Evidence map›Paper›PMID 39817137›Full record

ArticleWorld journal of gastrointestinal oncology2025

Development of a nomogram for overall survival in patients with esophageal carcinoma: A prospective cohort study in China.

Shi-Shi Yu, Xi Zheng, Xiao-Sheng Li, Qian-Jie Xu, Wei Zhang, Zhong-Li Liao, Hai-Ke Lei

Abstract read
In one paragraph

Article in World journal of gastrointestinal oncology, 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

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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

1 citing paper in PubMed.

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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

7 authors.

Shi-Shi YuDepartment of Gastroenterology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Xi ZhengDepartment of Gastroenterology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Xiao-Sheng LiChongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing 400030, China.
Qian-Jie XuDepartment of Health Statistics, School of Public Health, Chongqing Medical University, Chongqing 400016, China.
Wei ZhangChongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing 400030, China.
Zhong-Li LiaoDepartment of Gastroenterology, Chongqing University Cancer Hospital, Chongqing 400030, China.
Hai-Ke LeiChongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing 400030, China. tohaike@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEsophageal carcinoma (EC) presents a significant public health issue in China, with its prognosis impacted by myriad factors. The creation of a reliable prognostic model for the overall survival (OS) of EC patients promises to greatly advance the customization of treatment approaches.

aimTo create a more systematic and practical model that incorporates clinically significant indicators to support decision-making in clinical settings.

methodsThis study utilized data from a prospective longitudinal cohort of 3127 EC patients treated at Chongqing University Cancer Hospital between January 1, 2018, and December 12, 2020. Utilizing the least absolute shrinkage and selection operator regression alongside multivariate Cox regression analyses helped pinpoint pertinent variables for constructing the model. Its efficacy was assessed by concordance index (C-index), area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA).

resultsNine variables were determined to be significant predictors of OS in EC patients: Body mass index (BMI), Karnofsky performance status, TNM stage, surgery, radiotherapy, chemotherapy, immunotherapy, platelet-to-lymphocyte ratio, and albumin-to-globulin ratio (ALB/GLB). The model demonstrated a C-index of 0.715 (95%CI: 0.701-0.729) in the training cohort and 0.711 (95%CI: 0.689-0.732) in the validation cohort. In the training cohort, AUCs for 1-year, 3-year, and 5-year OS predictions were 0.773, 0.787, and 0.750, respectively; in the validation cohort, they were 0.772, 0.768, and 0.723, respectively, illustrating the model's precision. Calibration curves and DCA verified the model's predictive accuracy and net benefit.

conclusionA novel prognostic model for determining the OS of EC patients was successfully developed and validated to help clinicians in devising individualized treatment schemes for EC patients.

Indexed as

Esophageal carcinomaHigh-risk factorsOverall survivalPrediction modelPrognosis

Identifiers

PMID39817137
PMCPMC11664612

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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.