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Record W4403902509 · doi:10.14740/jocmr5237

The Effects of Preoperative Serum Carcinoembryonic Antigen, Cancer Antigen 15-3 and Cancer Antigen 125 on the Prognosis of Breast Cancer Patients With Different Molecular Subtypes

2024· article· en· W4403902509 on OpenAlexvenueno aff
Yipala Yilihamu, Lei Wang, Tao Ma, Ting Zhao, Yan Wang, Sun Gang

Bibliographic record

VenueJournal of Clinical Medicine Research · 2024
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsnot available
FundersNatural Science Foundation of XinjiangNational Natural Science Foundation of ChinaScience and Technology Department of Xinjiang Uygur Autonomous Region
KeywordsCarcinoembryonic antigenMedicineCancer antigenBreast cancerAntigenCancerOncologyInternal medicineCancer researchImmunology

Abstract

fetched live from OpenAlex

Background: The aim of the study was to investigate the relationship between serum carcinoembryonic antigen (CEA), cancer antigen 15-3 (CA15-3), and cancer antigen 125 (CA125) levels and traditional clinicopathological factors in patients with early invasive breast cancer in Xinjiang, and the influence of those serum markers on the prognosis of patients with different molecular subtypes. Methods: We conducted a retrospective study based on the clinical data of 2,940 invasive breast cancer patients who were diagnosed and treated at the Affiliated Cancer Hospital of Xinjiang Medical University from 2015 to 2019. Firstly, in this study, preoperative serum CEA, CA15-3, and CA125 levels were divided into elevated and normal groups based on the optimal cut-off values. Secondly, Chi-square test was used to analyze the correlation between the elevated and normal groups of CEA, CA15-3, and CA125 and traditional clinicopathological factors. Finally, Cox regression model was also used to evaluate the effect of preoperative CEA, CA15-3, and CA125 elevated groups on the prognosis of patients with different molecular subtypes compared with normal groups. Results: The optimal cut-off values for preoperative CEA, CA15-3, and CA125 were 4.32 ng/mL, 23.10 U/mL and 29.80 U/mL, respectively. The elevated group of preoperative CEA, CA15-3, and CA125 patients usually had larger tumors (tumor size: T2-4), later clinical staging (TNM stage: II-III), and higher histological grading (histological grade: II-III). Univariate analysis showed that the overall survival (OS) of preoperative CEA, CA15-3, and CA125 patients in the elevated group was lower than that in the normal group (P < 0.0001), the 5-year OS was 76.63% vs. 95.35%, 74.34% vs. 95.60%, and 83.73% vs. 94.71%, respectively. Multivariate analysis revealed that for the luminal A, compared with the normal group, the hazard ratios (HRs) of preoperative CEA, CA15-3, and CA125 elevated groups were 6.475 (95% confidence interval (CI): 1.850 - 22.66), 5.192 (95% CI: 1.153 - 23.38), and 7.294 (95% CI: 1.152 - 46.18), respectively. However, for the luminal B, elevated levels of CEA, CA15-3, and CA125 were not independent prognostic factors for OS. For the human epidermal growth factor receptor-2 (HER2)-enriched, the HR of preoperative CA15-3 elevated group was 3.155 (95% CI: 1.325 - 7.509). Additionally, for the triple-negative breast cancer, the HR of preoperative CEA elevated group was 2.390 (95% CI: 1.247 - 4.583). Conclusions: High levels of CEA, CA15-3, and CA125 were positively correlated with increased tumor load. Preoperative CEA, CA15-3, and CA125 levels may have different prognostic effects on patients with different molecular subtypes. Particularly, preoperative elevated levels of CEA have a significant adverse impact on the prognosis of luminal A and triple-negative patients, while preoperative elevated levels of CA15-3 have an adverse effect on the prognosis of luminal A and HER-positive patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.483
Teacher spread0.411 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2024
Admission routes1
Has abstractyes

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