Prognostic Value of a CT Radiomics-Based Nomogram for the Overall Survival of Patients with Nonmetastatic BCLC Stage C Hepatocellular Carcinoma after Stereotactic Body Radiotherapy
Copyright © 2023 Lihong Wang et al..
Purpose: This study aimed to investigatie the feasibility of pretherapeutic CT radiomics-based nomograms to predict the overall survival (OS) of patients with nondistant metastatic Barcelona Clinic Liver Cancer stage C (BCLC-C) hepatocellular carcinoma (HCC) undergoing stereotactic body radiotherapy (SBRT).
Methods: A retrospective review of 137 patients with nondistant metastatic BCLC-C HCC who underwent SBRT was made. Radiomics features distilled from pretherapeutic CT images were selected by the method of LASSO regression for radiomics signature construction. Then, the clinical model was constructed based on clinical characteristics. A radiomics nomogram was constructed using the radiomics score (Rad-score) and clinical characteristics to predict post-SBRT OS in BCLC-C HCC patients. An analysis of discriminatory ability and calibration was performed to confirm the efficacy of the radiomics nomogram.
Results: In order to construct the radiomic signature, seven significant features were selected. Patients were divided into low-risk (Rad-score < -0.03) and high-risk (Rad-score ≥ -0.03) groups based on the best Rad-score cutoff value. There were statistically significant differences in OS both in the training set (p < 0.0001) and the validation set (p=0.03) after stratification. The C-indexes of the radiomics nomogram were 0.77 (95% CI: 0.72-0.82) in the training set and 0.71 (95% CI: 0.61-0.81) in the validation set, which outperformed the clinical model and radiomics signature. An AUC of 0.76, 0.79, and 0.84 was reached for 6-, 12-, and 18-month survival predictions, respectively.
Conclusions: The predictive nomogram that combines radiomic features with clinical characteristics has great prospects for application in the prediction of post-SBRT OS in nondistant metastatic BCLC-C HCC patients.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:2023 |
|---|---|
| Enthalten in: |
Journal of oncology - 2023(2023) vom: 17., Seite 1554599 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Wang, Lihong [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| Anmerkungen: |
Date Revised 08.08.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
|---|
| doi: |
10.1155/2023/1554599 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM35146977X |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM35146977X | ||
| 003 | DE-627 | ||
| 005 | 20231226051435.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1155/2023/1554599 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1171.xml |
| 035 | |a (DE-627)NLM35146977X | ||
| 035 | |a (NLM)36636027 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Wang, Lihong |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Prognostic Value of a CT Radiomics-Based Nomogram for the Overall Survival of Patients with Nonmetastatic BCLC Stage C Hepatocellular Carcinoma after Stereotactic Body Radiotherapy |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 08.08.2023 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Copyright © 2023 Lihong Wang et al. | ||
| 520 | |a Purpose: This study aimed to investigatie the feasibility of pretherapeutic CT radiomics-based nomograms to predict the overall survival (OS) of patients with nondistant metastatic Barcelona Clinic Liver Cancer stage C (BCLC-C) hepatocellular carcinoma (HCC) undergoing stereotactic body radiotherapy (SBRT) | ||
| 520 | |a Methods: A retrospective review of 137 patients with nondistant metastatic BCLC-C HCC who underwent SBRT was made. Radiomics features distilled from pretherapeutic CT images were selected by the method of LASSO regression for radiomics signature construction. Then, the clinical model was constructed based on clinical characteristics. A radiomics nomogram was constructed using the radiomics score (Rad-score) and clinical characteristics to predict post-SBRT OS in BCLC-C HCC patients. An analysis of discriminatory ability and calibration was performed to confirm the efficacy of the radiomics nomogram | ||
| 520 | |a Results: In order to construct the radiomic signature, seven significant features were selected. Patients were divided into low-risk (Rad-score < -0.03) and high-risk (Rad-score ≥ -0.03) groups based on the best Rad-score cutoff value. There were statistically significant differences in OS both in the training set (p < 0.0001) and the validation set (p=0.03) after stratification. The C-indexes of the radiomics nomogram were 0.77 (95% CI: 0.72-0.82) in the training set and 0.71 (95% CI: 0.61-0.81) in the validation set, which outperformed the clinical model and radiomics signature. An AUC of 0.76, 0.79, and 0.84 was reached for 6-, 12-, and 18-month survival predictions, respectively | ||
| 520 | |a Conclusions: The predictive nomogram that combines radiomic features with clinical characteristics has great prospects for application in the prediction of post-SBRT OS in nondistant metastatic BCLC-C HCC patients | ||
| 650 | 4 | |a Journal Article | |
| 700 | 1 | |a Yan, Danfang |e verfasserin |4 aut | |
| 700 | 1 | |a Shen, Liang |e verfasserin |4 aut | |
| 700 | 1 | |a Xie, Yalin |e verfasserin |4 aut | |
| 700 | 1 | |a Yan, Senxiang |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of oncology |d 2008 |g 2023(2023) vom: 17., Seite 1554599 |w (DE-627)NLM186830491 |x 1687-8469 |7 nnns |
| 773 | 1 | 8 | |g volume:2023 |g year:2023 |g day:17 |g pages:1554599 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1155/2023/1554599 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 2023 |j 2023 |b 17 |h 1554599 | ||