Machine learning identifies the association between second primary malignancies and postoperative radiotherapy in young-onset breast cancer patients

YWBC patients receiving PORT had a greater risk of developing SPSMs (thyroid, lung, and breast cancer), indicating the necessity of long-term surveillance of these patients. Standard adjuvant PORT should not be recommended for breast cancer patients with favorable histology and a low risk of relapse.

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Publication Details

Journal
PLoS ONE
Published
2025-02-06
DOI
https://doi.org/10.1371/journal.pone.0316722
Citations
1
Primary Topic
Breast Cancer Treatment Studies
Type
article
Field-Weighted Citation Impact
0.94
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article

Machine learning identifies the association between second primary malignancies and postoperative radiotherapy in young-onset breast cancer patients

Peiyuan Huang, Yulin Lai
1 citations
PLoS ONE
Breast Cancer Treatment Studies
0.94
article

Machine learning identifies the association between second primary malignancies and postoperative radiotherapy in young-onset breast cancer patients

Peiyuan Huang, Yulin Lai
article en
1 citations

Abstract

YWBC patients receiving PORT had a greater risk of developing SPSMs (thyroid, lung, and breast cancer), indicating the necessity of long-term surveillance of these patients. Standard adjuvant PORT should not be recommended for breast cancer patients with favorable histology and a low risk of relapse.

PLoS ONEVol. 20(2)
ShenZhen People’s Hospital (CN), Gaozhou People's Hospital (CN)
No poverty
Openalex Percentile: Top 29%
Breast Cancer Treatment Studies
0.94
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