Evidence map›Paper›PMID 42447238›Full record

ReviewProceedings (Baylor University. Medical Center)2026

Thyroid tissue in cervical lymph nodes: clinical significance, management, and review of the literature.

Payam S Pahlavan

Abstract readReview
In one paragraph

Review in Proceedings (Baylor University. Medical Center), 2026. 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. Article
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

1 author.

Payam S PahlavanDepartment of Pathology, Lutheran Hospital, Fort Wayne, Indiana, USA.ORCID 0000-0001-8777-8373

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhen thyroid tissue is found within a cervical lymph node, clinicians must distinguish between a benign ectopic inclusion (thyroidosis) and metastatic thyroid carcinoma-a distinction with major management implications. This narrative review synthesizes the available literature on benign thyroid tissue incidentally identified in cervical lymph nodes.

methodsA focused literature search was conducted using the PubMed/MEDLINE database with an end date of April 15, 2026. Publications were included if they reported cases of benign thyroid tissue identified in cervical lymph nodes with histological or molecular confirmation, encompassing case reports, case series, or original studies.

resultsFifteen publications were identified, covering approximately 35 to 45 cases. Patients ranged in age from 13 to 72 years (mean 46), with a marked female predominance (∼75%). Lateral cervical nodes (levels II-IV) were involved in ∼80% of cases. Histologically, benign inclusions were characterized by well-formed follicles with colloid, capsular or subcapsular positioning, and no malignant cytology. Immunohistochemical markers (e.g., HBME-1, CK19) and molecular testing (BRAF/RAS mutation analysis) were reported to be helpful in differentiating benign from malignant thyroid tissue. Associated conditions included autoimmune thyroiditis, head and neck malignancies, and postablative states. Over follow-up periods of 6 months to 10 years, no malignant transformation was observed.

conclusionRigorous histological evaluation, supported by ancillary testing, enables confident diagnosis. Conservative surveillance-rather than thyroidectomy-is appropriate when malignancy has been excluded.

Indexed as

Lymph NodesThyroid GlandThyroid NeoplasmsAdultDiagnosis, DifferentialFemaleHumansNeckBenign thyroid inclusioncervical lymph nodecervical metastasisectopic thyroidneck dissectionthyroidosisthyroid tissue

Identifiers

PMID42447238
PMCPMC13682227

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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.