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A model to guide the management and decision of re-planning during radiotherapy for cervical cancer
BACKGROUND: To establish a model to predict whether re-planning is needed in the process of cervical cancer radiotherapy. METHODS: We collected the clinical indexes of 132 patients diagnosed with cervical cancer receiving concurrent chemotherapy and radiotherapy, including 33 factors about tumor mar...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797880/ https://www.ncbi.nlm.nih.gov/pubmed/35116382 http://dx.doi.org/10.21037/tcr-21-2545 |
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author | Zhang, Wei Li, Xiuhua Lin, Tingting Ma, Fang Ma, Xiaoyu Wu, Xiaoli Sun, Yingming Sun, Xiaoge |
author_facet | Zhang, Wei Li, Xiuhua Lin, Tingting Ma, Fang Ma, Xiaoyu Wu, Xiaoli Sun, Yingming Sun, Xiaoge |
author_sort | Zhang, Wei |
collection | PubMed |
description | BACKGROUND: To establish a model to predict whether re-planning is needed in the process of cervical cancer radiotherapy. METHODS: We collected the clinical indexes of 132 patients diagnosed with cervical cancer receiving concurrent chemotherapy and radiotherapy, including 33 factors about tumor markers [carcinoembryonic antigen (CEA), cancer antigen 125 (CA-125), squamous cell carcinoma antigen (SCC)], tumor volume, rectal volume, bladder volume, volumes receiving 30–50 Gy in organs-at-risk (OARs), and the maximum dose (Dmax) received by 1–2 cc in OARs. We established a multivariate model for re-planning evaluation via principal component analysis, and then verified the model based on the internal data. RESULTS: We identified the dose index (P1), tumor size index (P2), and volumes receiving 30–50 Gy in OARs and the tumor (P3) as the three most weighted factors of the re-planning model. We set the cut-off for the re-planning modification requirement at 1. The model was consistent with R = 0.12P1 + 0.21P2 + 0.31P3, and it performed accurately that area under the test set characteristics curve (AUC) =0.826]. CONCLUSIONS: Our proposed method can help to reduce image re-examination during treatment, decrease toxicities in OARs, shorten the radiotherapy course, lessen oncologists’ efforts, and save medical resources. |
format | Online Article Text |
id | pubmed-8797880 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-87978802022-02-02 A model to guide the management and decision of re-planning during radiotherapy for cervical cancer Zhang, Wei Li, Xiuhua Lin, Tingting Ma, Fang Ma, Xiaoyu Wu, Xiaoli Sun, Yingming Sun, Xiaoge Transl Cancer Res Original Article BACKGROUND: To establish a model to predict whether re-planning is needed in the process of cervical cancer radiotherapy. METHODS: We collected the clinical indexes of 132 patients diagnosed with cervical cancer receiving concurrent chemotherapy and radiotherapy, including 33 factors about tumor markers [carcinoembryonic antigen (CEA), cancer antigen 125 (CA-125), squamous cell carcinoma antigen (SCC)], tumor volume, rectal volume, bladder volume, volumes receiving 30–50 Gy in organs-at-risk (OARs), and the maximum dose (Dmax) received by 1–2 cc in OARs. We established a multivariate model for re-planning evaluation via principal component analysis, and then verified the model based on the internal data. RESULTS: We identified the dose index (P1), tumor size index (P2), and volumes receiving 30–50 Gy in OARs and the tumor (P3) as the three most weighted factors of the re-planning model. We set the cut-off for the re-planning modification requirement at 1. The model was consistent with R = 0.12P1 + 0.21P2 + 0.31P3, and it performed accurately that area under the test set characteristics curve (AUC) =0.826]. CONCLUSIONS: Our proposed method can help to reduce image re-examination during treatment, decrease toxicities in OARs, shorten the radiotherapy course, lessen oncologists’ efforts, and save medical resources. AME Publishing Company 2021-12 /pmc/articles/PMC8797880/ /pubmed/35116382 http://dx.doi.org/10.21037/tcr-21-2545 Text en 2021 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/. |
spellingShingle | Original Article Zhang, Wei Li, Xiuhua Lin, Tingting Ma, Fang Ma, Xiaoyu Wu, Xiaoli Sun, Yingming Sun, Xiaoge A model to guide the management and decision of re-planning during radiotherapy for cervical cancer |
title | A model to guide the management and decision of re-planning during radiotherapy for cervical cancer |
title_full | A model to guide the management and decision of re-planning during radiotherapy for cervical cancer |
title_fullStr | A model to guide the management and decision of re-planning during radiotherapy for cervical cancer |
title_full_unstemmed | A model to guide the management and decision of re-planning during radiotherapy for cervical cancer |
title_short | A model to guide the management and decision of re-planning during radiotherapy for cervical cancer |
title_sort | model to guide the management and decision of re-planning during radiotherapy for cervical cancer |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797880/ https://www.ncbi.nlm.nih.gov/pubmed/35116382 http://dx.doi.org/10.21037/tcr-21-2545 |
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