Development of a nomogram for preoperative prediction of malignant risk in thyroid follicular tumors based on multimodal ultrasound and clinical features: A retrospective observational study
- 1Ultrasound Medical Center, The Second Hospital of Lanzhou University, China
Abstract
Background: Preoperative differentiation of thyroid follicular tumors remains challenging because cytology has a limited ability to assess capsular and vascular invasion. This study aimed to develop a nomogram integrating multimodal ultrasound and clinical features to predict the risk of malignancy in follicular thyroid tumors.
Methods: A total of 483 patients with pathologically confirmed follicular thyroid tumors were retrospectively enrolled. Follicular thyroid adenoma was defined as the benign group, whereas follicular tumor of uncertain malignant potential and follicular thyroid carcinoma were combined into the high-risk group. Clinical data and multimodal ultrasound features were collected. Independent predictors were identified using univariate and multivariate logistic regression analyses, and a nomogram was constructed. Model performance was evaluated using the area under the receiver operating characteristic curve, calibration curve, Hosmer–Lemeshow test, and decision curve analysis.
Results: Sex, lesion multiplicity, preoperative thyroglobulin, halo characteristics, “nodule-in-nodule” appearance, and trabecular structure were identified as independent predictors of malignancy (all p < 0.05). The nomogram demonstrated excellent discrimination, with an area under the receiver operating characteristic curve of 0.94 (95% confidence interval: 0.90–0.97). Internal validation using 1000 bootstrap resamples yielded a mean area under the receiver operating characteristic curve of 0.928 (95% confidence interval: 0.915–0.934). Calibration analysis showed good agreement between predicted and observed outcomes (Hosmer–Lemeshow test, p = 0.578). Decision curve analysis indicated a significant net clinical benefit across a threshold probability range of 15%–85%.
Conclusion: In this exploratory retrospective study, the proposed nomogram showed preliminary potential for the preoperative prediction of malignant risk in thyroid follicular tumors. However, because of the lack of external validation, these findings should be considered hypothesis-generating. The model requires validation in independent cohorts before clinical application.
Related
- Development and external validation of a preoperative prediction model for in-hospital major adverse cardiovascular events after hip fracture surgery in older adults: a retrospective two-center study.
- Development and Internal Validation of a Clinical Prediction Model for Coronary Slow Flow Phenomenon in Type 2 Diabetes: A Retrospective Observational Study.
- Preoperative prediction of microvascular invasion in hepatocellular carcinoma using routine clinical variables: development and temporal validation of an interpretable random forest model in a single-center retrospective cohort study.
- Development and validation of machine learning models for preoperative prediction of perioperative outcomes in patients with thymic epithelial tumors
- Development and validation of a machine learning model for preoperative prediction of intraoperative hypothermia in gynecological laparoscopic surgery: a two-center cohort study
BibTeX
@article{tingkun2026development,
title = {{Development of a nomogram for preoperative prediction of malignant risk in thyroid follicular tumors based on multimodal ultrasound and clinical features: A retrospective observational study}},
author = {Hou Tingkun and Song Hongyan and Zheng Ran and Wang Yanfang and Nie Fang},
journal = {The Journal of International Medical Research},
year = {2026},
month = sep,
doi = {10.1177/03000605261467637},
url = {https://doi.org/10.1177/03000605261467637},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Development of a nomogram for preoperative prediction of malignant risk in thyroid follicular tumors based on multimodal ultrasound and clinical features: A retrospective observational study
AU - Hou Tingkun
AU - Song Hongyan
AU - Zheng Ran
AU - Wang Yanfang
AU - Nie Fang
PY - 2026
DA - 2026/09/29
JO - The Journal of International Medical Research
DO - 10.1177/03000605261467637
UR - https://doi.org/10.1177/03000605261467637
AB - Background: Preoperative differentiation of thyroid follicular tumors remains challenging because cytology has a limited ability to assess capsular and vascular invasion. This study aimed to develop a nomogram integrating multimodal ultrasound and clinical features to predict the risk of malignancy in follicular thyroid tumors. Methods: A total of 483 patients with pathologically confirmed follicular thyroid tumors were retrospectively enrolled. Follicular thyroid adenoma was defined as the benign group, whereas follicular tumor of uncertain malignant potential and follicular thyroid carcinoma were combined into the high-risk group. Clinical data and multimodal ultrasound features were collected. Independent predictors were identified using univariate and multivariate logistic regression analyses, and a nomogram was constructed. Model performance was evaluated using the area under the receiver operating characteristic curve, calibration curve, Hosmer–Lemeshow test, and decision curve analysis. Results: Sex, lesion multiplicity, preoperative thyroglobulin, halo characteristics, “nodule-in-nodule” appearance, and trabecular structure were identified as independent predictors of malignancy (all p < 0.05). The nomogram demonstrated excellent discrimination, with an area under the receiver operating characteristic curve of 0.94 (95% confidence interval: 0.90–0.97). Internal validation using 1000 bootstrap resamples yielded a mean area under the receiver operating characteristic curve of 0.928 (95% confidence interval: 0.915–0.934). Calibration analysis showed good agreement between predicted and observed outcomes (Hosmer–Lemeshow test, p = 0.578). Decision curve analysis indicated a significant net clinical benefit across a threshold probability range of 15%–85%. Conclusion: In this exploratory retrospective study, the proposed nomogram showed preliminary potential for the preoperative prediction of malignant risk in thyroid follicular tumors. However, because of the lack of external validation, these findings should be considered hypothesis-generating. The model requires validation in independent cohorts before clinical application.
SN - 0300-0605
SN - 1473-2300
ER -