Evidence map›Paper›PMID 36717897›Full record

ArticleJournal of ovarian research2023

Prognostic significance and risk factors for pelvic and para-aortic lymph node metastasis in type I and type II ovarian cancer: a large population-based database analysis.

Hailin Yu, Jieyu Wang, Beibei Wu, Jun Li, Ruifang Chen

Abstract read
In one paragraph

Article in Journal of ovarian research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  9. Molecular image-guided surgery in gynaecological cancer: where do we stand?European journal of nuclear medicine and molecular imaging · 2024
    Review
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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

5 authors.

Hailin YuObstetrics and Gynecology Hospital, Fudan University, Shanghai, China.
Jieyu WangObstetrics and Gynecology Hospital, Fudan University, Shanghai, China.
Beibei WuObstetrics and Gynecology Hospital, Fudan University, Shanghai, China.
Jun LiObstetrics and Gynecology Hospital, Fudan University, Shanghai, China.
Ruifang ChenObstetrics and Gynecology Hospital, Fudan University, Shanghai, China. chenruifang1570@fckyy.org.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo compare the prognosis of lymphatic metastasis in type I and type II epithelial ovarian cancer (OC) and to identify the risk factors for pelvic lymph node metastases (PLNs) and para-aortic lymph node metastases (PALNs).

methodsPatients diagnosed with epithelial OC were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival (OS) and cancer-specific survival (CSS) were estimated. The Cox proportional hazards regression model was used to identify independent predictors of survival.

resultsA total of 11,275 patients with OC were enrolled, including 31.2% with type I and 68.8% with type II. Type II and high tumour stage were risk factors for lymph node involvement (p < 0.05). The overall rate of lymph node metastasis in type I was 11.8%, and that in type II was 36.7%. In the type I group, the lymph node metastasis rates in stages T1, T2, T3 and T

conclusionsThe clinical characteristics and prognoses of patients with type I and type II OC differed greatly. Patients with type II and higher tumour stages had poorer prognoses. Type I with PALN metastasis and type II with PLN metastasis indicated a worse prognosis. Patients with stage TI did not require lymph node dissection, especially in the type I group.

Indexed as

Lymph NodesOvarian NeoplasmsFemaleHumansLymphatic MetastasisLymph Node ExcisionPrognosisRetrospective StudiesRisk FactorsLymph node metastasisOvarian cancerPara-aortic lymph nodesPelvic lymph nodesPrognosisRisk factorsTwo-tier classification system

Identifiers

PMID36717897
PMCPMC9885671

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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.