Evidence map›Paper›PMID 32410792›Full record

ArticleChinese journal of cancer research = Chung-kuo yen cheng yen chiu2020

The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC): A report of 2,781 cases in a Chinese population.

Yanli Zhu, Yuntao Song, Guohui Xu, Zhihui Fan, Wenhao Ren

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Article in Chinese journal of cancer research = Chung-kuo yen cheng yen chiu, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 12% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Yanli Zhu
Yuntao SongDepartment of Head and Neck Surgery.
Guohui XuDepartment of Head and Neck Surgery.
Zhihui FanDepartment of Ultrasound, Peking University Cancer Hospital and Institute, Beijing 100142, China.
Wenhao Ren
Peking University Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the diagnostic utility of The Bethesda System for Reporting Thyroid Cytology (TBSRTC) at Peking University Cancer Hospital, the incidence of noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP), and the impact of reclassification on cytopathological outcomes.

methodsWe performed a retrospective study of thyroid fine-needle aspiration (FNA) cases between April 2014 and March 2019. The FNA results were classified according to TBSRTC. Post-surgery histological findings were followed up.

resultsA total of 2,781 thyroid FNAs were performed. The incidences of the 6 diagnostic categories (DCs I-VI) were 14.8%, 17.1%, 15.8%, 2.3%, 11.6% and 38.5%, respectively. A total of 1,122 patients (40.3%) had corresponding histological results. NIFTP accounted for 0.4% of papillary thyroid carcinoma (PTC) cases, and there was no significant difference in the risk of malignancy (ROM) for each TBSRTC DC between "NIFTP=carcinoma (Ca)" and "NIFTP≠Ca". When "NIFTP=Ca", the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of TBSRTC were 98.0%, 84.0%, 99.4%, 58.3%, and 97.5%, respectively. When "NIFTP≠Ca", the sensitivity, specificity, PPV, NPV and accuracy of the TBSRTC were 98.1%, 81.5%, 99.3%, 61.1%, and 97.5%, respectively.

conclusionsTBSRTC is effective in the preoperative diagnosis of thyroid nodules in Peking University Cancer Hospital. The impact of the reclassification of NIFTP on cytopathological outcomes is limited because of its low incidence, and the revised ROMs are not suitable for Asian patients.

Indexed as

Bethesda systemcytopathologyFNANIFTPthyroid

Identifiers

PMID32410792
PMCPMC7219100
OpenAlexW3024922256

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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.