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A Bayesian phase 2 model based adaptive design to optimise antivenom dosing: Application to a dose-finding trial for a novel Russell’s viper antivenom in Myanmar

For most antivenoms there is little information from clinical studies to infer the relationship between dose and efficacy or dose and toxicity. Antivenom dose-finding studies usually recruit too few patients (e.g. fewer than 20) relative to clinically significant event rates (e.g. 5%). Model based a...

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Autores principales: Watson, James A., Lamb, Thomas, Holmes, Jane, Warrell, David A., Thwin, Khin Thida, Aung, Zaw Lynn, Oo, Min Zaw, Nwe, Myat Thet, Smithuis, Frank, Ashley, Elizabeth A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7704047/
https://www.ncbi.nlm.nih.gov/pubmed/33196672
http://dx.doi.org/10.1371/journal.pntd.0008109
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author Watson, James A.
Lamb, Thomas
Holmes, Jane
Warrell, David A.
Thwin, Khin Thida
Aung, Zaw Lynn
Oo, Min Zaw
Nwe, Myat Thet
Smithuis, Frank
Ashley, Elizabeth A.
author_facet Watson, James A.
Lamb, Thomas
Holmes, Jane
Warrell, David A.
Thwin, Khin Thida
Aung, Zaw Lynn
Oo, Min Zaw
Nwe, Myat Thet
Smithuis, Frank
Ashley, Elizabeth A.
author_sort Watson, James A.
collection PubMed
description For most antivenoms there is little information from clinical studies to infer the relationship between dose and efficacy or dose and toxicity. Antivenom dose-finding studies usually recruit too few patients (e.g. fewer than 20) relative to clinically significant event rates (e.g. 5%). Model based adaptive dose-finding studies make efficient use of accrued patient data by using information across dosing levels, and converge rapidly to the contextually defined ‘optimal dose’. Adequate sample sizes for adaptive dose-finding trials can be determined by simulation. We propose a model based, Bayesian phase 2 type, adaptive clinical trial design for the characterisation of optimal initial antivenom doses in contexts where both efficacy and toxicity are measured as binary endpoints. This design is illustrated in the context of dose-finding for Daboia siamensis (Eastern Russell’s viper) envenoming in Myanmar. The design formalises the optimal initial dose of antivenom as the dose closest to that giving a pre-specified desired efficacy, but resulting in less than a pre-specified maximum toxicity. For Daboia siamensis envenoming, efficacy is defined as the restoration of blood coagulability within six hours, and toxicity is defined as anaphylaxis. Comprehensive simulation studies compared the expected behaviour of the model based design to a simpler rule based design (a modified ‘3+3’ design). The model based design can identify an optimal dose after fewer patients relative to the rule based design. Open source code for the simulations is made available in order to determine adequate sample sizes for future adaptive snakebite trials. Antivenom dose-finding trials would benefit from using standard model based adaptive designs. Dose-finding trials where rare events (e.g. 5% occurrence) are of clinical importance necessitate larger sample sizes than current practice. We will apply the model based design to determine a safe and efficacious dose for a novel lyophilised antivenom to treat Daboia siamensis envenoming in Myanmar.
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spelling pubmed-77040472020-12-08 A Bayesian phase 2 model based adaptive design to optimise antivenom dosing: Application to a dose-finding trial for a novel Russell’s viper antivenom in Myanmar Watson, James A. Lamb, Thomas Holmes, Jane Warrell, David A. Thwin, Khin Thida Aung, Zaw Lynn Oo, Min Zaw Nwe, Myat Thet Smithuis, Frank Ashley, Elizabeth A. PLoS Negl Trop Dis Research Article For most antivenoms there is little information from clinical studies to infer the relationship between dose and efficacy or dose and toxicity. Antivenom dose-finding studies usually recruit too few patients (e.g. fewer than 20) relative to clinically significant event rates (e.g. 5%). Model based adaptive dose-finding studies make efficient use of accrued patient data by using information across dosing levels, and converge rapidly to the contextually defined ‘optimal dose’. Adequate sample sizes for adaptive dose-finding trials can be determined by simulation. We propose a model based, Bayesian phase 2 type, adaptive clinical trial design for the characterisation of optimal initial antivenom doses in contexts where both efficacy and toxicity are measured as binary endpoints. This design is illustrated in the context of dose-finding for Daboia siamensis (Eastern Russell’s viper) envenoming in Myanmar. The design formalises the optimal initial dose of antivenom as the dose closest to that giving a pre-specified desired efficacy, but resulting in less than a pre-specified maximum toxicity. For Daboia siamensis envenoming, efficacy is defined as the restoration of blood coagulability within six hours, and toxicity is defined as anaphylaxis. Comprehensive simulation studies compared the expected behaviour of the model based design to a simpler rule based design (a modified ‘3+3’ design). The model based design can identify an optimal dose after fewer patients relative to the rule based design. Open source code for the simulations is made available in order to determine adequate sample sizes for future adaptive snakebite trials. Antivenom dose-finding trials would benefit from using standard model based adaptive designs. Dose-finding trials where rare events (e.g. 5% occurrence) are of clinical importance necessitate larger sample sizes than current practice. We will apply the model based design to determine a safe and efficacious dose for a novel lyophilised antivenom to treat Daboia siamensis envenoming in Myanmar. Public Library of Science 2020-11-16 /pmc/articles/PMC7704047/ /pubmed/33196672 http://dx.doi.org/10.1371/journal.pntd.0008109 Text en © 2020 Watson et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Watson, James A.
Lamb, Thomas
Holmes, Jane
Warrell, David A.
Thwin, Khin Thida
Aung, Zaw Lynn
Oo, Min Zaw
Nwe, Myat Thet
Smithuis, Frank
Ashley, Elizabeth A.
A Bayesian phase 2 model based adaptive design to optimise antivenom dosing: Application to a dose-finding trial for a novel Russell’s viper antivenom in Myanmar
title A Bayesian phase 2 model based adaptive design to optimise antivenom dosing: Application to a dose-finding trial for a novel Russell’s viper antivenom in Myanmar
title_full A Bayesian phase 2 model based adaptive design to optimise antivenom dosing: Application to a dose-finding trial for a novel Russell’s viper antivenom in Myanmar
title_fullStr A Bayesian phase 2 model based adaptive design to optimise antivenom dosing: Application to a dose-finding trial for a novel Russell’s viper antivenom in Myanmar
title_full_unstemmed A Bayesian phase 2 model based adaptive design to optimise antivenom dosing: Application to a dose-finding trial for a novel Russell’s viper antivenom in Myanmar
title_short A Bayesian phase 2 model based adaptive design to optimise antivenom dosing: Application to a dose-finding trial for a novel Russell’s viper antivenom in Myanmar
title_sort bayesian phase 2 model based adaptive design to optimise antivenom dosing: application to a dose-finding trial for a novel russell’s viper antivenom in myanmar
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7704047/
https://www.ncbi.nlm.nih.gov/pubmed/33196672
http://dx.doi.org/10.1371/journal.pntd.0008109
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