Cargando…
Development and validation of nomograms by radiomic features on ultrasound imaging for predicting overall survival in patients with primary nodal diffuse large B-cell lymphoma
OBJECTIVES: To develop and validate a nomogram to predict the overall survival (OS) of patients with primary nodal diffuse large B-cell lymphoma(N-DLBCL) based on radiomic features and clinical features. MATERIALS AND METHODS: A retrospective analysis was performed on 145 patients confirmed with N-D...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9768489/ https://www.ncbi.nlm.nih.gov/pubmed/36568168 http://dx.doi.org/10.3389/fonc.2022.991948 |
_version_ | 1784854179883253760 |
---|---|
author | Deng, Hongyan Zhou, Yasu Lu, Wenjuan Chen, Wenqin Yuan, Ya Li, Lu Shu, Hua Zhang, Pingyang Ye, Xinhua |
author_facet | Deng, Hongyan Zhou, Yasu Lu, Wenjuan Chen, Wenqin Yuan, Ya Li, Lu Shu, Hua Zhang, Pingyang Ye, Xinhua |
author_sort | Deng, Hongyan |
collection | PubMed |
description | OBJECTIVES: To develop and validate a nomogram to predict the overall survival (OS) of patients with primary nodal diffuse large B-cell lymphoma(N-DLBCL) based on radiomic features and clinical features. MATERIALS AND METHODS: A retrospective analysis was performed on 145 patients confirmed with N-DLBCL and they were randomly assigned to training set(n=78), internal validation set(n=33), external validation set(n=34). First, a clinical model (model 1) was established according to clinical features and ultrasound (US) results. Then, based on the radiomics features extracted from conventional ultrasound images, a radiomic signature was constructed (model 2), and the radiomics score (Rad-Score) was calculated. Finally, a comprehensive model was established (model 3) combined with Rad-score and clinical features. Receiver operating characteristic (ROC) curves were employed to evaluate the performance of model 1, model 2 and model 3. Based on model 3, we plotted a nomogram. Calibration curves were used to test the effectiveness of the nomogram, and decision curve analysis (DCA) was used to asset the nomogram in clinical use. RESULTS: According to multivariate analysis, 3 clinical features and Rad-score were finally selected to construct the model 3, which showed better predictive value for OS in patients with N-DLBCL than mode 1 and model 2 in training (AUC,0. 891 vs. 0.779 vs.0.756), internal validation (AUC, 0.868 vs. 0.713, vs.0.756) and external validation (AUC, 914 vs. 0.866, vs.0.789) sets. Decision curve analysis demonstrated that the nomogram based on model 3 was more clinically useful than the other two models. CONCLUSION: The developed nomogram is a useful tool for precisely analyzing the prognosis of N-DLBCL patients, which could help clinicians in making personalized survival predictions and assessing individualized clinical options. |
format | Online Article Text |
id | pubmed-9768489 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97684892022-12-22 Development and validation of nomograms by radiomic features on ultrasound imaging for predicting overall survival in patients with primary nodal diffuse large B-cell lymphoma Deng, Hongyan Zhou, Yasu Lu, Wenjuan Chen, Wenqin Yuan, Ya Li, Lu Shu, Hua Zhang, Pingyang Ye, Xinhua Front Oncol Oncology OBJECTIVES: To develop and validate a nomogram to predict the overall survival (OS) of patients with primary nodal diffuse large B-cell lymphoma(N-DLBCL) based on radiomic features and clinical features. MATERIALS AND METHODS: A retrospective analysis was performed on 145 patients confirmed with N-DLBCL and they were randomly assigned to training set(n=78), internal validation set(n=33), external validation set(n=34). First, a clinical model (model 1) was established according to clinical features and ultrasound (US) results. Then, based on the radiomics features extracted from conventional ultrasound images, a radiomic signature was constructed (model 2), and the radiomics score (Rad-Score) was calculated. Finally, a comprehensive model was established (model 3) combined with Rad-score and clinical features. Receiver operating characteristic (ROC) curves were employed to evaluate the performance of model 1, model 2 and model 3. Based on model 3, we plotted a nomogram. Calibration curves were used to test the effectiveness of the nomogram, and decision curve analysis (DCA) was used to asset the nomogram in clinical use. RESULTS: According to multivariate analysis, 3 clinical features and Rad-score were finally selected to construct the model 3, which showed better predictive value for OS in patients with N-DLBCL than mode 1 and model 2 in training (AUC,0. 891 vs. 0.779 vs.0.756), internal validation (AUC, 0.868 vs. 0.713, vs.0.756) and external validation (AUC, 914 vs. 0.866, vs.0.789) sets. Decision curve analysis demonstrated that the nomogram based on model 3 was more clinically useful than the other two models. CONCLUSION: The developed nomogram is a useful tool for precisely analyzing the prognosis of N-DLBCL patients, which could help clinicians in making personalized survival predictions and assessing individualized clinical options. Frontiers Media S.A. 2022-12-07 /pmc/articles/PMC9768489/ /pubmed/36568168 http://dx.doi.org/10.3389/fonc.2022.991948 Text en Copyright © 2022 Deng, Zhou, Lu, Chen, Yuan, Li, Shu, Zhang and Ye 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 Deng, Hongyan Zhou, Yasu Lu, Wenjuan Chen, Wenqin Yuan, Ya Li, Lu Shu, Hua Zhang, Pingyang Ye, Xinhua Development and validation of nomograms by radiomic features on ultrasound imaging for predicting overall survival in patients with primary nodal diffuse large B-cell lymphoma |
title | Development and validation of nomograms by radiomic features on ultrasound imaging for predicting overall survival in patients with primary nodal diffuse large B-cell lymphoma |
title_full | Development and validation of nomograms by radiomic features on ultrasound imaging for predicting overall survival in patients with primary nodal diffuse large B-cell lymphoma |
title_fullStr | Development and validation of nomograms by radiomic features on ultrasound imaging for predicting overall survival in patients with primary nodal diffuse large B-cell lymphoma |
title_full_unstemmed | Development and validation of nomograms by radiomic features on ultrasound imaging for predicting overall survival in patients with primary nodal diffuse large B-cell lymphoma |
title_short | Development and validation of nomograms by radiomic features on ultrasound imaging for predicting overall survival in patients with primary nodal diffuse large B-cell lymphoma |
title_sort | development and validation of nomograms by radiomic features on ultrasound imaging for predicting overall survival in patients with primary nodal diffuse large b-cell lymphoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9768489/ https://www.ncbi.nlm.nih.gov/pubmed/36568168 http://dx.doi.org/10.3389/fonc.2022.991948 |
work_keys_str_mv | AT denghongyan developmentandvalidationofnomogramsbyradiomicfeaturesonultrasoundimagingforpredictingoverallsurvivalinpatientswithprimarynodaldiffuselargebcelllymphoma AT zhouyasu developmentandvalidationofnomogramsbyradiomicfeaturesonultrasoundimagingforpredictingoverallsurvivalinpatientswithprimarynodaldiffuselargebcelllymphoma AT luwenjuan developmentandvalidationofnomogramsbyradiomicfeaturesonultrasoundimagingforpredictingoverallsurvivalinpatientswithprimarynodaldiffuselargebcelllymphoma AT chenwenqin developmentandvalidationofnomogramsbyradiomicfeaturesonultrasoundimagingforpredictingoverallsurvivalinpatientswithprimarynodaldiffuselargebcelllymphoma AT yuanya developmentandvalidationofnomogramsbyradiomicfeaturesonultrasoundimagingforpredictingoverallsurvivalinpatientswithprimarynodaldiffuselargebcelllymphoma AT lilu developmentandvalidationofnomogramsbyradiomicfeaturesonultrasoundimagingforpredictingoverallsurvivalinpatientswithprimarynodaldiffuselargebcelllymphoma AT shuhua developmentandvalidationofnomogramsbyradiomicfeaturesonultrasoundimagingforpredictingoverallsurvivalinpatientswithprimarynodaldiffuselargebcelllymphoma AT zhangpingyang developmentandvalidationofnomogramsbyradiomicfeaturesonultrasoundimagingforpredictingoverallsurvivalinpatientswithprimarynodaldiffuselargebcelllymphoma AT yexinhua developmentandvalidationofnomogramsbyradiomicfeaturesonultrasoundimagingforpredictingoverallsurvivalinpatientswithprimarynodaldiffuselargebcelllymphoma |