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Generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups
BACKGROUND: Visceral leishmaniasis (VL) is a parasitic disease transmitted by sandflies and is fatal if left untreated. Phase II trials of new treatment regimens for VL are primarily carried out to evaluate safety and efficacy, while pharmacokinetic data are also important to inform future combinati...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4647805/ https://www.ncbi.nlm.nih.gov/pubmed/26573827 http://dx.doi.org/10.1186/s13063-015-1018-1 |
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author | Allison, Annabel Edwards, Tansy Omollo, Raymond Alves, Fabiana Magirr, Dominic E. Alexander, Neal D. |
author_facet | Allison, Annabel Edwards, Tansy Omollo, Raymond Alves, Fabiana Magirr, Dominic E. Alexander, Neal D. |
author_sort | Allison, Annabel |
collection | PubMed |
description | BACKGROUND: Visceral leishmaniasis (VL) is a parasitic disease transmitted by sandflies and is fatal if left untreated. Phase II trials of new treatment regimens for VL are primarily carried out to evaluate safety and efficacy, while pharmacokinetic data are also important to inform future combination treatment regimens. The efficacy of VL treatments is evaluated at two time points, initial cure, when treatment is completed and definitive cure, commonly 6 months post end of treatment, to allow for slow response to treatment and detection of relapses. This paper investigates a generalization of the triangular design to impose a minimum sample size for pharmacokinetic or other analyses, and methods to estimate efficacy at extended follow-up accounting for the sequential design and changes in cure status during extended follow-up. METHODS: We provided R functions that generalize the triangular design to impose a minimum sample size before allowing stopping for efficacy. For estimation of efficacy at a second, extended, follow-up time, the performance of a shrinkage estimator (SHE), a probability tree estimator (PTE) and the maximum likelihood estimator (MLE) for estimation was assessed by simulation. RESULTS: The SHE and PTE are viable approaches to estimate an extended follow-up although the SHE performed better than the PTE: the bias and root mean square error were lower and coverage probabilities higher. CONCLUSIONS: Generalization of the triangular design is simple to implement for adaptations to meet requirements for pharmacokinetic analyses. Using the simple MLE approach to estimate efficacy at extended follow-up will lead to biased results, generally over-estimating treatment success. The SHE is recommended in trials of two or more treatments. The PTE is an acceptable alternative for one-arm trials or where use of the SHE is not possible due to computational complexity. TRIAL REGISTRATION: NCT01067443, February 2010. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13063-015-1018-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4647805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46478052015-11-18 Generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups Allison, Annabel Edwards, Tansy Omollo, Raymond Alves, Fabiana Magirr, Dominic E. Alexander, Neal D. Trials Methodology BACKGROUND: Visceral leishmaniasis (VL) is a parasitic disease transmitted by sandflies and is fatal if left untreated. Phase II trials of new treatment regimens for VL are primarily carried out to evaluate safety and efficacy, while pharmacokinetic data are also important to inform future combination treatment regimens. The efficacy of VL treatments is evaluated at two time points, initial cure, when treatment is completed and definitive cure, commonly 6 months post end of treatment, to allow for slow response to treatment and detection of relapses. This paper investigates a generalization of the triangular design to impose a minimum sample size for pharmacokinetic or other analyses, and methods to estimate efficacy at extended follow-up accounting for the sequential design and changes in cure status during extended follow-up. METHODS: We provided R functions that generalize the triangular design to impose a minimum sample size before allowing stopping for efficacy. For estimation of efficacy at a second, extended, follow-up time, the performance of a shrinkage estimator (SHE), a probability tree estimator (PTE) and the maximum likelihood estimator (MLE) for estimation was assessed by simulation. RESULTS: The SHE and PTE are viable approaches to estimate an extended follow-up although the SHE performed better than the PTE: the bias and root mean square error were lower and coverage probabilities higher. CONCLUSIONS: Generalization of the triangular design is simple to implement for adaptations to meet requirements for pharmacokinetic analyses. Using the simple MLE approach to estimate efficacy at extended follow-up will lead to biased results, generally over-estimating treatment success. The SHE is recommended in trials of two or more treatments. The PTE is an acceptable alternative for one-arm trials or where use of the SHE is not possible due to computational complexity. TRIAL REGISTRATION: NCT01067443, February 2010. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13063-015-1018-1) contains supplementary material, which is available to authorized users. BioMed Central 2015-11-16 /pmc/articles/PMC4647805/ /pubmed/26573827 http://dx.doi.org/10.1186/s13063-015-1018-1 Text en © Allison et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Allison, Annabel Edwards, Tansy Omollo, Raymond Alves, Fabiana Magirr, Dominic E. Alexander, Neal D. Generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups |
title | Generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups |
title_full | Generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups |
title_fullStr | Generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups |
title_full_unstemmed | Generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups |
title_short | Generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups |
title_sort | generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4647805/ https://www.ncbi.nlm.nih.gov/pubmed/26573827 http://dx.doi.org/10.1186/s13063-015-1018-1 |
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