Evidence map›Paper›PMID 34448961›Full record

ArticleAnnals of surgical oncology2022

Lymphatic Node Metastasis Risk Scoring System: A Novel Instrument for Predicting Lymph Node Metastasis After Thymic Epithelial Tumor Resection.

Xinxin Cheng, Yaxin Lu, Sai Chen, Weilin Yang, Bo Xu, Jianyong Zou, Zhenguang Chen

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Annals of surgical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 43% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Xinxin Cheng *Department of Cardiothoracic Surgery of East Division, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China.
Yaxin Lu *Department of Clinical Data Center, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China.
Sai Chen *Department of Center for Private Medical Service and Healthcare, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China.
Weilin YangDepartment of Cardiothoracic Surgery of East Division, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China.
Bo XuDepartment of Cardiothoracic Surgery of East Division, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China.
Jianyong ZouDepartment of Thoracic Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China.
Zhenguang Chen *Department of Cardiothoracic Surgery of East Division, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China. chzheng@mail.sysu.edu.cn.
The First Affiliated Hospital, Sun Yat-sen University · CNSun Yat-sen University · CNThird Affiliated Hospital of Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe authors aimed to create a novel model to predict lymphatic metastasis in thymic epithelial tumors.

methodsData of 1018 patients were collected from the Surveillance, Epidemiology, and End Results database from 2004 to 2015. To construct a nomogram, the least absolute shrinkage and selection operator (LASSO) regression model was used to select candidate features of the training cohort from 2004 to 2013. A simple model called the Lymphatic Node Metastasis Risk Scoring System (LNMRS) was constructed to predict lymphatic metastasis. Using patients from 2014 to 2015 as the validation cohort, the predictive performance of the model was determined by receiver operating characteristic (ROC) curves.

resultsThe LASSO regression model showed that age, extension, and histology type were significantly associated with lymph node metastasis, which were used to construct the nomogram. Through analysis of the area under the curve (AUC), the nomogram achieved a AUC value of 0.80 (95 % confidence interval [Cl] 0.75-0.85) in the training cohort and 0.82 (95 % Cl 0.70-0.93) in the validation cohort, and had closed calibration curves. Based on the nomogram, the authors constructed the LNMRS model, which had an AUC of 0.80 (95 % Cl 0.75-0.85) in the training cohort and 0.82 (95% Cl 0.70-0.93) in the validation cohort. The ROC curves indicated that the LNMRS had excellent predictive performance for lymph node metastasis.

conclusionThis study established a nomogram for predicting lymph node metastasis. The LNMRS model, constructed to predict lymphatic involvement of patients, was more convenient than the nomogram.

Indexed as

Neoplasms, Glandular and EpithelialHumansLymphatic MetastasisThymus Neoplasms

Identifiers

PMID34448961
PMCPMC8677650
OpenAlexW3194905754

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.