Comparative study of different worldwide versions of the thyroid risk stratification system in patients with thyroid nodules in China

Introduction

The detection of thyroid nodules has increased dramatically over the past two decades as ultrasound screening has become widely available. The vast majority of thyroid nodules do not require intervention; however, a small percentage are malignant tumours. Therefore, accurate and effective risk assessment is crucial (1). In this context, researchers have developed different versions of risk stratification systems for thyroid nodules in different geographical regions worldwide. These regions include Europe, North America, Korea, and China (2-5). These risk stratification systems are established based on local population nodule characteristics; thus, the ultrasound characteristics, malignancy risk categorization, and biopsy indications may differ accordingly (6). However, the goal of each system is the same: identify risk and guide clinicians in thyroid nodule management.

In China, the risk stratification system for thyroid nodules has not yet reached a uniform consensus, which may lead to the application of different risk stratification systems in medical institutions across different regions. Currently, risk stratification systems for thyroid nodules can be broadly classified into two types worldwide: one is a modality-based system that defines several categories with different risks of malignancy, such as the Korean Thyroid Imaging Reporting and Data Systems (K-TIRADS), developed by the Korean Society of Radiology and the Korean Society of Thyroid Radiology in 2016 (2), and the European TIRADS (EU-TIRADS), developed by the European Thyroid Association and the European Association of Radiology in 2017 (3). The other is a fraction-based calculation system that calculates mainly with different ultrasound image features with corresponding weights, such as the American College of Radiology TIRADS (ACR-TIRADS) created by the American College of Radiology in 2017 (4) and the Chinese TIRADS (C-TIRADS) created by The Superficial Organ and Vascular Ultrasound Group in the Chinese Medical Association in 2020 (5). According to several previous studies, different versions of the thyroid risk stratification system in different geographical settings may perform slightly differently for the same nodule. Additionally, different systems have different size thresholds for fine-needle aspiration (FNA), which also affects the final diagnostic performance (7-10). To date, researchers have not reached a consensus on which system is ideal for patients in China. Therefore, this study aimed to compare the applicability of different geographical versions of the thyroid risk stratification system in patients with thyroid nodules in China. We present this article in accordance with the STARD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-527/rc).

Methods

Compliance with ethical standards

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by institutional ethics board of Cancer Hospital of Shantou University Medical College (No. 2024055) and individual consent for this retrospective analysis was waived.

Study population

Patients with thyroid nodules who underwent surgical resection or core needle biopsy at the Second Affiliated Hospital of Shantou University Medical College from January 2020 to December 2023 were included. Thyroid nodules were included if they had the following complete information: (I) clear histopathological findings, either based on surgical resection or core needle biopsy; and (II) documentation of clear ultrasound images retained at the Second Affiliated Hospital of Shantou University Medical College within 1 month before surgery. Thyroid nodules were excluded from the database if (I) there were no clear histopathological findings and (II) no clear or complete ultrasound image data had been retained at the Second Affiliated Hospital of Shantou University Medical College for one month before surgery. When a patient had more than one nodule, a nodule which has a typical image and final clear histology will be included in the database. In total, 1,196 patients with 1,196 thyroid nodules underwent surgical resection or core needle biopsy. Among them, 22 nodules in 22 patients were excluded from this study due to blurred ultrasound images or a lack of final pathological confirmation. Ultimately, 1,174 thyroid nodules from 1,174 patients were included in the study (Figure 1).

Figure 1 Flowchart showing the recruitment of study participants.

The ultrasound images were acquired by Logiq E9 (GE Healthcare, Chicago, USA) with a linear high-frequency probe (ML6-15) and RS80A (SAMSUNG Healthcare, Seoul, Korea) with a linear high-frequency probe (L3-12A). All neck and thyroid images have clear grayscale images and colour Doppler images in both transverse and longitudinal sections, as well as documented measurements on the images. Two radiologists with more than 10 years of experience reread, analysed, and scored the ultrasound images retrospectively. Furthermore, postoperative pathology and prior risk stratification for the nodules were unknown. In the event of a discrepancy between the two radiologists’ judgements, a radiologist with more than 30 years of extensive experience made the final confirmation. The thyroid nodule ultrasound image features were revised by two radiologists according to the requirements of the four risk stratification systems described above. They include nodule size thresholds, composition (spongiform, cystic, or almost completely cystic; mixed cystic and solid; solid or almost completely solid), echogenicity (anechoic, hyperechoic, or isoechoic; hypoechoic; markedly hypoechoic), shape (wider-than-tall; taller-than-wide), margin (smooth; lobulated or irregular; extrathyroidal extension), and echogenic foci (none or comet-tail artefacts; macrocalcification; peripheral calcification; punctate echogenic foci). Each nodule was then stratified for malignant risk according to the stratification methodology of each of the above risk stratification systems. The necessary FNA recommendations were given accordingly (Figures 2,3).

Figure 2 A solid nodule in the right lobe of the thyroid gland, with a maximum diameter of 3.5 cm, smooth margin, shape of wider-than-taller, and iso-echogenicity inside.

Figure 3 A solid nodule in the left lobe of the thyroid gland, with a maximum diameter of 0.7 cm, irregular margin, shape of wider-than-taller, and hypo-echogenicity and punctate echogenic foci inside.

Data and statistical analysis

In the case of continuous variables with normal distributions, the mean ± standard deviation (SD) is expressed, whereas for variables with an abnormal distribution, the median is expressed (interquartile range). Frequencies and proportions were used to express nominal and ordinal variables. Nonparametric data were analysed using the Mann-Whitney U test, and parametric data were analysed using the unpaired t-test. Fisher’s exact test or chi-square test was used to compare categorical variables, multiple group rates, or component ratios.

The risk of malignancy for each node was categorized according to each of the four risk stratification systems. The final histopathological findings of each nodule were subsequently used to determine the proportion of benign and malignant nodules in each risk stratification. Moreover, according to each risk stratification system’s FNA recommendations, the percentage of malignant nodules was also calculated. Afterwards, receiver operating characteristic (ROC) curves for the medium- and high-risk nodules (categories 4 and 5) are drawn for each risk stratification system. The cut-off of categories for their respective areas under the receiver operating characteristic curves (AUROCs) were determined. Based on the established cut-off values, the Delong test was used to compare the differences in the AUROC among the groups. Moreover, the AUROC differences among the groups of different sizes (nodules <1.0 mm; nodules ≥1.0 mm) were also compared. Finally, the AUROCs under the FNA recommendations based on each risk stratification system were compared using the Delong test. All statistical data were analysed with SPSS software for Windows (version 26.0; SPSS Institute, USA) and MedCalc software (version 18.2.1; Mariakerke, Belgium). Two-sided P values <0.05 were considered to indicate statistical significance.

Results

Clinical baseline characteristics and ultrasound features of the nodules

Among the 1,174 thyroid nodules (201 males and 973 females; average age, 45.86±13.66 years), 699 were benign (120 males and 579 females; average age, 45.92±13.95 years), and 475 were malignant (81 males and 394 females; average age, 45.77±13.25 years). There were no statistically significant differences in age or sex between patients with benign and malignant thyroid nodules (age, P=0.640; sex, P=0.959). Among each thyroid nodule range threshold, a total of 109 cases (35 benign and 74 malignant) had nodules with a maximum diameter between 15 mm, a total of 297 cases (123 benign and 174 malignant) had nodules with a maximum diameter between 5 and 10 mm, a total of 193 cases (104 benign and 89 malignant) had nodules with a maximum diameter between 10 and 15 mm, a total of 170 cases (105 benign and 65 malignant) had nodules with a maximum diameter between 15 mm and 20 mm, and a total of 405 cases (332 benign and 73 malignant) had nodules with a minimum diameter of 20 mm. The differences between the groups were statistically significant (P<0.001). More detailed information is presented in Table 1.

Malignancy rates and malignant detection of FNAs in each category

The malignancy rates and malignant detection results of the FNAs in each category are summarised in Table 2. In the C-TIRADS risk stratification system, the number of nodules, malignancy rate, and FNA malignancy detection rate for categories 2, 3, 4A, 4B, 4C, and 5 were 45 cases, 0.0%, and not applicable (NA); 252 cases, 1.2%; NA; 370 cases, 16.5%, 7.7%; 210 cases, 64.3%, 67.0%; and 284 cases, 93.0%, 98.5% and 13 cases, 92.3%, 100.0%, respectively. In the ACR-TIRADS risk stratification system, the number of nodules, malignancy rate, and FNA malignancy detection rate for categories 1 through 5 were as follows: 66 cases, 0.0%, NA; 245 cases, 0.4%, NA; 130 cases, 2.3%, 0.0%; 256 cases, 24.2%, 17.8%; and 477 cases, 85.7%, 88.5%, respectively. In the EU-TIRADS risk stratification system, the number of nodules, malignancy rate, and FNA malignancy detection rate for categories 2, 3, 4, and 5 were as follows: 171 cases, 0.0%, NA; 281 cases, 1.8%, 0.6%; 213 cases, 28.2%, 18.1%; and 509 cases, 80.6%, 81.8%, respectively. In the K-TIRADS risk stratification system, the number of nodules, malignancy rate, and FNA malignancy detection rate for categories 2, 3, 4, and 5 were as follows: 197 cases, 0.0%, 0.0%; 269 cases, 2.2%, 1.0%; 266 cases, 33.5%, 29.3%; and 442 cases, 86.0%, 89.1%, respectively.

The cut-off category in each risk stratification system

The receiver operating characteristic curves show the cut-off category for each risk stratification system. The best diagnostic performance cut-off categories for each risk stratification system were C-TIRADS 4B [area under the curve (AUC) =0.864], ACR-TIRADS 5 (AUC =0.882), EU-TIRADS 5 (AUC =0.861) and K-TIRADS 5 (AUC =0.856). More detailed information is presented in Table 3.

Comparison of diagnostic performance for each cut-off category

Comparisons of the four risk stratification systems’ best cut-off categories are shown in Figures 4-6 and Table 4. The AUROC of ACR-TIRADS 5 was significantly greater than those of C-TIRADS 4B, EU-TIRADS 5, and K-TIRADS 5 (vs. C-TIRADS 4B, P=0.0191; vs. EU-TIRADS 5, P=0.0031; vs. K-TIRADS 5, P=0.0001). Comparisons of the AUROCs of C-TIRADS 4B, EU-TIRADS 5, and K-TIRADS 5 revealed no statistically significant differences (C-TIRADS 4B vs. EU-TIRADS 5, P=0.4184; C-TIRADS 4B vs. K-TIRADS 5, P=0.2388; EU-TIRADS 5 vs. K-TIRADS 5, P=0.4659).

Figure 4 Receiver operating characteristic curve of C-TIRADS, ACR-TIRADS, EU-TIRADS, and K-TIRADS in each cut-off categories. ACR-TIRADS, Thyroid Imaging Reporting and Data System of the American College of Radiology; C-TIRADS, Chinese Thyroid Imaging Reporting and Data System; EU-TIRADS, European Thyroid Imaging Reporting and Data System; K-TIRADS, Korean Thyroid Imaging Reporting and Data System.

Figure 5 Receiver operating characteristic curve of C-TIRADS, ACR-TIRADS, EU-TIRADS, and K-TIRADS in each cut-off categories with nodules size <10 mm. ACR-TIRADS, Thyroid Imaging Reporting and Data System of the American College of Radiology; C-TIRADS, Chinese Thyroid Imaging Reporting and Data System; EU-TIRADS, European Thyroid Imaging Reporting and Data System; K-TIRADS, Korean Thyroid Imaging Reporting and Data System; NS, nodule size.

Figure 6 Receiver operating characteristic curve of C-TIRADS, ACR-TIRADS, EU-TIRADS, and K-TIRADS in each cut-off categories with nodules size ≥10 mm. ACR-TIRADS, Thyroid Imaging Reporting and Data System of the American College of Radiology; C-TIRADS, Chinese Thyroid Imaging Reporting and Data System; EU-TIRADS, European Thyroid Imaging Reporting and Data System; K-TIRADS, Korean Thyroid Imaging Reporting and Data System; NS, nodule size.

Comparison of diagnostic performance for each FNA recommendation in each cut-off category

The FNA recommendation of CI-TIRADS 4B showed the best FNA diagnostic performance, with an AUROC of 0.658. Compared with those of ACR-TIRADS 5, EU-TIRADS 5, and KI-TIRADS 5, the AUROC of the FNA recommendation of ACR-TIRADS 5 was significantly better (all P<0.0001). Additionally, compared with those of the EU-TIRADS 5 (vs. EU-TIRADS 5, P<0.0001; vs. KI-TIRADS 5, P=0.0133), the AUROC of the ACR-TIRADS 5 was significantly better. However, there was no significant difference in the comparison between the FNA recommendations of the EU-TIRADS-5 and KI-TIRADS-5 (P=0.8275). More detailed information is presented in Table 5 and Figure 7.

Figure 7 Receiver operating characteristic curve of C-TIRADS, ACR-TIRADS, EU-TIRADS, and K-TIRADS in each cut-off category of FNA recommendation. ACR-TIRADS, Thyroid Imaging Reporting and Data System of the American College of Radiology; C-TIRADS, Chinese Thyroid Imaging Reporting and Data System; EU-TIRADS, European Thyroid Imaging Reporting and Data System; FNA, fine-needle aspiration; K-TIRADS, Korean Thyroid Imaging Reporting and Data System.

Discussion

The results of our study revealed significant differences between benign and malignant nodules in terms of composition, echogenicity, shape, margin, and echogenic foci, suggesting that these features are associated with malignancy in patients from China. In our study, four different geographical setting versions of the thyroid risk stratification system were used to evaluate and manage the above five ultrasound features. Although they use similar ultrasound features for evaluation, inconsistent weights are assigned to these ultrasound features by different versions, making the calculation different. Owing to the difference in how features are considered concerning for each system, the risk stratification varies.

Our results revealed that the optimal cut-off values for the four risk stratification systems were C-TIRADS 4B, ACR-TIRADS 5, EU-TIRADS 5, and KI-TIRADS 5. Our results are in general agreement with those of previous studies (11,12). The data in Table 2 show that the malignancy rates for their subgroups increase rapidly at these optimal cut-off values. In this way, optimal cut-offs can be obtained for each risk stratification system from the subgroups mentioned above. At these optimal cut-off values, the diagnostic performance of the ACR-TIRADS was slightly better than that of the other three risk stratification systems, while there was no difference in diagnostic performance between the other three systems. This result may be explained by the fact that the ACR-TIRADS uses a weighted scoring system, assigning different scores to various acoustic features, which may allow for greater diagnostic accuracy (13). Although the diagnostic performance of the ACR is better than that of the other three systems, the evaluation process of the ACR takes longer and requires more experience from evaluators. This leads to a decrease in evaluation efficiency in situations where resources are limited or when doctors lack experience, thereby affecting the timeliness and accuracy of diagnosis. All three of the other risk stratification systems also have high diagnostic performance, with all of them having an AUROC of approximately 0.86. However, their assessment methods are relatively rapid, and they require the identification of only a few key ultrasound features to complete the assessment. In our assessment, overall, all four systems demonstrated an appropriate ability to assess thyroid nodules in patients from China.

In the subcentimetre subgroup exploration, the diagnostic performance of subcentimetre nodules was inferior to that of large nodules in all four risk stratification systems in our study, which is consistent with previous findings (14). We determined that this may be related to the display resolution of the image. Larger thyroid nodules may be easier to recognize accurately with ultrasound features, which explains why nodules larger than 1 cm had better diagnostic performance in our study. However, some previous studies have shown that the diagnostic performance of these risk stratification systems does not vary with nodule size (15,16). We suggest that the differences in results may be related to case selection bias.

FNA recommendations following the evaluation of thyroid nodules are a crucial part of the risk stratification system, as is their diagnostic performance. The higher the diagnostic performance recommended by FNA is, the higher the accuracy of nodule diagnosis while reducing unnecessary FNA. Our study revealed that the diagnostic performance of the best-performing C-TIRADS was significantly better than that of the other three stratification systems. In addition to specificity, the recommended FNA of the C-TIRADS had the highest sensitivity, PPV, NPV, and accuracy among the four systems, which is consistent with previous study (17). In the Chinese geographic setting, although patients may know that most thyroid malignancies are indolent, they still present with higher levels of concern when test results suggest a high risk. In particular, patients may be more inclined to undergo surgical treatment when FNA is recommended through a risk stratification system, but no definitive pathological results can be obtained. This excessive treatment of thyroid nodules has significantly increased the socioeconomic burden in China, which may not be consistent with the management of thyroid nodules abroad. In cases where a diagnosis cannot be made, patients may be more willing to undergo follow-up examinations. Compared with the other three systems, the C-TIRADS has better recommended FNA diagnostic performance, which may be related to the range of FNAs selected. In the C-TIRADS, multifocal, subperitoneal, tracheal, and recurrent laryngeal nerve invasion are recognized as predictors of poor prognosis in papillary thyroid cancer (18-22). This system recommends FNA for nodules with a diameter larger than 10 mm in category 4A, as well as for nodules with a diameter larger than 5 mm in categories 4B, 4C, and 5, if the aforementioned adverse prognostic factors exist. For the same situation, the other three risk stratification systems in different geographic settings maintain conservative recommendations. To some extent, these factors certainly increase the diagnostic performance of the recommended FNA. In summary, the C-TIRADS evaluation process is relatively simple, rapid, and adaptable to evaluators at different levels. Moreover, it also has high diagnostic performance, especially when high FNA is recommended. Therefore, we believe that in China’s specific geographic environment and national consciousness, the C-TIRADS is indeed more suitable for recommendation.

There are several limitations to our study. First, our study was a retrospective static image analysis, which may affect the assessment of ultrasound features, especially the margins of the nodule as well as the overall internal structure, a shortcoming that may be compensated for by real-time dynamic assessment. Second, the proportion of malignant nodules was greater in this study than in other studies, which may be related to the fact that we are a tertiary referral hospital with a high prevalence of frontal thyroid tumours. Finally, this was a single-centre retrospective data study, and some cases without biopsy or surgical diagnosis were not included in this study, which may have resulted in potential sample errors. Therefore, we hope that future studies will involve more centres and a larger number of cases.

Conclusions

Overall, all four thyroid risk stratification systems with different geographical settings have high diagnostic performance. Although the diagnostic performance of the ACR-TIRADS may be slightly better than that of the other three methods, FNA based on C-TIRADS recommendations has significantly better diagnostic performance and may be more suitable for use in patients with thyroid nodules in China.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-527/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-527/dss

Funding: This work was supported by the Science and Technology Planning Project of Shantou (Nos. 240507196498846 and 240416216497338).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-527/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by institutional ethics board of Cancer Hospital of Shantou University Medical College (No. 2024055) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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