Evidence map›Paper›PMID 40119689›Full record

Observational studyThe Journal of international medical research2025

Computed tomography-based radiomics modeling to predict patient overall survival in cervical cancer with intensity-modulated radiotherapy combined with concurrent chemotherapy.

Lihong Xiao, Youhua Wang, Xiangxiang Shi, Haowen Pang, Yunfei Li

Abstract readObservational Study
In one paragraph

Observational study in The Journal of international medical research, 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

5 authors.

Lihong XiaoDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.ORCID 0000-0002-7111-1299
Youhua WangDepartment of Oncology, Gulin County People's Hospital, Luzhou, Sichuan, China.
Xiangxiang ShiDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Haowen PangDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Yunfei LiDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ObjectiveThe objective of this study was to develop a predictive model combining radiomic characteristics and clinical features to forecast overall survival in cervical cancer patients treated with intensity-modulated radiotherapy and concurrent chemotherapy.MethodsIn this retrospective observational study, 159 patients were divided into a training group (n = 95) and a validation group (n = 64). Radiomic characteristics were extracted from contrast-enhanced computed tomography scans. The least absolute shrinkage and selection operator regression analysis was used to filter the extracted radiomic characteristics and reduce the dimensionality of the data. A radiomic score was calculated from the selected features, and multivariate Cox regression models were established to analyze overall survival. A nomogram combining radiomic score and clinical features was developed, and its reliability was assessed using the area under the receiver operating characteristic curve.ResultsFour radiomic characteristics and two clinical features were extracted for overall survival analysis. A nomogram combining these factors was developed and validated, showing good performance with a high C-index. Patients were categorized as low-risk or high-risk for overall survival based on a cut-off value.ConclusionsOur model combining computed tomography-extracted radiomic characteristics and clinical features shows good potential for evaluating overall survival in cervical cancer patients treated with intensity-modulated radiotherapy and concurrent chemotherapy.

Indexed as

ChemoradiotherapyRadiotherapy, Intensity-ModulatedTomography, X-Ray ComputedUterine Cervical NeoplasmsAdultAgedFemaleHumansMiddle AgedNomogramsPrognosisProportional Hazards ModelsRadiomicsRetrospective StudiesROC Curvecomputed tomographydrug therapyintensity-modulatedprediction modelradiotherapyUterine cervical neoplasms

Identifiers

PMID40119689
PMCPMC11938878

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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.