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Establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study
BACKGROUND: To establish a prognostic model to predict the overall survival (OS) in patients with unresectable hepatocellular carcinoma (HCC) treated with intensity modulated radiotherapy (IMRT). METHODS: The unresectable HCC patients treated with IMRT were retrospectively analyzed and randomized in...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245442/ https://www.ncbi.nlm.nih.gov/pubmed/37287040 http://dx.doi.org/10.1186/s13014-023-02292-7 |
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author | Long, Meiying Li, Jianxu He, Meiling Qiu, Jialin Zhang, Ruijun Liu, Yingchun Liang, Chunfeng Lu, Haiyan Pang, Yadan Zhou, Hongmei Yu, Hongping Qiu, Moqin |
author_facet | Long, Meiying Li, Jianxu He, Meiling Qiu, Jialin Zhang, Ruijun Liu, Yingchun Liang, Chunfeng Lu, Haiyan Pang, Yadan Zhou, Hongmei Yu, Hongping Qiu, Moqin |
author_sort | Long, Meiying |
collection | PubMed |
description | BACKGROUND: To establish a prognostic model to predict the overall survival (OS) in patients with unresectable hepatocellular carcinoma (HCC) treated with intensity modulated radiotherapy (IMRT). METHODS: The unresectable HCC patients treated with IMRT were retrospectively analyzed and randomized into development cohort (n = 237) and validation cohort (n = 103) in a 7:3 ratio. We developed a prognosis model with the multivariate Cox regression analysis in the development cohort to derive the predictive nomogram, which was then validated in the validation cohort. Model performance was evaluated by the c-index, the area under curve(AUC) and the calibration plot. RESULTS: A total of 340 patients were enrolled. Tumor numbers > 3 (HR = 1.69, 95% CI = 1.21–2.37), AFP ≥ 400 ng/ml (HR = 1.52, 95% CI = 1.10–2.10), PLT < 100 × 10^9(HR = 1.7495% CI = 1.11–2.73), ALP > 150U/L (HR = 1.65, 95% CI = 1.15–2.37) and prior surgery (HR = 0.63, 95% CI = 0.43–0.93) were independent prognostic factors. The nomogram based on independent factors was constructed. The c-index for OS prediction was 0.658 (95% CI, 0.647–0.804) and 0.683 (95% CI, 0.580–0.785) in the development and validation cohort, respectively. The nomogram demonstrated good discriminative ability with AUC rates of 0.726, 0.739 and 0.753 at 1-year, 2-year and 3-year models in the development cohort, and 0.715, 0.756 and 0.780 in the validation cohort, respectively. Additionally, good prognostic discrimination of the nomogram is also reflected in stratifying patients into two subgroups with distinct prognosis. CONCLUSIONS: We constructed a prognostic nomogram for predicting the survival of patients with unresectable HCC treated with IMRT. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13014-023-02292-7. |
format | Online Article Text |
id | pubmed-10245442 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102454422023-06-08 Establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study Long, Meiying Li, Jianxu He, Meiling Qiu, Jialin Zhang, Ruijun Liu, Yingchun Liang, Chunfeng Lu, Haiyan Pang, Yadan Zhou, Hongmei Yu, Hongping Qiu, Moqin Radiat Oncol Research BACKGROUND: To establish a prognostic model to predict the overall survival (OS) in patients with unresectable hepatocellular carcinoma (HCC) treated with intensity modulated radiotherapy (IMRT). METHODS: The unresectable HCC patients treated with IMRT were retrospectively analyzed and randomized into development cohort (n = 237) and validation cohort (n = 103) in a 7:3 ratio. We developed a prognosis model with the multivariate Cox regression analysis in the development cohort to derive the predictive nomogram, which was then validated in the validation cohort. Model performance was evaluated by the c-index, the area under curve(AUC) and the calibration plot. RESULTS: A total of 340 patients were enrolled. Tumor numbers > 3 (HR = 1.69, 95% CI = 1.21–2.37), AFP ≥ 400 ng/ml (HR = 1.52, 95% CI = 1.10–2.10), PLT < 100 × 10^9(HR = 1.7495% CI = 1.11–2.73), ALP > 150U/L (HR = 1.65, 95% CI = 1.15–2.37) and prior surgery (HR = 0.63, 95% CI = 0.43–0.93) were independent prognostic factors. The nomogram based on independent factors was constructed. The c-index for OS prediction was 0.658 (95% CI, 0.647–0.804) and 0.683 (95% CI, 0.580–0.785) in the development and validation cohort, respectively. The nomogram demonstrated good discriminative ability with AUC rates of 0.726, 0.739 and 0.753 at 1-year, 2-year and 3-year models in the development cohort, and 0.715, 0.756 and 0.780 in the validation cohort, respectively. Additionally, good prognostic discrimination of the nomogram is also reflected in stratifying patients into two subgroups with distinct prognosis. CONCLUSIONS: We constructed a prognostic nomogram for predicting the survival of patients with unresectable HCC treated with IMRT. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13014-023-02292-7. BioMed Central 2023-06-07 /pmc/articles/PMC10245442/ /pubmed/37287040 http://dx.doi.org/10.1186/s13014-023-02292-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Long, Meiying Li, Jianxu He, Meiling Qiu, Jialin Zhang, Ruijun Liu, Yingchun Liang, Chunfeng Lu, Haiyan Pang, Yadan Zhou, Hongmei Yu, Hongping Qiu, Moqin Establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study |
title | Establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study |
title_full | Establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study |
title_fullStr | Establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study |
title_full_unstemmed | Establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study |
title_short | Establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study |
title_sort | establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245442/ https://www.ncbi.nlm.nih.gov/pubmed/37287040 http://dx.doi.org/10.1186/s13014-023-02292-7 |
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