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Economic Analysis of Tissue-First, Plasma-First, and Complementary NGS Approaches for Treatment-Naïve Metastatic Lung Adenocarcinoma
BACKGROUND: To compare the testing costs and testing turnaround times of tissue-first, plasma-first, and complementary next-generation sequencing (NGS) approaches in patients with treatment-naïve metastatic lung adenocarcinoma. MATERIALS AND METHODS: We developed a decision tree model to compare thr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163561/ https://www.ncbi.nlm.nih.gov/pubmed/35669427 http://dx.doi.org/10.3389/fonc.2022.873111 |
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author | Yang, Szu-Chun Lin, Chien-Chung Chen, Yi-Lin Su, Wu-Chou |
author_facet | Yang, Szu-Chun Lin, Chien-Chung Chen, Yi-Lin Su, Wu-Chou |
author_sort | Yang, Szu-Chun |
collection | PubMed |
description | BACKGROUND: To compare the testing costs and testing turnaround times of tissue-first, plasma-first, and complementary next-generation sequencing (NGS) approaches in patients with treatment-naïve metastatic lung adenocarcinoma. MATERIALS AND METHODS: We developed a decision tree model to compare three different approaches. Patients were entered into the model upon cancer diagnosis and those with both insufficient tissue specimens and negative liquid-based NGS were subjected to tissue re-biopsy. Actionable gene alterations with the U.S. Food and Drug Administration (FDA)-approved therapies included epidermal growth factor receptor (EGFR) mutation, anaplastic lymphoma kinase (ALK) gene rearrangement, ROS proto-oncogene 1 (ROS1) rearrangement, B-Raf proto-oncogene (BRAF) V600E mutation, rearranged during transfection (RET) gene rearrangement, mesenchymal-epithelial transition factor (MET) mutation, neurotrophic tyrosine receptor kinase (NTRK) gene rearrangement, K-Ras proto-oncogene (KRAS) G12C mutation, and human epidermal growth factor receptor 2 (HER2) mutation. Model outcomes were testing costs, testing turnaround times, and monetary losses taking both cost and time into consideration. We presented base-case results using probabilistic analysis. Stacked one-way and three-way sensitivity analyses were also performed. RESULTS: In terms of testing costs, tissue-first approach incurred US$2,354($1,963–$2,779) and was the most cost-efficient strategy. Complementary approach testing turnaround time (days) of 12.7 (10.8 to 14.9) was found as the least time-consuming strategy. Tissue-first, complementary, and plasma-first approaches resulted in monetary losses in USD of $4,745 ($4,010–$5,480), $6,778 ($5,923–$7,600), and $7,006 ($6,047–$7,964) respectively, and identified the same percentage of patients with appropriate FDA-approved therapies. Costs for liquid-based NGS, EGFR mutation rates, and quantity of tissue specimens were the major determinants in minimizing monetary loss. Plasma-first approach would be the preferable strategy if its testing price was reduced in USD to $818, $1,343, and $1,869 for populations with EGFR mutation rates of 30%, 45%, and 60% respectively. CONCLUSION: The tissue-first approach is currently the best strategy in minimizing monetary loss. The complementary approach is an alternative for populations with a low EGFR mutation rate. The plasma-first approach becomes increasingly preferable as EGFR mutation rates gradually increase. |
format | Online Article Text |
id | pubmed-9163561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91635612022-06-05 Economic Analysis of Tissue-First, Plasma-First, and Complementary NGS Approaches for Treatment-Naïve Metastatic Lung Adenocarcinoma Yang, Szu-Chun Lin, Chien-Chung Chen, Yi-Lin Su, Wu-Chou Front Oncol Oncology BACKGROUND: To compare the testing costs and testing turnaround times of tissue-first, plasma-first, and complementary next-generation sequencing (NGS) approaches in patients with treatment-naïve metastatic lung adenocarcinoma. MATERIALS AND METHODS: We developed a decision tree model to compare three different approaches. Patients were entered into the model upon cancer diagnosis and those with both insufficient tissue specimens and negative liquid-based NGS were subjected to tissue re-biopsy. Actionable gene alterations with the U.S. Food and Drug Administration (FDA)-approved therapies included epidermal growth factor receptor (EGFR) mutation, anaplastic lymphoma kinase (ALK) gene rearrangement, ROS proto-oncogene 1 (ROS1) rearrangement, B-Raf proto-oncogene (BRAF) V600E mutation, rearranged during transfection (RET) gene rearrangement, mesenchymal-epithelial transition factor (MET) mutation, neurotrophic tyrosine receptor kinase (NTRK) gene rearrangement, K-Ras proto-oncogene (KRAS) G12C mutation, and human epidermal growth factor receptor 2 (HER2) mutation. Model outcomes were testing costs, testing turnaround times, and monetary losses taking both cost and time into consideration. We presented base-case results using probabilistic analysis. Stacked one-way and three-way sensitivity analyses were also performed. RESULTS: In terms of testing costs, tissue-first approach incurred US$2,354($1,963–$2,779) and was the most cost-efficient strategy. Complementary approach testing turnaround time (days) of 12.7 (10.8 to 14.9) was found as the least time-consuming strategy. Tissue-first, complementary, and plasma-first approaches resulted in monetary losses in USD of $4,745 ($4,010–$5,480), $6,778 ($5,923–$7,600), and $7,006 ($6,047–$7,964) respectively, and identified the same percentage of patients with appropriate FDA-approved therapies. Costs for liquid-based NGS, EGFR mutation rates, and quantity of tissue specimens were the major determinants in minimizing monetary loss. Plasma-first approach would be the preferable strategy if its testing price was reduced in USD to $818, $1,343, and $1,869 for populations with EGFR mutation rates of 30%, 45%, and 60% respectively. CONCLUSION: The tissue-first approach is currently the best strategy in minimizing monetary loss. The complementary approach is an alternative for populations with a low EGFR mutation rate. The plasma-first approach becomes increasingly preferable as EGFR mutation rates gradually increase. Frontiers Media S.A. 2022-05-20 /pmc/articles/PMC9163561/ /pubmed/35669427 http://dx.doi.org/10.3389/fonc.2022.873111 Text en Copyright © 2022 Yang, Lin, Chen and Su https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Yang, Szu-Chun Lin, Chien-Chung Chen, Yi-Lin Su, Wu-Chou Economic Analysis of Tissue-First, Plasma-First, and Complementary NGS Approaches for Treatment-Naïve Metastatic Lung Adenocarcinoma |
title | Economic Analysis of Tissue-First, Plasma-First, and Complementary NGS Approaches for Treatment-Naïve Metastatic Lung Adenocarcinoma |
title_full | Economic Analysis of Tissue-First, Plasma-First, and Complementary NGS Approaches for Treatment-Naïve Metastatic Lung Adenocarcinoma |
title_fullStr | Economic Analysis of Tissue-First, Plasma-First, and Complementary NGS Approaches for Treatment-Naïve Metastatic Lung Adenocarcinoma |
title_full_unstemmed | Economic Analysis of Tissue-First, Plasma-First, and Complementary NGS Approaches for Treatment-Naïve Metastatic Lung Adenocarcinoma |
title_short | Economic Analysis of Tissue-First, Plasma-First, and Complementary NGS Approaches for Treatment-Naïve Metastatic Lung Adenocarcinoma |
title_sort | economic analysis of tissue-first, plasma-first, and complementary ngs approaches for treatment-naïve metastatic lung adenocarcinoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163561/ https://www.ncbi.nlm.nih.gov/pubmed/35669427 http://dx.doi.org/10.3389/fonc.2022.873111 |
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