Evidence map›Paper›PMID 40116474›Full record

ArticleCancer medicine2025

Nomogram Development for Assessing Oncotype DX Recurrence Scores in Breast Cancer: A Chinese Population Study.

Jiayin Song, Lin Yang, Zhengqi Feng, Liyu Jiang

Abstract read
In one paragraph

Article in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Jiayin SongDepartment of Breast Surgery, General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.ORCID https://orcid.org/0009-0004-7718-2946
Lin YangDepartment of Breast Surgery, General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Zhengqi FengDepartment of Breast Surgery, General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Liyu JiangDepartment of Breast Surgery, General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer (BC) is the most prevalent cancer among women worldwide, with increasing incidence rates, particularly in China. Given the high costs of Oncotype DX (ODX) testing, which predicts recurrence scores (RSs) on the basis of gene expression, developing a nomogram utilizing clinicopathological variables may provide an accessible alternative for risk stratification.

methodsWe conducted a retrospective analysis of 703 estrogen receptor (ER)-positive, HER2-negative T1-3N0M0 BC patients who underwent ODX testing at Qilu Hospital. A nomogram was developed using multivariate logistic regression to predict low and high RSs in the group. Model performance was validated by receiver operating characteristic curve, calibration curve, and decision curve analysis.

resultsMultivariate analysis revealed that older age, lower histologic grade, a higher ER expression level, a higher proportion of cells expressing progesterone receptor, and a lower proportion of cells expressing Ki-67 were significantly associated with a patient being in the low-risk subgroup. A nomogram was then developed using these variables to predict the RS, with an area under the curve (AUC) of 0.811 (95% confidence interval [CI] = 0.772-0.850) in the development group and 0.794 (95% CI = 0.737-0.851) in the validation group. Calibration and decision curve analyses further confirmed the nomogram's clinical utility. Moreover, a comparison between the TAILORx-nomogram and our nomogram was conducted, which proved that our nomogram has better predictive accuracy and reliability in Chinese BC patients.

conclusionWe present the first nomogram for predicting the RS in Chinese patients with BC on the basis of clinicopathological factors. This model could aid in identifying patients who may not need ODX testing and serve as a cost-effective alternative for those unable to access ODX, thereby optimizing treatment decisions and enhancing patient management in resource-limited settings.

Indexed as

Biomarkers, TumorBreast NeoplasmsNeoplasm Recurrence, LocalNomogramsAdultAgedChinaEast Asian PeopleErb-b2 Receptor Tyrosine KinasesFemaleGene Expression ProfilingHumansMiddle AgedReceptors, EstrogenReceptors, ProgesteroneRetrospective StudiesBiomarkers, TumorErb-b2 Receptor Tyrosine KinasesReceptors, EstrogenReceptors, Progesteronebreast cancernomogramOncotype DXpredictionrecurrence

Identifiers

PMID40116474
PMCPMC11926913

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.