Evidence map›Paper›PMID 34975754›Full record

ArticleFrontiers in endocrinology2021

Effects of Metabolic Syndrome and Its Components on the Prognosis of Endometrial Cancer.

Xiao Yang, Xingchen Li, Yangyang Dong, Yuan Fan, Yuan Cheng, Lirong Zhai, Shuyi Zhang, Jingyi Zhou, Jianliu Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 3 pooled it
5.3field-weighted citation impact, top 3% of its field
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

40 citing papers in PubMed, 3 syntheses or guidelines pooled it, 60 citations in OpenAlex.

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  12. Multifactorial construction of low-grade and high-grade endometrial cancer recurrence prediction models.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
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  20. circRNAs in Endometrial Cancer-A Promising Biomarker: State of the Art.International journal of molecular sciences · 2024
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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

9 authors at 2 institutions in 1 country.

Xiao YangDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.
Xingchen LiDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.
Yangyang DongDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.
Yuan FanDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.
Yuan ChengDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.
Lirong ZhaiDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.
Shuyi ZhangDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.
Jingyi ZhouDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.
Jianliu WangDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.
Peking University People's Hospital · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the effects of metabolic syndrome (MetS) on the prognosis of endometrial cancer (EC) and to identify key components of MetS associated with EC. Methods: A total of 506 patients surgically diagnosed with EC were analyzed in this study. These patients were diagnosed with EC in the Department of Obstetrics and Gynecology at the People's Hospital of Peking University between 2010 and 2016. The follow-up time was cut off at December 2019. MetS was characterized based on standards provided by the Chinese Diabetes Society in 2004. Results: Among the 506 EC patients analyzed, 153 patients were diagnosed with MetS. MetS patients were more likely to be older and postmenopausal. MetS was positively related to tumor grade, stage, LNM, LVSI, and MI. The univariate analysis showed that MetS was closely related to the OS (HR = 2.14; P = 0.032) and RFS (HR = 1.80; P = 0.045) of EC patients. K-M analysis also indicated that EC patients with MetS had shorter OS and RFS than EC patients without MetS. More specifically, patients that had ≥3 components showed a worse outcome compared with patients only having 0 or 1-2 components (P <0.05). In the multivariate-adjust model, after adjusting for age, histotype, tumor grade, and stage, HDL-C was found to be associated with increased risk of death related to EC (HR = 2.2, P = 0.034). However, MetS did not significantly correlate with this. ROC analysis revealed that the area under the ROC curve of combined factors (HDL-C + grade + stage) was better than traditional stage or grade at 1-, 3-, and 5-year survival rates. From this, a nomogram based on HDL-C, grade, and stage was constructed to predict survival of EC patients. Calibration curve analysis and decision curve analysis (DCA) showed the nomogram we constructed could better predict the survival of EC patients. Conclusion: MetS is closely related to poor prognosis in EC patients. The prevalence of individual MetS components increase with worse outcomes in EC patients. A nomogram based on HDL-C, grade, and stage has good ability to predict survival of EC patients.

Indexed as

Body Mass IndexDyslipidemiasEndometrial NeoplasmsFemaleHumansHypertensionLymphatic MetastasisMetabolic SyndromeMiddle AgedNeoplasm StagingNomogramsOdds RatioPrognosisRetrospective StudiesROC CurveSurvival Rateclinicopathological characteristicsendometrial cancermetabolic syndromeoverall survivalrecurrence-free survival

Identifiers

PMID34975754
PMCPMC8717682
OpenAlexW4200164224

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.