Evidence map›Paper›PMID 39678872›Full record

ArticleJournal of thoracic disease2024

Development and validation of a nomogram for incorporating

Daojia Liu, Duanyu Lin, Zhongmei Lin, Ying Peng, Siqian Cai, Qiwei Yang, Zhizhong Lin, Yuanmei Chen, Yongshi Shen, Yuanji Xu

Abstract read
In one paragraph

Article in Journal of thoracic disease, 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

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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Gland surgery · 2025
    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.

Daojia LiuDepartment of Nuclear Medicine, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.ORCID https://orcid.org/0000-0002-7044-3742
Duanyu LinDepartment of Nuclear Medicine, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Zhongmei LinDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Ying PengDepartment of Thoracic Oncology Surgery, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Siqian CaiDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Qiwei YangSchool of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Zhizhong LinDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Yuanmei ChenDepartment of Thoracic Oncology Surgery, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Yongshi ShenDepartment of Intensive Care Unit, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Yuanji XuDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is currently no widely accepted prognostic model specifically for elderly patients with esophageal squamous cell carcinoma (ESCC) undergoing radiotherapy. This study aimed to develop a nomogram incorporating metabolic imaging parameters from Methods: A retrospective analysis was conducted on 118 elderly patients with ESCC treated with radiotherapy. The patients were evaluated using Results: SLR and Lv were found to be independent predictors of OS in elderly patients with ESCC. The nomogram developed by incorporating these factors, along with cTNM staging, showed superior predictive power compared to the traditional TNM staging system. ROC curve analysis demonstrated greater accuracy in predicting 1-, 2-, and 3-year OS rates, with area under the curve (AUC) values of 0.771, 0.763, and 0.815, respectively. DCA confirmed that the nomogram provided a greater clinical benefit. Patients were stratified into low-risk, intermediate-risk, and high-risk groups, with corresponding 3-year OS rates of 60.3%, 25.0%, and 3.6%, respectively. Conclusions: The developed nomogram incorporating SLR, Lv, and cTNM staging offers a reliable tool for the risk stratification of elderly patients with ESCC undergoing radiotherapy. This model may serve as a reference for personalized treatment planning, potentially improving clinical outcomes in this patient population.

Indexed as

18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT)elderly esophageal cancerNomogramprognostic model

Identifiers

PMID39678872
PMCPMC11635226

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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.