Evidence map›Paper›PMID 37355519›Full record

ArticleAnnals of surgical oncology2023

Development and Validation of PET/CT-Based Nomogram for Preoperative Prediction of Lymph Node Status in Esophageal Squamous Cell Carcinoma.

Shaoyuan Zhang, Linyi Sun, Danjie Cai, Guobing Liu, Dongxian Jiang, Jun Yin, Yong Fang, Hao Wang, Yaxing Shen, Yingyong Hou and 2 more

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Annals of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
5.7field-weighted citation impact, top 3% of its field
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

20 citing papers in PubMed, 18 citations in OpenAlex.

  1. Evaluation of PET-detected nodal upstaging and planning target volume expansion in esophageal cancer radiotherapy planning.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026
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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

12 authors at 4 institutions in 1 country.

Shaoyuan Zhang *Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Linyi Sun *Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Danjie Cai *Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Guobing LiuDepartment of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Dongxian JiangDepartment of Pathology, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Jun YinDepartment of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Yong FangDepartment of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Hao WangDepartment of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Yaxing ShenDepartment of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Yingyong HouDepartment of Pathology, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Hongcheng ShiDepartment of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China. shi.hongcheng@zs-hospital.sh.cn.
Lijie TanDepartment of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China. tan.lijie@zs-hospital.sh.cn.
The First Affiliated Hospital, Sun Yat-sen University · CNZhongshan Hospital · CNFudan University · CNSun Yat-sen University · CN

Funding

2021 Clinical Research Navigation Program of Shanghai Medical College of Fudan University DGF501035/002Science and Technology Commission of Shanghai Municipality 16411965900Zhongshan Hospital Fudan University 2016ZSLC15Zhongshan Hospital Fudan University 2019ZSFZ16Zhongshan Hospital Fudan University 2020ZSLC5
6 · The paper itself

Abstract

purposeThis study was conducted to predict the lymph node status and survival of esophageal squamous cell carcinoma before treatment by PET-CT-related parameters.

methodsFrom January 2013 to July 2018, patients with pathologically diagnosed ESCC at our hospital were retrospectively enrolled. Completed esophagectomy and two- or three-field lymph node dissections were conducted. Those with neoadjuvant therapy were excluded. The first 65% of patients in each year were regarded as the training set and the last 35% as the test set. Nomogram was constructed by the "rms" package. Five-year, overall survival was analyzed based on the best cutoff value of risk score determined by the "survivalROC" package.

resultsUltimately, 311 patients were included with 209 in the training set and 102 in the test set. The positive rate of the lymph node in the training set was 36.8% and that in the test set was 32.4%. The C-index of the training set was 0.763 and the test set was 0.766. The decision curve analysis showed that it was superior to the previous methods based on lymph node uptake or long/short axis diameter or axial ratio. Risk score > 0.20 was significantly associated with 5-year, overall survival (p = 0.0015) in all patients.

conclusionsThe nomogram constructed from PET-CT parameters including primary tumor metabolic length and thickness can accurately predict the risk of lymph node metastasis in ESCC. The risk score calculated by our model accurately predicts the patient's 5-year overall survival.

Indexed as

Esophageal NeoplasmsEsophageal Squamous Cell CarcinomaLymph NodesNomogramsPositron Emission Tomography Computed TomographyAgedEsophagectomyFemaleFollow-Up StudiesHumansLymphatic MetastasisLymph Node ExcisionMaleMiddle AgedPrognosisRetrospective StudiesEsophageal squamous cell carcinomaLymph node metastasisNomogramPET-CT

Identifiers

PMID37355519
OpenAlexW4381849034

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.