Evidence map›Paper›PMID 42369731›Full record

ArticleTherapeutic advances in medical oncology2026

Exploring the molecular classification-based personalized treatment decision-making in FIGO stage I-III endometrial carcinoma after surgery: a population-based real-world study.

Lingxia Xin, Kang Ren, Zihan Yan, Yunlong Sheng, Yaqi Wang, Yihan Zhang, Xiaorong Hou, Huanwen Wu, Fuquan Zhang

Abstract read
In one paragraph

Article in Therapeutic advances in medical oncology, 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

9 authors.

Lingxia XinDepartment of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0009-0009-1499-8012
Kang RenDepartment of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Zihan YanDepartment of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Yunlong ShengDepartment of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Yaqi WangDepartment of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Yihan ZhangDepartment of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Xiaorong HouDepartment of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing 100730, China.ORCID https://orcid.org/0000-0002-4903-9489
Huanwen WuDepartment of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing 100730, China.
Fuquan ZhangDepartment of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing 100730, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Robust real-world evidence supporting the clinical utility of molecular classification in endometrial carcinoma (EC) remains limited. Objectives: To investigate the molecular classification-based personalized treatment decision-making for EC by presenting real-world data, including survival outcomes and failure patterns. Methods: This retrospective cohort study included patients with International Federation of Gynecology and Obstetrics (FIGO) stage I-III EC who underwent initial surgery and had available molecular classification at Peking Union Medical College Hospital, between December 2017 and April 2025. The primary endpoint was disease-free survival (DFS). We evaluated survival outcomes, visualized dynamic annual hazard rates (AHRs), and compared failure patterns across subgroups. Independent prognostic factors were identified using Cox regression analyses. Results: Between December 2017 and April 2025, 267 eligible patients were evaluated. The median age was 55 years, and the median follow-up was 31.10 months. NSMP was the most common molecular subtype (46.8%), followed by MMRd (27.7%), POLEmut (13.1%), and p53abn (12.4%). Endometrioid carcinoma G1-2 was the predominant histological type overall (74.5%). According to FIGO, the 2009 criteria, the stage distribution was as follows: IA (66.7%), IB (20.6%), II (4.5%), and III (12.2%). Restaging under the FIGO 2023 system resulted in upstaging in 20.2% and downstaging in 2.6% of patients. Most patients (56.6%) were classified as low-risk per the ESGO-ESTRO-ESP 2025 risk classification. Although observation alone was used in 45.7% of the entire cohort, intensified treatment was administered to 33.3% of the p53abn subgroup. Excellent 3-year overall survival (OS, 99.2%) and (DFS, 88.4%) were observed in the entire cohort. The p53abn group exhibited the highest recurrence rate (30.3%), frequently presenting as simultaneous multi-site recurrences. No recurrences were observed in the POLEmut group. The p53abn group exhibited the highest recurrence hazard rate (peak: 2.2% at 16.8 months), followed by the MMRd group (peak: 0.8% at 14.0 months) and the NSMP group (peak: 0.3% at 21.0 months). Both the ESGO-ESTRO-ESP 2025 risk classification and FIGO 2023 staging were independent prognostic factors for recurrence. Conclusion: This study provides evidence that molecular classification-based personalized treatment decision-making is feasible and can yield excellent survival outcomes in patients with stage I-III EC.

Indexed as

endometrial carcinomaFIGO 2023managementmolecular classificationrisk classification

Identifiers

PMID42369731
PMCPMC13305793

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.