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Neoadjuvant therapy versus upfront surgery for potentially resectable pancreatic cancer: A Markov decision analysis

BACKGROUND: Neoadjuvant therapy has emerged as an alternative treatment strategy for potentially resectable pancreatic cancer. In the absence of large randomized controlled trials offering a direct comparison, this study aims to use Markov decision analysis to compare efficacy of traditional surgery...

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Autores principales: Bradley, Alison, Van Der Meer, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394923/
https://www.ncbi.nlm.nih.gov/pubmed/30817807
http://dx.doi.org/10.1371/journal.pone.0212805
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author Bradley, Alison
Van Der Meer, Robert
author_facet Bradley, Alison
Van Der Meer, Robert
author_sort Bradley, Alison
collection PubMed
description BACKGROUND: Neoadjuvant therapy has emerged as an alternative treatment strategy for potentially resectable pancreatic cancer. In the absence of large randomized controlled trials offering a direct comparison, this study aims to use Markov decision analysis to compare efficacy of traditional surgery first (SF) and neoadjuvant treatment (NAT) pathways for potentially resectable pancreatic cancer. METHODS: An advanced Markov decision analysis model was constructed to compare SF and NAT pathways for potentially resectable pancreatic cancer. Transition probabilities were calculated from randomized control and Phase II/III trials after comprehensive literature search. Utility outcomes were measured in overall and quality-adjusted life months (QALMs) on an intention-to-treat basis as the primary outcome. Markov cohort analysis of treatment received was the secondary outcome. Model uncertainties were tested with one and two-way deterministic and probabilistic Monte Carlo sensitivity analysis. RESULTS: SF gave 23.72 months (18.51 QALMs) versus 20.22 months (16.26 QALMs). Markov Cohort Analysis showed that where all treatment modalities were received NAT gave 35.05 months (29.87 QALMs) versus 30.96 months (24.86QALMs) for R0 resection and 34.08 months (29.87 QALMs) versus 25.85 months (20.72 QALMs) for R1 resection. One-way deterministic sensitivity analysis showed that NAT was superior if the resection rate was greater than 51.04% or below 75.68% in SF pathway. Two-way sensitivity analysis showed that pathway superiority depended on obtaining multimodal treatment in either pathway. CONCLUSION: Whilst NAT is a viable alternative to traditional SF approach, superior pathway selection depends on the individual patient’s likelihood of receiving multimodal treatment in either pathway.
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spelling pubmed-63949232019-03-08 Neoadjuvant therapy versus upfront surgery for potentially resectable pancreatic cancer: A Markov decision analysis Bradley, Alison Van Der Meer, Robert PLoS One Research Article BACKGROUND: Neoadjuvant therapy has emerged as an alternative treatment strategy for potentially resectable pancreatic cancer. In the absence of large randomized controlled trials offering a direct comparison, this study aims to use Markov decision analysis to compare efficacy of traditional surgery first (SF) and neoadjuvant treatment (NAT) pathways for potentially resectable pancreatic cancer. METHODS: An advanced Markov decision analysis model was constructed to compare SF and NAT pathways for potentially resectable pancreatic cancer. Transition probabilities were calculated from randomized control and Phase II/III trials after comprehensive literature search. Utility outcomes were measured in overall and quality-adjusted life months (QALMs) on an intention-to-treat basis as the primary outcome. Markov cohort analysis of treatment received was the secondary outcome. Model uncertainties were tested with one and two-way deterministic and probabilistic Monte Carlo sensitivity analysis. RESULTS: SF gave 23.72 months (18.51 QALMs) versus 20.22 months (16.26 QALMs). Markov Cohort Analysis showed that where all treatment modalities were received NAT gave 35.05 months (29.87 QALMs) versus 30.96 months (24.86QALMs) for R0 resection and 34.08 months (29.87 QALMs) versus 25.85 months (20.72 QALMs) for R1 resection. One-way deterministic sensitivity analysis showed that NAT was superior if the resection rate was greater than 51.04% or below 75.68% in SF pathway. Two-way sensitivity analysis showed that pathway superiority depended on obtaining multimodal treatment in either pathway. CONCLUSION: Whilst NAT is a viable alternative to traditional SF approach, superior pathway selection depends on the individual patient’s likelihood of receiving multimodal treatment in either pathway. Public Library of Science 2019-02-28 /pmc/articles/PMC6394923/ /pubmed/30817807 http://dx.doi.org/10.1371/journal.pone.0212805 Text en © 2019 Bradley, Van Der Meer 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
Bradley, Alison
Van Der Meer, Robert
Neoadjuvant therapy versus upfront surgery for potentially resectable pancreatic cancer: A Markov decision analysis
title Neoadjuvant therapy versus upfront surgery for potentially resectable pancreatic cancer: A Markov decision analysis
title_full Neoadjuvant therapy versus upfront surgery for potentially resectable pancreatic cancer: A Markov decision analysis
title_fullStr Neoadjuvant therapy versus upfront surgery for potentially resectable pancreatic cancer: A Markov decision analysis
title_full_unstemmed Neoadjuvant therapy versus upfront surgery for potentially resectable pancreatic cancer: A Markov decision analysis
title_short Neoadjuvant therapy versus upfront surgery for potentially resectable pancreatic cancer: A Markov decision analysis
title_sort neoadjuvant therapy versus upfront surgery for potentially resectable pancreatic cancer: a markov decision analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394923/
https://www.ncbi.nlm.nih.gov/pubmed/30817807
http://dx.doi.org/10.1371/journal.pone.0212805
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