00218.x>; the design of Wages & Tait (2015) <doi:10.1080/10543406.2014.920873>, and the 3+3 described by Korn et al. (1994) <doi:10.1002/sim.4780131802>. All designs are implemented with a common interface. We also offer optional additional classes to tailor the behaviour of all designs, including avoiding skipping doses, stopping after n patients have been treated at the recommended dose, stopping when a toxicity condition is met, or demanding that n patients are treated before stopping is allowed. By daisy-chaining together these classes using the pipe operator from 'magrittr', it is simple to tailor the behaviour of a dose-finding design so it behaves how the trialist wants. Having provided a flexible interface for specifying designs, we then provide functions to run simulations and calculate dose-paths for future cohorts of patients.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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