Evidence map›Paper›PMID 42290019›Full record

ReviewInternational journal of cancer2026

Oncotype DX: Clinical Utility, Evidence, and Future Trends in Personalized Breast Cancer Management.

Robert Le Yang, Yiran Liang

Abstract readReview
In one paragraph

Review in International journal of cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Robert Le YangDepartment of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Yiran LiangDepartment of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China.ORCID https://orcid.org/0000-0002-2404-0408

Funding

China Postdoctoral Science Foundation 2024M762334National Natural Science Foundation of China 82573252Shandong Provincial Natural Science Foundation ZR2024MH242Special Foundation for Taishan Scholars tsqn202507348
6 · The paper itself

Abstract

The Oncotype DX assay has revolutionized the management of early-stage, hormone receptor-positive, HER2-negative breast cancer. Developed in 2004, it quantifies 21 genes to generate a recurrence score that predicts distant recurrence risk and guides adjuvant chemotherapy. Multiple studies have validated its reliability and clinical utility in enabling more precise risk stratification and individualized treatment planning, thereby minimizing unnecessary chemotherapy exposure and improving patient outcomes. Leading oncology organizations such as the American Society of Clinical Oncology and National Comprehensive Cancer Network have incorporated it into their clinical guidelines. Beyond its well-established role in adjuvant chemotherapy decision-making, Oncotype DX is increasingly being investigated in broader clinical contexts, including lymph node-positive breast cancer, neoadjuvant therapy, radiotherapy, and ductal carcinoma in situ. Ongoing research and technological advancements, such as artificial intelligence-based predictive models and novel biomarker identification, hold significant promise for further enhancing its predictive accuracy and expanding its applications. This review synthesizes current evidence supporting the clinical utility of Oncotype DX, discusses evolving applications, and highlights future directions for integrating this genomic tool into precision oncology practice.

Indexed as

Breast NeoplasmsGene Expression ProfilingPrecision MedicineBiomarkers, TumorChemotherapy, AdjuvantFemaleHumansNeoplasm Recurrence, LocalBiomarkers, Tumorbreast cancerchemotherapy benefitOncotype DXrecurrence riskrisk score

Identifiers

PMID42290019
PMCPMC13547999

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.