Cargando…

Identifying Outcomes of Patients With Advanced Pancreatic Adenocarcinoma and RECIST Stable Disease Using Radiomics Analysis

Few studies have explored the biomarkers for predicting the heterogeneous outcomes of patients with advanced pancreatic adenocarcinoma showing stable disease (SD) on the initial postchemotherapy computed tomography. We aimed to devise a radiomics signature (RS) to predict these outcomes for further...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Qiuxia, Mao, Yize, Xie, Hui, Qin, Tao, Mai, Zhijun, Cai, Qian, Wen, Hailin, Li, Yong, Zhang, Rong, Liu, Lizhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8966975/
https://www.ncbi.nlm.nih.gov/pubmed/35319966
http://dx.doi.org/10.1200/PO.21.00362
_version_ 1784678739046563840
author Yang, Qiuxia
Mao, Yize
Xie, Hui
Qin, Tao
Mai, Zhijun
Cai, Qian
Wen, Hailin
Li, Yong
Zhang, Rong
Liu, Lizhi
author_facet Yang, Qiuxia
Mao, Yize
Xie, Hui
Qin, Tao
Mai, Zhijun
Cai, Qian
Wen, Hailin
Li, Yong
Zhang, Rong
Liu, Lizhi
author_sort Yang, Qiuxia
collection PubMed
description Few studies have explored the biomarkers for predicting the heterogeneous outcomes of patients with advanced pancreatic adenocarcinoma showing stable disease (SD) on the initial postchemotherapy computed tomography. We aimed to devise a radiomics signature (RS) to predict these outcomes for further risk stratification. MATERIALS AND METHODS: Patients with advanced pancreatic adenocarcinoma and SD after chemotherapy were included. Pancreatic lesions on initial postchemotherapy computed tomography images were evaluated by radiomics analysis for predicting early death (≤ 1 year). RS was then internally and externally tested. The progression-free survival and objective response rate were compared between the low-risk and high-risk group of patients classified following RS. RESULTS: Approximately 62.7% of patients receiving chemotherapy showed SD at first response evaluation in the primary cohort, which were 59.6% and 57.9% in internal and external testing cohorts, respectively. The RS predicted 1-year overall survival well, with areas under the receiver operating characteristic curve of 0.91 in the training cohort, 0.90 in the validation cohort, 0.84 in the internal testing cohort, and 0.87 in the external testing cohort. The high-risk group had a shorter median progression-free survival (7.3 months v 9.0 months, P = .016, in the training cohort; 5.9 months v 9.2 months, P = .026, in the internal testing cohort) and a lower objective response rate (2.2% v 24.0% in the training cohort) than the low-risk group. In addition, RS was not related to the clinical characteristics and chemotherapy regimens. CONCLUSION: RS independently predicts the outcomes of patients with SD after chemotherapy well and can help to improve treatment decisions by identifying patients for whom current treatment may not be suitable.
format Online
Article
Text
id pubmed-8966975
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Wolters Kluwer Health
record_format MEDLINE/PubMed
spelling pubmed-89669752022-03-31 Identifying Outcomes of Patients With Advanced Pancreatic Adenocarcinoma and RECIST Stable Disease Using Radiomics Analysis Yang, Qiuxia Mao, Yize Xie, Hui Qin, Tao Mai, Zhijun Cai, Qian Wen, Hailin Li, Yong Zhang, Rong Liu, Lizhi JCO Precis Oncol ORIGINAL REPORTS Few studies have explored the biomarkers for predicting the heterogeneous outcomes of patients with advanced pancreatic adenocarcinoma showing stable disease (SD) on the initial postchemotherapy computed tomography. We aimed to devise a radiomics signature (RS) to predict these outcomes for further risk stratification. MATERIALS AND METHODS: Patients with advanced pancreatic adenocarcinoma and SD after chemotherapy were included. Pancreatic lesions on initial postchemotherapy computed tomography images were evaluated by radiomics analysis for predicting early death (≤ 1 year). RS was then internally and externally tested. The progression-free survival and objective response rate were compared between the low-risk and high-risk group of patients classified following RS. RESULTS: Approximately 62.7% of patients receiving chemotherapy showed SD at first response evaluation in the primary cohort, which were 59.6% and 57.9% in internal and external testing cohorts, respectively. The RS predicted 1-year overall survival well, with areas under the receiver operating characteristic curve of 0.91 in the training cohort, 0.90 in the validation cohort, 0.84 in the internal testing cohort, and 0.87 in the external testing cohort. The high-risk group had a shorter median progression-free survival (7.3 months v 9.0 months, P = .016, in the training cohort; 5.9 months v 9.2 months, P = .026, in the internal testing cohort) and a lower objective response rate (2.2% v 24.0% in the training cohort) than the low-risk group. In addition, RS was not related to the clinical characteristics and chemotherapy regimens. CONCLUSION: RS independently predicts the outcomes of patients with SD after chemotherapy well and can help to improve treatment decisions by identifying patients for whom current treatment may not be suitable. Wolters Kluwer Health 2022-03-23 /pmc/articles/PMC8966975/ /pubmed/35319966 http://dx.doi.org/10.1200/PO.21.00362 Text en © 2022 by American Society of Clinical Oncology https://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/)
spellingShingle ORIGINAL REPORTS
Yang, Qiuxia
Mao, Yize
Xie, Hui
Qin, Tao
Mai, Zhijun
Cai, Qian
Wen, Hailin
Li, Yong
Zhang, Rong
Liu, Lizhi
Identifying Outcomes of Patients With Advanced Pancreatic Adenocarcinoma and RECIST Stable Disease Using Radiomics Analysis
title Identifying Outcomes of Patients With Advanced Pancreatic Adenocarcinoma and RECIST Stable Disease Using Radiomics Analysis
title_full Identifying Outcomes of Patients With Advanced Pancreatic Adenocarcinoma and RECIST Stable Disease Using Radiomics Analysis
title_fullStr Identifying Outcomes of Patients With Advanced Pancreatic Adenocarcinoma and RECIST Stable Disease Using Radiomics Analysis
title_full_unstemmed Identifying Outcomes of Patients With Advanced Pancreatic Adenocarcinoma and RECIST Stable Disease Using Radiomics Analysis
title_short Identifying Outcomes of Patients With Advanced Pancreatic Adenocarcinoma and RECIST Stable Disease Using Radiomics Analysis
title_sort identifying outcomes of patients with advanced pancreatic adenocarcinoma and recist stable disease using radiomics analysis
topic ORIGINAL REPORTS
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8966975/
https://www.ncbi.nlm.nih.gov/pubmed/35319966
http://dx.doi.org/10.1200/PO.21.00362
work_keys_str_mv AT yangqiuxia identifyingoutcomesofpatientswithadvancedpancreaticadenocarcinomaandreciststablediseaseusingradiomicsanalysis
AT maoyize identifyingoutcomesofpatientswithadvancedpancreaticadenocarcinomaandreciststablediseaseusingradiomicsanalysis
AT xiehui identifyingoutcomesofpatientswithadvancedpancreaticadenocarcinomaandreciststablediseaseusingradiomicsanalysis
AT qintao identifyingoutcomesofpatientswithadvancedpancreaticadenocarcinomaandreciststablediseaseusingradiomicsanalysis
AT maizhijun identifyingoutcomesofpatientswithadvancedpancreaticadenocarcinomaandreciststablediseaseusingradiomicsanalysis
AT caiqian identifyingoutcomesofpatientswithadvancedpancreaticadenocarcinomaandreciststablediseaseusingradiomicsanalysis
AT wenhailin identifyingoutcomesofpatientswithadvancedpancreaticadenocarcinomaandreciststablediseaseusingradiomicsanalysis
AT liyong identifyingoutcomesofpatientswithadvancedpancreaticadenocarcinomaandreciststablediseaseusingradiomicsanalysis
AT zhangrong identifyingoutcomesofpatientswithadvancedpancreaticadenocarcinomaandreciststablediseaseusingradiomicsanalysis
AT liulizhi identifyingoutcomesofpatientswithadvancedpancreaticadenocarcinomaandreciststablediseaseusingradiomicsanalysis