Evidence map›Paper›PMID 36568092›Full record

ArticleFrontiers in endocrinology2022

The number of metastatic lymph nodes optimizes staging in patients aged 55 years or older with papillary thyroid cancer.

Yun-Gang Sun, Fei Chen, Qiao-Ling Sun, Jin-Yu Tian, Xiao-Chuan He

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2022. 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
0.3field-weighted citation impact, top 39% 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 3 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Yun-Gang SunDepartment of Nuclear Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Fei ChenDepartment of Thyroid Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Qiao-Ling SunDepartment of Nuclear Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Jin-Yu TianDepartment of Nuclear Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Xiao-Chuan HeDepartment of Nuclear Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Zhujiang Hospital · CNSouthern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Current staging criteria for papillary thyroid cancer (PTC) do not include the number of metastatic lymph nodes (LNs), which is highly predictive of survival in multiple cancers. The LN metastasis burden is particularly relevant for older adults with thyroid cancer because of their poor prognosis. We examined a modified staging system for this population utilizing node number (Nn). Methods: Overall, 14,341 patients aged 55 years or older with stage I-IVB PTC were identified in the 2004-2015 Surveillance, Epidemiology and End Results database. Cox regression models were conducted to test the relationship between positive LN number and PTC-specific survival (PTCSS). Independent training/validation sets were used to derive and validate a new revised TNnM grouping. The 8th edition American Joint Committee on Cancer TNM staging system was compared with TNnM stage by calculating the 10-year PTCSS rates, Harrell's concordance index (C-index), and Akaike's information criterion (AIC). Results: An increase in number of LN metastases was identified as an independent, negative prognostic factor for PTCSS in multivariate analysis. 10-year PTCSS for stage I-IVB based on the AJCC 8th edition TNM were 98.83%, 93.49%, 71.21%, 72.95%, and 58.52%, respectively, while 10-year PTCSS for the corresponding stage in the TNnM were 98.59%, 92.2%, 83.26%, 75.24%, and 56.73%, respectively. The revised TNnM stage was superior, with a higher C-index and a lower AIC in both the training and validation cohorts. Conclusion: The TNnM staging system for PTC patients ≥ 55 years could be associated with improved outcomes. External validation studies of this system are warranted.

Indexed as

Thyroid NeoplasmsAgedHumansLymph NodesNeoplasm StagingPrognosisThyroid Cancer, Papillarynumber of positive lymph nodespapillary thyroid cancerprognosisSEERTNM staging system

Identifiers

PMID36568092
PMCPMC9780272
OpenAlexW4311947840

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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.