Evidence map›Paper›PMID 40123892›Full record

ArticleFrontiers in endocrinology2025

Construction and validation of novel nomograms based on the log odds of positive lymph nodes to predict the prognosis of papillary thyroid cancer: a retrospective cohort study.

Saisai Jing, Jiazhao Song, Yupeng Di, Jiajia Xiao, Jianke Ma, Zimiao Wu

Abstract readValidation Study
In one paragraph

Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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

6 authors.

Saisai Jing *Department of Oncology, Affiliated Cixi Hospital, Wenzhou Medical University, Cixi, Zhejiang, China.
Jiazhao Song *Department of Radiotherapy, Air Force Medical Center, Air Force Medical University, Beijing, China.
Yupeng DiDepartment of Radiotherapy, Air Force Medical Center, Air Force Medical University, Beijing, China.
Jiajia XiaoGraduate School, Hebei North University, Zhangjiakou, Hebei, China.
Jianke MaDepartment of Oncology, Affiliated Cixi Hospital, Wenzhou Medical University, Cixi, Zhejiang, China.
Zimiao WuDepartment of Oncology, Affiliated Cixi Hospital, Wenzhou Medical University, Cixi, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to assess the long-term prognostic significance of the log odds of positive lymph nodes (LODDS) in patients diagnosed with papillary thyroid cancer (PTC) and to develop a novel nomogram for predicting long-term overall survival (OS). Methods: The cohort was randomly divided at a ratio of 7:3 from the Surveillance, Epidemiology, and End Results (SEER) database. Additionally, patient data from a medical center in China served as an external validation cohort. Nomograms were constructed using data from the training cohort and subsequently validated using both internal and external validation cohorts to predict 120- and 180-month OS in PTC patients. The predictive performance and clinical utility of the nomogram were assessed using various metrics, including the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), Integrated Discriminant Improvement Index (IDI), and Net Reclassification Improvement Index (NRI). Results: LODDS is an independent prognostic factor for PTC, a nomogram demonstrating high accuracy in predicting long-term OS. The C-index values, and time-dependent area under the curve (AUC) indicated well discriminatory ability of the nomogram. Calibration plots exhibited high concordance, while DCA, NRI, and IDI analyses revealed superior performance of the nomogram compared to AJCC staging system. Conclusion: The clinical prediction model incorporating LODDS exhibits robust predictive performance, aiding in the assessment of long-term prognosis post-surgery in PTC patients. It serves as a valuable adjunct to the AJCC system, offering a scientific basis for guiding interventions and rehabilitation strategies for PTC patients following surgery.

Indexed as

Lymph NodesNomogramsThyroid Cancer, PapillaryThyroid NeoplasmsAdultAgedChinaFemaleFollow-Up StudiesHumansLymphatic MetastasisMaleMiddle AgedPrognosisRetrospective StudiesROC Curvelong-term overall survivalnomogrampapillary thyroid cancerpost-operativeSEER

Identifiers

PMID40123892
PMCPMC11925767

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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.