Evidence map›Paper›PMID 41025051›Full record

ArticlePeerJ2025

Establishment and verification of a nomogram model based on the inflammatory indicators of patients with cervical cancer for predicting the risk of their lymph node metastasis.

Liyun Song, Kaiyun Qin, Suning Bai, Qi Wu, Jing Zhao, Jie Qi, Junmei Zhang, Yazhuo Wang, Yuan Zhang, Ren Xu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Liyun SongDepartment of Gynecology, Hebei General Hospital, Hebei Medical University, Shijiazhuang, Hebei, China.
Kaiyun QinDepartment of Gynecology, Hebei General Hospital, Hebei Medical University, Shijiazhuang, Hebei, China.
Suning BaiDepartment of Gynecology, Hebei General Hospital, Hebei Medical University, Shijiazhuang, Hebei, China.
Qi WuDepartment of Gynecology, Hebei General Hospital, Hebei Medical University, Shijiazhuang, Hebei, China.
Jing ZhaoDepartment of Gynecology, Hebei General Hospital, Hebei Medical University, Shijiazhuang, Hebei, China.
Jie QiDepartment of Gynecology, Hebei General Hospital, Hebei Medical University, Shijiazhuang, Hebei, China.
Junmei ZhangDepartment of Gynecology, Hebei General Hospital, Hebei Medical University, Shijiazhuang, Hebei, China.
Yazhuo WangDepartment of Gynecology, Hebei General Hospital, Hebei Medical University, Shijiazhuang, Hebei, China.
Yuan ZhangDepartment of Gynecology, Hebei General Hospital, Hebei Medical University, Shijiazhuang, Hebei, China.
Ren XuDepartment of Gynecology, Hebei General Hospital, Hebei Medical University, Shijiazhuang, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on inflammatory indicators, this study aimed to predict the risk of lymph node metastasis (LNM) in patients with cervical squamous cell carcinoma (CSCC) and establish a predictive nomogram model. Methods: This retrospective study analyzed the clinical data of 194 patients with stage IA2-IIA2 who underwent surgery at Hebei General Hospital (between January 2017 and August 2023). Patients were divided into two groups based on the presence of LNM or not. Clinical data of the participants were gathered and analyzed to compare the two groups. Logistic regression analysis was used to analyze the factors influencing LNM in patients with CSCC. R software was used to construct a nomogram model to predict LNM in patients with CSCC, and its accuracy was verified. Results: Squamous cell carcinoma antigen (SCC-Ag) level, D-dimer level, platelet (PLT) count, and platelet-to-lymphocyte ratio (PLR) index were significantly higher in patients with LNM than in those without LNM ( Conclusion: Establishing a nomogram model based on preoperative inflammatory indicators of patients with CSCC can accurately predict the risk of LNM, providing evidence for implementing a clinical diagnosis and treatment scheme.

Indexed as

Carcinoma, Squamous CellLymphatic MetastasisNomogramsUterine Cervical NeoplasmsAdultAgedAntigens, NeoplasmFemaleFibrin Fibrinogen Degradation ProductsHumansLogistic ModelsMiddle AgedPlatelet CountRetrospective StudiesRisk FactorsSerpinsAntigens, NeoplasmFibrin Fibrinogen Degradation ProductsSerpinssquamous cell carcinoma-related antigenCervical squamous cell carcinomaInflammatory indicatorLymphatic vascular space invasionLymph node metastasisNomogram modelPrediction

Identifiers

PMID41025051
PMCPMC12476862

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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.