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Model-Based dose escalation Designs in R with crmPack

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Model-Based dose escalation Designs in R with crmPack. / Bové, D.S.; Yeung, W.Y.; Palermo, G. et al.
In: Journal of Statistical Software, Vol. 89, No. 10, 13.06.2019.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Bové, DS, Yeung, WY, Palermo, G & Jaki, T 2019, 'Model-Based dose escalation Designs in R with crmPack', Journal of Statistical Software, vol. 89, no. 10. https://doi.org/10.18637/jss.v089.i10

APA

Bové, D. S., Yeung, W. Y., Palermo, G., & Jaki, T. (2019). Model-Based dose escalation Designs in R with crmPack. Journal of Statistical Software, 89(10). https://doi.org/10.18637/jss.v089.i10

Vancouver

Bové DS, Yeung WY, Palermo G, Jaki T. Model-Based dose escalation Designs in R with crmPack. Journal of Statistical Software. 2019 Jun 13;89(10). doi: 10.18637/jss.v089.i10

Author

Bové, D.S. ; Yeung, W.Y. ; Palermo, G. et al. / Model-Based dose escalation Designs in R with crmPack. In: Journal of Statistical Software. 2019 ; Vol. 89, No. 10.

Bibtex

@article{bb5b29f9d9c645aeb0cd26220ec0f34b,
title = "Model-Based dose escalation Designs in R with crmPack",
abstract = " Model-based dose escalation designs have gained increasing interest due to the need for more efficient and informative Phase I trials. The wide-spread implementation of such designs has been hindered by the need for either licensing specialized commercial software or programming the design and simulations from scratch for each project. The R package crmPack provides a simple and unified object-oriented framework for model-based dose escalation designs. This enables the standard use of such designs, while being able to flexibly adapt and extend them. The framework comprises classes and methods for the data structure including the dose grid, statistical models including prior specification, rules for maximum increments, next best dose, and adaptive stopping and cohort sizes. In addition to multiple modified classic continual reassessment method and escalation with overdose control designs with possibly advanced prior specifications (e.g., minimal informative and mixture priors), crmPack currently features dual-endpoint (safety and biomarker) designs and two-part designs. Optional assignment of a small number of patients in each cohort to placebo instead of treatment enables the use in trials outside oncology.",
author = "D.S. Bov{\'e} and W.Y. Yeung and G. Palermo and T. Jaki",
year = "2019",
month = jun,
day = "13",
doi = "10.18637/jss.v089.i10",
language = "English",
volume = "89",
journal = "Journal of Statistical Software",
issn = "1548-7660",
publisher = "University of California at Los Angeles",
number = "10",

}

RIS

TY - JOUR

T1 - Model-Based dose escalation Designs in R with crmPack

AU - Bové, D.S.

AU - Yeung, W.Y.

AU - Palermo, G.

AU - Jaki, T.

PY - 2019/6/13

Y1 - 2019/6/13

N2 - Model-based dose escalation designs have gained increasing interest due to the need for more efficient and informative Phase I trials. The wide-spread implementation of such designs has been hindered by the need for either licensing specialized commercial software or programming the design and simulations from scratch for each project. The R package crmPack provides a simple and unified object-oriented framework for model-based dose escalation designs. This enables the standard use of such designs, while being able to flexibly adapt and extend them. The framework comprises classes and methods for the data structure including the dose grid, statistical models including prior specification, rules for maximum increments, next best dose, and adaptive stopping and cohort sizes. In addition to multiple modified classic continual reassessment method and escalation with overdose control designs with possibly advanced prior specifications (e.g., minimal informative and mixture priors), crmPack currently features dual-endpoint (safety and biomarker) designs and two-part designs. Optional assignment of a small number of patients in each cohort to placebo instead of treatment enables the use in trials outside oncology.

AB - Model-based dose escalation designs have gained increasing interest due to the need for more efficient and informative Phase I trials. The wide-spread implementation of such designs has been hindered by the need for either licensing specialized commercial software or programming the design and simulations from scratch for each project. The R package crmPack provides a simple and unified object-oriented framework for model-based dose escalation designs. This enables the standard use of such designs, while being able to flexibly adapt and extend them. The framework comprises classes and methods for the data structure including the dose grid, statistical models including prior specification, rules for maximum increments, next best dose, and adaptive stopping and cohort sizes. In addition to multiple modified classic continual reassessment method and escalation with overdose control designs with possibly advanced prior specifications (e.g., minimal informative and mixture priors), crmPack currently features dual-endpoint (safety and biomarker) designs and two-part designs. Optional assignment of a small number of patients in each cohort to placebo instead of treatment enables the use in trials outside oncology.

U2 - 10.18637/jss.v089.i10

DO - 10.18637/jss.v089.i10

M3 - Journal article

VL - 89

JO - Journal of Statistical Software

JF - Journal of Statistical Software

SN - 1548-7660

IS - 10

ER -