Evidence map›Paper›PMID 39913454›Full record

ArticlePloS one2025

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

Yulin Lai, Peiyuan Huang

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Yulin LaiDepartment of Urology, The People's Hospital of Longhua, Shenzhen, P. R. China.
Peiyuan HuangDepartment of Pharmacy, Gaozhou People's Hospital, Maoming, P. R. China.ORCID https://orcid.org/0000-0003-1954-756X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA second primary malignant tumor is one of the most important factors affecting the long-term survival of young women with breast cancer (YWBC). As one of the main treatments for breast cancer YWBC patients, postoperative radiotherapy (PORT) may increase the risk of second primary malignancy (SPM).

methodsMachine learning components, including ridge regression, XGBoost, k-nearest neighbor, light gradient boosting machine, logistic regression, support vector machine, neural network, and random forest, were used to construct a predictive model and identify the risk factors for SPMs with data from the Surveillance, Epidemiology and End Results. Multivariate logistic regression analysis was used to assess the risk of SPM associated with PORT. The cumulative incidence of SPMs was determined by competing risk regression analysis.

resultsAmong the 44223 YWBC patients included in our study, 3017 developed SPMs. Among all the clinical characteristics, PORT was the most common SPM. YWBC patients receiving PORT had significantly greater risks of second primary solid malignancies (SPSMs, RR = 1.61), including breast cancer (RR = 1.89), lung cancer (RR = 2.12) and thyroid cancer (RR = 1.48), but not second primary hematologic malignancies (RR = 1.32; 0.94-1.88). SPSMs were more common in YWBC individuals who were black, had a lower median household income and had fewer lymph nodes examined. Additionally, we developed a prediction nomogram with an area under the curve of 0.75 to assess the likelihood of developing SPMs.

conclusionYWBC 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.

Indexed as

Breast NeoplasmsMachine LearningNeoplasms, Second PrimaryAdultFemaleHumansIncidenceMiddle AgedRadiotherapy, AdjuvantRisk FactorsSEER ProgramYoung Adult

Identifiers

PMID39913454
PMCPMC11801551

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