Evidence map›Paper›PMID 40784722›Full record

ArticleJournal of gynecologic oncology2026

Clinical analysis of the impact of systematic pelvic and para-aortic lymphadenectomy on the prognosis of patients with early-stage ovarian cancer (stage IA-IIA): a propensity score matching study.

Siyuan Zeng, Simin Xiao, Mingzhu Jia, Zhao Hu, Lin Changsheng, Lei Yu, Huiling Chen, Xue Xiao

Abstract read
In one paragraph

Article in Journal of gynecologic 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.

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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

8 authors.

Siyuan Zeng *Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.ORCID 0000-0001-7334-8284
Simin Xiao *Department of Radiology, Xin Du Hospital of Traditional Chinese Medicine, Chengdu, China.ORCID 0009-0009-9725-6152
Mingzhu Jia *Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.ORCID 0000-0003-0873-6226
Zhao HuDepartment of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.ORCID 0000-0001-8658-8180
Lin ChangshengDepartment of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.ORCID 0009-0007-2279-2714
Lei YuDepartment of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.ORCID 0009-0009-6012-9870
Huiling ChenDepartment of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.ORCID 0000-0002-8379-8649
Xue XiaoDepartment of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.ORCID 0009-0005-1736-4833

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe role of systematic pelvic and para-aortic lymphadenectomy (PPAL) in completion staging surgery for early-stage (stage I-IIA) ovarian cancer (EOC) remains controversial. This study evaluates the impact of PPAL on the prognosis of EOC patients.

methodsA retrospective cohort study was conducted using data from the Surveillance, Epidemiology, and End Results database. Patients with EOC (stage I-IIA) were included. Propensity score matching (PSM) was used at a 1:1 ratio based on age, marital status, race, tumor grade, histological type, FIGO stage, and postoperative adjuvant therapy. Post-matching overall survival (OS) and cancer-specific survival (CSS) were compared between the systematic PPAL group (pathological staging) and the non-lymphadenectomy group (clinical staging).

resultsAfter PSM, no significant differences were observed in OS (p=0.140) and CSS (p=0.066) between the two groups. Subgroup analysis showed that for tumor grade III patients, the pathological staging group had significantly higher OS (p=0.028) and CSS (p=0.010) than the clinical staging group. Multivariate Cox regression indicated that tumor grade III was an independent prognostic factor for OS (p=0.006) and CSS (p=0.020).

conclusionSystematic PPAL does not significantly improve survival in EOC patients. However, for tumor grade III patients, the pathological staging group demonstrates significantly better prognosis, offering a more personalized alternative to routine staging surgery, which requires further validation through prospective trials.

Indexed as

Carcinoma, Ovarian EpithelialLymph Node ExcisionOvarian NeoplasmsAdultAgedFemaleHumansMiddle AgedNeoplasm StagingPelvisPrognosisPropensity ScoreRetrospective StudiesSEER ProgramLymphadenectomyOvarian NeoplasmsPrognosisPropensity ScoreRetrospective Studies

Identifiers

PMID40784722
PMCPMC12867663

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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.