Evidence map›Paper›PMID 34510328›Full record

ArticleCurrent medical science2021

A Metabolic-associated Nomogram Predicts Recurrence Survival of Thyroid Cancer.

Zi-Han Xi, Xian-Xiong Ma, Heng-Yu Chen, Yuan-Hang Yu, Lei Li, Tao Huang

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Article in Current medical science, 2021. 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. A Clinical Nomogram to Predict Survival Outcomes in Patients with Well-Differentiated Thyroid Cancer.Thyroid : official journal of the American Thyroid Association · 2025
    Article
4 · The record

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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

6 authors.

Zi-Han Xi *Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Xian-Xiong Ma *Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Heng-Yu Chen *Department of Pancreatic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Yuan-Hang YuDepartment of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Lei LiDepartment of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China. leili2008@hust.edu.
Tao HuangDepartment of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China. huangtaowh@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveVarious studies have suggested that metabolic genes play a significant role in papillary thyroid cancer (PTC). The current study aimed to identify a metabolic signature related biomarker to predict the prognosis of patients with PTC.

methodsWe conducted a comprehensive analysis on the data obtained from the Cancer Genome Atlas (TCGA) database. The correlation between survival result and metabolic genes was evaluated based on the univariate Cox analyses, least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses. The performance of a 7-gene signature was assessed according to Kaplan-Meier and receiver operating characteristic (ROC) analysis. Multivariate Cox regression analysis was adopted to unearth clinical factors related to the recurrence free survival (RFS) of patients with PTC. Finally, a prognostic nomogram was developed based on risk score, cancer status and cancer width to improve the prediction for RFS of PTC patients.

resultsSeven metabolic genes were used to establish the prognostic model. The ROC curve and C-index exhibited high value in training, testing and the whole TCGA datasets. The established nomogram, incorporating the 7-metabolic gene signature and clinical factors, was able to predict the RFS with high effectiveness. The 7-metabolic gene signature-based nomogram had a good performance to predict the RFS of patients with PTC.

conclusionOur study identified a 7-metabolic gene signature and established a prognostic nomogram, which were useful in predicting the RFS of PTC.

Indexed as

Metabolic Networks and PathwaysNomogramsBiomarkers, TumorDatabases, GeneticFemaleHumansKaplan-Meier EstimateMaleNeoplasm StagingPrognosisSurvival AnalysisThyroid Cancer, PapillaryThyroid NeoplasmsBiomarkers, Tumormetabolismnomogrampapillary thyroid cancerrecurrence free survivalsignature

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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.