Evidence map›Paper›PMID 42164684›Full record

ArticleGland surgery2026

Assessment of malignant risk in thyroid nodules classified as category 4 and above against a background of Hashimoto's thyroiditis.

Dilinuerkezi Abulimiti, Xinxi Li, Ye Tian, Lei Zhang, Donglin Li, Zaiying Yeerbao, Xiangxiang Ru

Abstract read
In one paragraph

Article in Gland surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Dilinuerkezi AbulimitiDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Xinxi LiDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Ye TianDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Lei ZhangDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Donglin LiDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Zaiying YeerbaoDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Xiangxiang RuDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The assessment of malignancy risk in thyroid nodules classified as Thyroid Imaging, Reporting and Data System (TI-RADS) category 4 and above remains a clinical challenge. The impact of Hashimoto's thyroiditis (HT) on both the malignant risk and the predictive value of sonographic features in such nodules are not fully elucidated. This study aimed to investigate the malignant risk of TI-RADS 4+ nodules in patients with HT and to analyse the predictive value of their ultrasonic characteristics. Methods: In this retrospective study, we included 2,340 patients with TI-RADS category 4 or higher thyroid nodules treated at our hospital from January 2018 to December 2024. Based on the presence of HT, patients were divided into an HT group (n=733) and a non-HT group (n=1,607). Malignancy rates and ultrasonic features were compared between the two groups. Multivariate logistic regression was used to identify independent predictors of malignancy. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive performance of the models. Results: Among the 2,340 patients (595 males and 1,745 females), the malignancy rate was significantly higher in the HT group (86.6%, 635/733) than in the non-HT group (83.2%, 1,337/1,607; P=0.02). Univariate analysis showed that within each group, malignant nodules exhibited significantly higher proportions of several suspicious features, including solid composition, hypoechogenicity, indistinct margins, irregular shape, hyperechoic foci without acoustic shadowing, calcification, and heterogeneous internal echotexture (all P<0.05). Multivariate analysis identified hypoechogenicity [odds ratio (OR) =2.54], irregular shape (OR =1.85), and calcification (OR =2.09) as independent predictors of malignancy in the HT group (all P<0.05). For the non-HT group, independent predictors were hypoechogenicity (OR =3.182), indistinct margins (OR =2.023), irregular shape (OR =1.69), and heterogeneous internal echotexture (OR =3.65; all P<0.05). When nodules presented with "hyperechoic foci without acoustic shadowing" or "calcification", the positive predictive value (PPV) for malignancy was significantly higher in the HT group than in the non-HT group (both P<0.05). For other malignant ultrasonic features, there was no significant difference in predictive rates between the groups (P>0.05). Prediction models constructed based on the respective independent predictors showed similar discriminative performance between the two groups (P>0.05). Conclusions: HT is an independent risk factor for malignancy in thyroid nodules classified as TI-RADS category 4 and above. It reshapes the predictive value system of ultrasonic features by diminishing the diagnostic weight of features like "indistinct margins" while increasing the predictive importance of "hypoechogenicity", "irregular shape", and "calcification". Furthermore, HT exhibits a synergistic effect with the "calcification" feature, significantly amplifying the assessed malignant risk.

Indexed as

Hashimoto’s thyroiditis (HT)malignant riskpredictive modelthyroid noduleultrasonography (US)

Identifiers

PMID42164684
PMCPMC13184198

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.