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Noninvasive Imaging Evaluation Based on Computed Tomography of the Efficacy of Initial Transarterial Chemoembolization to Predict Outcome in Patients with Hepatocellular Carcinoma

PURPOSE: This study aims to develop a new model to more comprehensively and accurately predict the survival of patients with HCC after initial TACE. PATIENTS AND METHODS: The whole cohort (n = 102) was randomly divided into a training cohort and a validation cohort in the ratio of 8:2. The optimal r...

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Autores principales: Dai, Yanmei, Jiang, Huijie, Feng, Shi-Ting, Xia, Yuwei, Li, Jinping, Zhao, Sheng, Wang, Dandan, Zeng, Xu, Chen, Yusi, Xin, Yanjie, Liu, Dongmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994626/
https://www.ncbi.nlm.nih.gov/pubmed/35411303
http://dx.doi.org/10.2147/JHC.S351077
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author Dai, Yanmei
Jiang, Huijie
Feng, Shi-Ting
Xia, Yuwei
Li, Jinping
Zhao, Sheng
Wang, Dandan
Zeng, Xu
Chen, Yusi
Xin, Yanjie
Liu, Dongmin
author_facet Dai, Yanmei
Jiang, Huijie
Feng, Shi-Ting
Xia, Yuwei
Li, Jinping
Zhao, Sheng
Wang, Dandan
Zeng, Xu
Chen, Yusi
Xin, Yanjie
Liu, Dongmin
author_sort Dai, Yanmei
collection PubMed
description PURPOSE: This study aims to develop a new model to more comprehensively and accurately predict the survival of patients with HCC after initial TACE. PATIENTS AND METHODS: The whole cohort (n = 102) was randomly divided into a training cohort and a validation cohort in the ratio of 8:2. The optimal radiomics signatures were screened using the least absolute shrinkage and selection operator algorithm (LASSO) regression for constructing the radscore to predict overall survival (OS). The C-index (95% confidence interval, CI), calibration curve, and decision curve analysis (DCA) were used to evaluate the performance of the models. The independent risk factors (hazard ratio, HR) for predicting OS were stratified by Kaplan–Meier (K-M) analysis and the Log rank test. RESULTS: The median OS was 439 days (95% CI: 215.795–662.205) in whole cohort, and in the training cohort and validation cohort, the median OS was 552 days (95% CI: 171.172–932.828), 395 days (95% CI: 309.415–480.585), respectively (P = 0.889). After multivariate cox regression, the combined radscore-clinical model was consisted of radscore (HR: 2.065, 95% CI: 1.285–3.316; P = 0.0029) and post-response (HR: 1.880, 95% CI: 1.310–2.697; P = 0.0007), both of which were independent risk factors for the OS. In the validation cohort, the efficacy of both the radscore (C-index: 0.769, 95% CI: 0.496–1.000) and combined model (C-index: 0.770, 95% CI: 0.581–0.806) were higher than that of the clinical model (C-index: 0.655, 95% CI: 0.508–0.802). The calibration curve of the combined model for predicting OS presented good consistency between observations and predictions in both the training cohort and validation cohort. CONCLUSION: Noninvasive imaging has a good prediction performance of survival after initial TACE in patients with HCC. The combined model consisting of post-response and radscore may be able to better predict outcome.
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spelling pubmed-89946262022-04-10 Noninvasive Imaging Evaluation Based on Computed Tomography of the Efficacy of Initial Transarterial Chemoembolization to Predict Outcome in Patients with Hepatocellular Carcinoma Dai, Yanmei Jiang, Huijie Feng, Shi-Ting Xia, Yuwei Li, Jinping Zhao, Sheng Wang, Dandan Zeng, Xu Chen, Yusi Xin, Yanjie Liu, Dongmin J Hepatocell Carcinoma Original Research PURPOSE: This study aims to develop a new model to more comprehensively and accurately predict the survival of patients with HCC after initial TACE. PATIENTS AND METHODS: The whole cohort (n = 102) was randomly divided into a training cohort and a validation cohort in the ratio of 8:2. The optimal radiomics signatures were screened using the least absolute shrinkage and selection operator algorithm (LASSO) regression for constructing the radscore to predict overall survival (OS). The C-index (95% confidence interval, CI), calibration curve, and decision curve analysis (DCA) were used to evaluate the performance of the models. The independent risk factors (hazard ratio, HR) for predicting OS were stratified by Kaplan–Meier (K-M) analysis and the Log rank test. RESULTS: The median OS was 439 days (95% CI: 215.795–662.205) in whole cohort, and in the training cohort and validation cohort, the median OS was 552 days (95% CI: 171.172–932.828), 395 days (95% CI: 309.415–480.585), respectively (P = 0.889). After multivariate cox regression, the combined radscore-clinical model was consisted of radscore (HR: 2.065, 95% CI: 1.285–3.316; P = 0.0029) and post-response (HR: 1.880, 95% CI: 1.310–2.697; P = 0.0007), both of which were independent risk factors for the OS. In the validation cohort, the efficacy of both the radscore (C-index: 0.769, 95% CI: 0.496–1.000) and combined model (C-index: 0.770, 95% CI: 0.581–0.806) were higher than that of the clinical model (C-index: 0.655, 95% CI: 0.508–0.802). The calibration curve of the combined model for predicting OS presented good consistency between observations and predictions in both the training cohort and validation cohort. CONCLUSION: Noninvasive imaging has a good prediction performance of survival after initial TACE in patients with HCC. The combined model consisting of post-response and radscore may be able to better predict outcome. Dove 2022-04-05 /pmc/articles/PMC8994626/ /pubmed/35411303 http://dx.doi.org/10.2147/JHC.S351077 Text en © 2022 Dai et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Dai, Yanmei
Jiang, Huijie
Feng, Shi-Ting
Xia, Yuwei
Li, Jinping
Zhao, Sheng
Wang, Dandan
Zeng, Xu
Chen, Yusi
Xin, Yanjie
Liu, Dongmin
Noninvasive Imaging Evaluation Based on Computed Tomography of the Efficacy of Initial Transarterial Chemoembolization to Predict Outcome in Patients with Hepatocellular Carcinoma
title Noninvasive Imaging Evaluation Based on Computed Tomography of the Efficacy of Initial Transarterial Chemoembolization to Predict Outcome in Patients with Hepatocellular Carcinoma
title_full Noninvasive Imaging Evaluation Based on Computed Tomography of the Efficacy of Initial Transarterial Chemoembolization to Predict Outcome in Patients with Hepatocellular Carcinoma
title_fullStr Noninvasive Imaging Evaluation Based on Computed Tomography of the Efficacy of Initial Transarterial Chemoembolization to Predict Outcome in Patients with Hepatocellular Carcinoma
title_full_unstemmed Noninvasive Imaging Evaluation Based on Computed Tomography of the Efficacy of Initial Transarterial Chemoembolization to Predict Outcome in Patients with Hepatocellular Carcinoma
title_short Noninvasive Imaging Evaluation Based on Computed Tomography of the Efficacy of Initial Transarterial Chemoembolization to Predict Outcome in Patients with Hepatocellular Carcinoma
title_sort noninvasive imaging evaluation based on computed tomography of the efficacy of initial transarterial chemoembolization to predict outcome in patients with hepatocellular carcinoma
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994626/
https://www.ncbi.nlm.nih.gov/pubmed/35411303
http://dx.doi.org/10.2147/JHC.S351077
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