Evidence map›Paper›PMID 38752451›Full record

ArticleCancer medicine2024

Validating the 2023 FIGO staging system: A nomogram for endometrioid endometrial cancer and adenocarcinoma.

Yifan Feng, Fulu Miao, Yuyang Li, Min Li, Yunxia Cao

Abstract readValidation Study
In one paragraph

Article in Cancer medicine, 2024. 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

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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

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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.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yifan FengDepartment of Gynecology Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Fulu MiaoDepartment of Gynecology Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Yuyang LiDepartment of Gynecology Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Min LiDepartment of Gynecology Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.ORCID 0000-0003-3665-9600
Yunxia CaoDepartment of Gynecology Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.

Funding

Anhui Provincial Department of Science and Technology 202204295107020029
6 · The paper itself

Abstract

backgroundTo find the factors impacting overall survival (OS) prognosis in patients with endometrioid endometrial carcinoma (EEC) and adenocarcinoma and to establish a nomogram model to validate the 2023 International Federation of Obstetrics and Gynecology (FIGO) staging system for endometrial cancer.

methodsData were obtained from the Surveillance, Epidemiology, and End Results (SEER) training cohort. An independent validation cohort was obtained from the First Affiliated Hospital of Anhui Medical University between 2008 and 2023. Cox regression analysis identified independent prognostic factors for OS in EEC and adenocarcinoma patients. A nomogram predicting OS was developed and validated utilizing the C-index, calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). The relationship between the tumor grade and prognosis of EEC and adenocarcinoma was quantified using net reclassification improvement (NRI), propensity score matching (PSM), and Kaplan-Meier curves.

resultsCox regression analysis identified age, race, marital status, tumor grade, tumor stage, tumor size, and chemotherapy as independent prognostic factors for OS. A nomogram for predicting OS was developed based on these factors. The C-indexes for the OS nomogram was 0.743 and 0.720 for the SEER training set and external validation set, respectively. The area under the ROC (AUC) for the OS nomogram was 0.755, 0.757, and 0.741 for the SEER data subsets and 0.844, 0.719, and 0.743 for the external validation subsets. Calibration plots showed high concordance between the nomogram-predicted and observed OS. DCA also demonstrated the clinical utility of the OS nomogram. NRI, PSM, and survival analyses revealed that tumor grade was the most important histopathological factor for EEC and adenocarcinoma prognosis.

conclusionSeven independent prognostic variables for the OS of patients with EEC and adenocarcinoma were identified. The established OS nomogram has good predictive ability and clinical utility and validates the 2023 endometrial cancer FIGO staging system.

Indexed as

AdenocarcinomaCarcinoma, EndometrioidEndometrial NeoplasmsNeoplasm StagingNomogramsSEER ProgramAdultAgedFemaleHumansKaplan-Meier EstimateMiddle AgedNeoplasm GradingPrognosisROC Curveendometrial cancerFIGOgradenomogramoverall survival

Identifiers

PMID38752451
PMCPMC11097244

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