Nomogram model based on preoperative serum thyroglobulin and clinical characteristics of papillary thyroid carcinoma to predict cervical lymph node metastasis

Chang, Qungang; Zhang, Jieming; Wang, Yaqian; Li, Hongqiang; Du, Xin; Zuo, Daohong; Yin, Detao

doi:10.3389/fendo.2022.937049

Cited by 16 publications

(14 citation statements)

References 44 publications

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“…In this study, the proportion of LLNM in PTC patients reached 59.1%, which was consistent with previous studies [3,11]. However, it is signi cantly higher than the proportion in some studies (about 10-20%) [9,10]. This may be due to the fact that many suspected PTC patients with a mass less than 1 cm and no obvious cervical lymph node metastasis currently take follow-up observation rather than active surgery.…”

Section: Factor Selection and Nomogram Constructionsupporting

confidence: 90%

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Ultrasound-based nomogram for predicting lateral cervical lymph node metastasis in thyroid papillary carcinoma

Chen

Cang

et al. 2023

Preprint

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Objective: To explore the risk factors of lateral cervical lymph node metastasis(LLNM) in thyroid papillary carcinoma (PTC), establish a nomograph prediction model to predict the probability of LLNM before operation, reduce the risk of recurrence, avoid secondary surgery, and achieve the goal of accurate treatment. Methods: In this retrospective study, 242 patients were enrolled and randomly divided into two groups according to the ratio of 7:3. The preoperative clinical data of patients (including ultrasonic characteristics and selected clinical characteristics) were collected, and least absolute shrinkage and selection operator (Lasso) in the training cohort was used to screen the influencing factors. Based on the results of multivariable logistic regression, the nomograph model is established, and its performance is evaluated by its identification, calibration and clinical usefulness in training and validation cohorts. Results: This study showed that age>45 years (OR 0.340; 95%CI 0.129-0.856), abnormal serum TG (OR 3.626; 95%CI 1.397-10.187), thyroid tumer location1 (OR 0.250; 95%CI 0.083-0.702), US-reported positive central cervical lymph node (CLN) (OR 3.116; 95%CI 1.152-8.601), and US-reported positive LLN (OR 8.426; 95%CI 3.192-23.779) were independent risk factors for LLNM of PTC. The nomogram constructed based on the above factors has good resolution and calibration in predicting the LLNM of PTC. The Concordance index (C-index) of the experimental group and the validation group are 0.880 and 0.937, respectively. Conclusion: The nomogram based on ultrasound and clinical features constructed in this study has good performance in non-invasive predicting LLNM of PTC and is expected to promote clinical decision-making.

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Section: Factor Selection and Nomogram Constructionsupporting

confidence: 90%

“…Age has been considered as an independent risk factor for lymph node metastasis in PTC patients [10,12].…”

Section: Factor Selection and Nomogram Constructionmentioning

confidence: 99%

Ultrasound-based nomogram for predicting lateral cervical lymph node metastasis in thyroid papillary carcinoma

Chen

Cang

et al. 2023

Preprint

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“…Some studies concluded that tumor size ≥1 cm is more likely to develop CNLNM than tumor size <1 cm ( 20 – 22 ), although several studies have not segmented tumors by 1 cm ( 23 – 29 ), and some studies concluded that larger tumor volume is more likely to develop CNLNM ( 30 , 31 ). In sum, CNLNM is generally more likely to occur with larger tumors.…”

Section: Discussionmentioning

confidence: 99%

A nomogram based on clinicopathological and ultrasound characteristics to predict central neck lymph node metastases in papillary thyroid cancer

Chen,

Jiang,

Yao

et al. 2024

Front. Endocrinol.

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PurposePapillary thyroid cancer (PTC) has grown rapidly in prevalence over the past few decades, and central neck lymph node metastasis (CNLNM) is associated with poor prognoses. However, whether to carry out preventive central neck lymph node dissection (CNLND) is still controversial. We aimed to construct a prediction model of CNLNM to facilitate making clinical surgical regimens.MethodsA total of 691 patients with PTC between November 2018 and December 2021 were included in our study. Univariate and multivariate analyses were performed on basic information and clinicopathological characteristics, as well as ultrasound characteristics (American College of Radiology (ACR) scores). The prediction model was constructed and performed using a nomogram, and then discriminability, calibrations, and clinical applicability were evaluated.ResultsFive variables, namely, male, age >55 years, clinical lymph node positivity, tumor size ≥1 cm, and ACR scores ≥6, were independent predictors of CNLNM in the multivariate analysis, which were eventually included to construct a nomogram model. The area under the curve (AUC) of the model was 0.717, demonstrating great discriminability. A calibration curve was developed to validate the calibration of the present model by bootstrap resampling, which indicated that the predicted and actual values were in good agreement and had no differentiation from the ideal model. The decision curve analysis (DCA) indicated that the prediction model has good clinical applicability.ConclusionsOur non-invasive prediction model combines ACR scores with clinicopathological features presented through nomogram and has shown good performance and application prospects for the prediction of CNLNM in PTCs.

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“…[15][16][17] Most of the decisive factors involved in the published literature are independent and single, including age, gender, tumor size, and preoperative Tg. [41][42][43][44] Therefore, our study not only included the clinicopathological features closely related to LLNM but also introduced iodine nutrition-related markers, including SIC, TSH, and Tg.…”

Section: Discussionmentioning

confidence: 99%

Nomogram Model Based on Iodine Nutrition and Clinical Characteristics of Papillary Thyroid Carcinoma to Predict Lateral Lymph Node Metastasis

Wang,

Gao,

Zong

et al. 2023

Cancer Control

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Objective Preoperative evaluation of lateral lymph node metastasis (LLNM) in patients with papillary thyroid carcinoma (PTC) has been one of the major clinical challenges. This study aims to develop and validate iodine nutrition-related nomogram models to predict lateral cervical lymph node metastasis in patients with PTC. Methods This is a retrospective study. Urinary iodine concentration (UIC) and serum iodine concentration (SIC) were measured in 187 LLNM patients and 289 non-LLNM (NLLNM) patients. All patients were randomized 3:1 into the training cohort (n = 355) and the validation cohort (n = 121). Using logistic regression analysis, we analyzed the influence of iodine nutrition-related factors and clinicopathological characteristics on LLNM in PTC patients. Lasso regression method was used to screen risk factors and construct a nomogram for predicting LLNM. The receiver operating characteristic curve (ROC curve), calibration curve, and decision curve analysis (DCA) of the nomogram models were carried out for the training and validation cohorts. Results Gender, SIC, smoking history, drinking history, family history of PTC, multifocality, bilateral or unilateral tumors, TSH, Tg, and tumor size were included in the nomogram model predicting LLNM, with an area under the curve (AUC) of .795. The nomogram model showed good calibration and clinical benefit in both the training and validation cohorts. Conclusion The nomogram model based on iodine nutrition and other clinicopathological features is effective for predicting the lateral lymph node metastasis in PTC patients.

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Nomogram model based on preoperative serum thyroglobulin and clinical characteristics of papillary thyroid carcinoma to predict cervical lymph node metastasis

Cited by 16 publications

References 44 publications

Ultrasound-based nomogram for predicting lateral cervical lymph node metastasis in thyroid papillary carcinoma

Ultrasound-based nomogram for predicting lateral cervical lymph node metastasis in thyroid papillary carcinoma

A nomogram based on clinicopathological and ultrasound characteristics to predict central neck lymph node metastases in papillary thyroid cancer

Nomogram Model Based on Iodine Nutrition and Clinical Characteristics of Papillary Thyroid Carcinoma to Predict Lateral Lymph Node Metastasis

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