Evidence map›Paper›PMID 41774295›Full record

ArticleInsights into imaging2026

Prognostic value of Node-RADS scoring in stage IIICr cervical cancer: development and validation of novel nomograms.

Li Jiang, Shanshan Ma, Qinghua Du, Jun Lv, Minghua Guo, Huisi Lin, Yanmei Que, Ting Gao, Shuxin Liang, Fang Wu and 1 more

Abstract read
In one paragraph

Article in Insights into imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

11 authors.

Li Jiang *Department of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Shanshan Ma *Department of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Qinghua Du *Department of Radiation Oncology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Jun Lv *Department of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Minghua GuoDepartment of Gynecology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Huisi LinDepartment of Gynecology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Yanmei QueDepartment of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Ting GaoDepartment of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Shuxin LiangGuangxi Medical University, Nanning, China.
Fang WuDepartment of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China. wufang@gxmu.edu.cn.
Yong ZhangDepartment of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China. zhangyonggxmu@163.com.

Funding

the China Postdoctoral Science Foundation 2024MD763945the Joint Project on Regional High-Incidence Diseases Research of the Guangxi Natural Science Foundation 2023GXNSFBA026211the Joint Project on Regional High-Incidence Diseases Research of the Guangxi Natural Science Foundation 2024GXNSFAA010026the National Natural Science Foundation of China 82202940the National Natural Science Foundation of China 82460573
6 · The paper itself

Abstract

objectivesThis study aimed to establish and validate nomograms integrating the Node-Reporting and Data System (Node-RADS) score and clinical variables to predict overall survival (OS) and progression-free survival (PFS) in patients with International Federation of Obstetrics and Gynecology (FIGO) 2018 stage IIICr cervical cancer receiving definitive chemoradiotherapy. MATERIALS AND

methodsA retrospective two-center cohort study was conducted, enrolling eligible patients treated between March 2011 and December 2022. Nomograms were established based on least absolute shrinkage and selection operator (LASSO) regression, and Cox regression was used to identify prognostic features. The performance of the nomograms was assessed using receiver operating characteristic curves (ROC), calibration curves, and decision curve analysis (DCA).

resultsA total of 307 eligible patients were analyzed. For OS, independent prognostic factors included para-aortic lymph node (PALN) metastasis, non-squamous histology, Node-RADS score, and lymph node (LN) boost irradiation ≥ 60 Gy EQD2 (Equivalent dose in 2Gy fractions); for PFS, these were T stage, non-squamous histology, and LN boost irradiation ≥ 60 Gy EQD2. Nomograms outperformed FIGO 2009/2018 staging in discrimination and clinical utility, with calibration curves showing good agreement between predicted and observed outcomes. Kaplan-Meier analysis linked higher Node-RADS scores, PALN metastasis, > 3 positive LNs, and LN boost irradiation < 60 Gy EQD2 to poorer OS and PFS.

conclusionA nomogram incorporating the Node-RADS score, which is significantly associated with survival, can serve as a potential prognostic marker to assist clinicians in making informed decisions and developing individualized treatment strategies. Notably, the inherent treatment-selection bias in the retrospective design limits its direct therapeutic implications. CRITICAL RELEVANCE STATEMENT: Node-RADS-based nomograms offer superior risk stratification and prognosis prediction for stage IIICr cervical cancer patients. KEY POINTS: The nomogram incorporating the Node-Reporting and Data System (Node-RADS) score can serve as a potential prognostic marker to assist clinicians. The nomogram incorporating the Node-RADS score, which integrated clinicopathological data and therapies, outperformed Federation of Obstetrics and Gynecology (FIGO) staging in discriminative ability and clinical utility. Higher Node-RADS scores correlated with worse survival outcomes of patients, and lymph node (LN) boost irradiation ≥ 60 Gy EQD2 might provide survival benefits.

Indexed as

ChemoradiotherapyFIGO stage IIICr cervical cancerNode-RADSNomogramPrognosis

Identifiers

PMID41774295
PMCPMC12957706

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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.