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A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer
PURPOSE: The impact of progesterone receptor (PR) status on the prognosis of breast cancer after isolated locoregional recurrence (ILRR) remains unclear. This study evaluated the impact of clinicopathologic factors, including PR status of ILRR, on distant metastasis (DM) after ILRR. METHODS: We retr...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10147732/ https://www.ncbi.nlm.nih.gov/pubmed/36869991 http://dx.doi.org/10.1007/s10549-023-06901-7 |
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author | Murata, Takeshi Yoshida, Masayuki Shiino, Sho Ogawa, Ayumi Watase, Chikashi Satomi, Kaishi Jimbo, Kenjiro Maeshima, Akiko Iwamoto, Eriko Takayama, Shin Suto, Akihiko |
author_facet | Murata, Takeshi Yoshida, Masayuki Shiino, Sho Ogawa, Ayumi Watase, Chikashi Satomi, Kaishi Jimbo, Kenjiro Maeshima, Akiko Iwamoto, Eriko Takayama, Shin Suto, Akihiko |
author_sort | Murata, Takeshi |
collection | PubMed |
description | PURPOSE: The impact of progesterone receptor (PR) status on the prognosis of breast cancer after isolated locoregional recurrence (ILRR) remains unclear. This study evaluated the impact of clinicopathologic factors, including PR status of ILRR, on distant metastasis (DM) after ILRR. METHODS: We retrospectively identified 306 patients with ILRR diagnosed at the National Cancer Center Hospital between 1993 and 2021 from the database. Cox proportional hazards analysis was performed to examine factors associated with DM after ILRR. We developed a risk prediction model based on the number of detected risk factors and estimated survival curves using the Kaplan–Meier method. RESULTS: During a median follow-up time of 4.7 years after ILRR diagnosis, 86 patients developed DM, and 50 died. Multivariate analysis revealed that seven risk factors were associated with poor distant metastasis-free survival (DMFS): estrogen receptor-positive/PR-negative/human epidermal growth factor receptor 2-negative ILRR, short disease-free interval, recurrence site other than ipsilateral breast, no-resection of ILRR tumor, chemotherapy for the primary tumor, nodal stage in the primary tumor, and no endocrine therapy for ILRR. The predictive model classified patients into 4 groups based on the number of risk factors: low-, intermediate-, high-, and the highest-risk groups with 0 to 1, 2, 3 to 4, and 5 to 7 factors, respectively. This revealed significant variation in DMFS among the groups. A higher number of the risk factors was associated with poorer DMFS. CONCLUSION: Our prediction model, which considered the ILRR receptor status, may contribute to the development of a treatment strategy for ILRR. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10549-023-06901-7. |
format | Online Article Text |
id | pubmed-10147732 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-101477322023-04-30 A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer Murata, Takeshi Yoshida, Masayuki Shiino, Sho Ogawa, Ayumi Watase, Chikashi Satomi, Kaishi Jimbo, Kenjiro Maeshima, Akiko Iwamoto, Eriko Takayama, Shin Suto, Akihiko Breast Cancer Res Treat Clinical Trial PURPOSE: The impact of progesterone receptor (PR) status on the prognosis of breast cancer after isolated locoregional recurrence (ILRR) remains unclear. This study evaluated the impact of clinicopathologic factors, including PR status of ILRR, on distant metastasis (DM) after ILRR. METHODS: We retrospectively identified 306 patients with ILRR diagnosed at the National Cancer Center Hospital between 1993 and 2021 from the database. Cox proportional hazards analysis was performed to examine factors associated with DM after ILRR. We developed a risk prediction model based on the number of detected risk factors and estimated survival curves using the Kaplan–Meier method. RESULTS: During a median follow-up time of 4.7 years after ILRR diagnosis, 86 patients developed DM, and 50 died. Multivariate analysis revealed that seven risk factors were associated with poor distant metastasis-free survival (DMFS): estrogen receptor-positive/PR-negative/human epidermal growth factor receptor 2-negative ILRR, short disease-free interval, recurrence site other than ipsilateral breast, no-resection of ILRR tumor, chemotherapy for the primary tumor, nodal stage in the primary tumor, and no endocrine therapy for ILRR. The predictive model classified patients into 4 groups based on the number of risk factors: low-, intermediate-, high-, and the highest-risk groups with 0 to 1, 2, 3 to 4, and 5 to 7 factors, respectively. This revealed significant variation in DMFS among the groups. A higher number of the risk factors was associated with poorer DMFS. CONCLUSION: Our prediction model, which considered the ILRR receptor status, may contribute to the development of a treatment strategy for ILRR. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10549-023-06901-7. Springer US 2023-03-04 2023 /pmc/articles/PMC10147732/ /pubmed/36869991 http://dx.doi.org/10.1007/s10549-023-06901-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . |
spellingShingle | Clinical Trial Murata, Takeshi Yoshida, Masayuki Shiino, Sho Ogawa, Ayumi Watase, Chikashi Satomi, Kaishi Jimbo, Kenjiro Maeshima, Akiko Iwamoto, Eriko Takayama, Shin Suto, Akihiko A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer |
title | A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer |
title_full | A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer |
title_fullStr | A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer |
title_full_unstemmed | A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer |
title_short | A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer |
title_sort | prediction model for distant metastasis after isolated locoregional recurrence of breast cancer |
topic | Clinical Trial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10147732/ https://www.ncbi.nlm.nih.gov/pubmed/36869991 http://dx.doi.org/10.1007/s10549-023-06901-7 |
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