Evidence map›Paper›PMID 37293802›Full record

Trial reportJournal of gynecologic oncology2023

Development and validation of a prognostic model based on metabolic risk score to predict overall survival of endometrial cancer in Chinese patients.

Xingchen Li, Xiao Yang, Yuan Cheng, Yangyang Dong, Jingyuan Wang, Jianliu Wang

Abstract readRandomized Controlled TrialValidation Study
In one paragraph

Trial report in Journal of gynecologic oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

6 authors.

Xingchen Li *Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.ORCID 0000-0003-3373-1670
Xiao Yang *Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.ORCID 0000-0002-5172-8267
Yuan ChengDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.ORCID 0000-0002-4476-7241
Yangyang DongDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.ORCID 0000-0002-1142-9131
Jingyuan WangDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.ORCID 0000-0002-0599-955X
Jianliu WangDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.ORCID 0000-0001-8932-317X

Funding

NSFC 82103419NSFC 82203568PKUPH RDJP2022-09PKUPH RDY2021-13PKUPH RS2021-05
6 · The paper itself

Abstract

objectiveMetabolic syndrome (MetS) is closely related to the increased risk and poor prognosis of endometrial cancer (EC). The purpose of this study was to analyze the relationship between metabolic risk score (MRS) and EC, and establish a predictive model to predict the prognosis of EC.

methodsA retrospective study was designed of 834 patients admitted between January 2004 to December 2019. Univariate and multivariate Cox analysis were performed to screen independent prognostic factors for overall survival (OS). A predictive nomogram is built based on independent risk factors for OS. Consistency index (C-index), calibration plots and receiver operating characteristic curve were used to evaluate the predictive accuracy of the nomogram.

resultsThe patients were randomly divided into training cohort (n=556) and validation cohort (n=278). The MRS of EC patients, ranging from -8 to 15, was calculated. Univariate and multivariate Cox analysis indicated that age, MRS, FIGO stage, and tumor grade were independent risk factors for OS (p<0.05). The Kaplan-Meier analysis demonstrated that EC patients with low score showed a better prognosis in OS. Then, a nomogram was established and validated based on the above four variables. The C-index of nomogram were 0.819 and 0.829 in the training and validation cohorts, respectively. Patients with high-risk score had a worse OS according to the nomogram.

conclusionWe constructed and validated a prognostic model based on MRS and clinical prognostic factors to predict the OS of EC patients accurately, which may help clinicians personalize prognostic assessments and effective clinical decisions.

Indexed as

East Asian PeopleEndometrial NeoplasmsFemaleHumansPrognosisRetrospective StudiesRisk FactorsEndometrial CancerMetabolic SyndromeNomogramPrognosisRisk factor

Identifiers

PMID37293802
PMCPMC10627753

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Registered trials

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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.