Evidence map›Paper›PMID 36098339›Full record

ReviewKorean journal of radiology2022

Diagnostic Performance of Core Needle Biopsy for Characterizing Thyroidectomy Bed Lesions.

So Yeong Jeong, Jung Hwan Baek, Sae Rom Chung, Young Jun Choi, Dong Eun Song, Ki-Wook Chung, Won Woong Kim, Jeong Hyun Lee

Open access · hybridAbstract readReview
In one paragraph

Review in Korean journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 28% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Guideline
  2. Review
  3. Article
  4. Article
  5. 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

8 authors at 1 institution in 1 country.

So Yeong JeongDepartment of Radiology, Hanyang University Medical Center, Hanyang University Medical College, Seoul, Korea.ORCID 0000-0003-4705-0008
Jung Hwan BaekDepartment of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea. radbaek@naver.com.ORCID 0000-0003-0480-4754
Sae Rom ChungDepartment of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID 0000-0003-4219-7166
Young Jun ChoiDepartment of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID 0000-0001-7098-5042
Dong Eun SongDepartment of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID 0000-0002-9583-9794
Ki-Wook ChungDepartment of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID 0000-0002-4418-1857
Won Woong KimDepartment of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID 0000-0003-3471-2068
Jeong Hyun LeeDepartment of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID 0000-0002-0021-4477
Ulsan College · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThyroidectomy bed lesions frequently show suspicious ultrasound (US) features after thyroid surgery. Fine-needle aspiration (FNA) may not provide definitive pathological information about the lesions. Although core-needle biopsy (CNB) has excellent diagnostic performance in characterizing suspicious thyroid nodules, no published studies have evaluated the performance of CNB specifically for thyroidectomy bed lesions. Therefore, we aimed to evaluate the diagnostic performance and safety of CNB for characterizing thyroidectomy bed lesions. MATERIALS AND

methodsA total of 124 thyroidectomy bed lesions in 113 patients (79 female and 34 male; age, 23-85 years) who underwent US-guided CNB between December 2008 and December 2020 were included. We reviewed the US imaging features of the target lesions and the histories of previous biopsies. The pathologic results, diagnostic performance for malignancy, and complications of CNB were analyzed.

resultsAll samples (100%) obtained by CNB were adequate for pathological analysis. Pathological analysis revealed inconclusive results in two lesions (1.6%). According to the reference standard, 50 lesions were ultimately malignant (40.3%), and 72 were benign (58.1%), excluding the two inconclusive lesions. The performance of CNB for diagnosing malignant thyroidectomy bed lesions in the 122 lesions had a sensitivity of 98.0% (49/50), a specificity of 100% (72/72), positive predictive value of 100% (49/49), and negative predictive value of 98.6% (72/73). Eleven lesions were referred for CNB after prior inconclusive FNA results in thyroidectomy bed lesions, for all of which CNB yielded correct conclusive pathologic diagnoses. According to the pathological analysis of CNB, there were various benign lesions (58.9%, 73/124) besides recurrence, including benign postoperative lesions other than suture granuloma (32.3%, 40/124), suture granuloma (15.3%, 19/124), remnant thyroid tissue (5.6%, 7/124), parathyroid lesions (4%, 5/124), and abscesses (1.6%, 2/124). No major or minor complications were associated with the CNB procedure.

conclusionUS-guided CNB is accurate and safe for characterizing thyroidectomy bed lesions.

Indexed as

Thyroid NeoplasmsThyroid NoduleAdultAgedAged, 80 and overBiopsy, Fine-NeedleBiopsy, Large-Core NeedleFemaleHumansMaleMiddle AgedRetrospective StudiesSensitivity and SpecificityThyroidectomyYoung AdultCore-needle biopsyFine-needle aspirationThyroidThyroid cancerThyroidectomyUltrasonography

Identifiers

PMID36098339
PMCPMC9523230
OpenAlexW4294577756

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.