Evidence map›Paper›PMID 42131423›Full record

ArticleAnnals of surgical treatment and research2026

Prognostic value of carcinoembryonic antigen kinetics in predicting distant metastatic recurrence of breast cancer: a multicenter cohort study.

Bong Kyun Kim, Dooreh Kim, Jong Min Baek, Yong Hwa Eom, Young-Joon Kang, Jiyoung Rhu, Juneyoung Ahn, Ye Won Jeon, Woo Young Sun

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Article in Annals of surgical treatment and research, 2026. 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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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Bong Kyun KimDepartment of Surgery, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0002-3845-9584
Dooreh KimDepartment of Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0003-1758-4439
Jong Min BaekDepartment of Surgery, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0001-5260-3821
Yong Hwa EomDepartment of Surgery, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0002-1799-5214
Young-Joon KangDepartment of Surgery, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0002-6546-0513
Jiyoung RhuDepartment of Surgery, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0002-9173-5445
Juneyoung AhnDepartment of Surgery, Uijeongbu St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0002-6840-4496
Ye Won JeonDepartment of Surgery, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0002-4434-4855
Woo Young SunDepartment of Surgery, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0002-5447-4266

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Distant metastasis of breast cancer significantly affects the prognosis. Serum markers such as CEA and cancer antigen (CA) 15-3 are used for surveillance. However, the nonspecificity and nonmalignant elevation of CEA limit its absolute value in predicting metastatic recurrence. We reevaluated the clinical value of CEA kinetics in predicting metastatic recurrence in breast cancer. Methods: In this multicenter retrospective cohort study, we utilized electronic medical record data from eight institutions (2008-2023), including 4,872 surgically treated patients with invasive breast cancer. Novel CEA kinetic indices were defined. Predictive capabilities were assessed using logistic regression, Kaplan-Meier survival curves, and Cox proportional hazards models. Results: CEA velocity (vCEA) and last-interval vCEA (vCEA-L) showed higher accuracy and sensitivity in predicting distant metastasis than absolute CEA indices. All tumor marker indices were independent predictors; vCEA, vCEA-L, and maximum vCEA (vCEAmax) showed the highest association. In the 5-year distant disease-free survival analysis of patients, vCEA showed the most significant difference based on whether its cutoff value was exceeded (84.1% Conclusion: Analysis of dynamic CEA changes, particularly velocity-based indices, offers superior predictive power than the static-based CEA indices for metastatic recurrence in breast cancer. These kinetic markers enhance prognostic accuracy when combined with CA 15-3. Future research should integrate these markers with imaging, liquid biopsy, and artificial intelligence for personalized follow-up.

Indexed as

Breast neoplasmsCarcinoembryonic antigenNeoplasm metastasisPrognosisTumor biomarkers

Identifiers

PMID42131423
PMCPMC13161727

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