Risk factors associated with preferential lateral lymph node metastasis in papillary thyroid carcinoma

Shao, Liang; Wang, Zhihong; Dong, Wenwu; Sun, Wei; Zhang, Hao

doi:10.1002/cam4.6567

Cited by 4 publications

(7 citation statements)

References 27 publications

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“…In this study, we found that unclear boundaries, nodular microcalcification, tumor-foci numbers, tumor diameter, and lymph node blood-flow signal were independent risk factors for CLNM, consistent with the findings of previous studies ( 4 – 7 , 15 – 17 , 33 , 34 ). All patients were assessed as tumor-free at 12 months post-surgery, which was significantly associated with a reduction in STK1p to disease-free levels ( Figures 4A–D ), indicating that prophylactic CLNM dissection, based on individual patient monitoring, was effective.…”

Section: Discussionsupporting

confidence: 92%

“…Although a series of reports have shown that nomograms based on risk factors determined from ultrasonography or CEUS parameters can be used to evaluate the probability of individual treatment effect in PTC patients with CLNM ( 4 – 7 , 15 – 17 , 33 , 34 ), those characteristics do not measure PTC cell proliferation rate. In this study, we constructed a nomogram prediction model for CLNM, based on ROC curve and multivariate logistic regression analyses.…”

Section: Discussionmentioning

confidence: 99%

“…Thyroid cell function is closely related to the structure and organization of follicles, and polarization is a key factor in hormone production ( 2 ). The most common thyroid cancer is papillary thyroid cancer (PTC), 80%–85% of which derives from well-differentiated follicular thyroid cancer cells and has a good prognosis, and with a 10-year survival of approximately 93%, it is considered an indolent PTC ( 3 ); however, differentiated thyroid carcinoma is characterized by an increased number of tumor foci, expanded total tumor diameter, and metastasis or recurrence in lateral lymph nodes ( 2 , 4 – 7 ). At initial presentation, PTC is associated with a high rate of lymph node metastases (LNMs), with lateral lymph node metastasis (LLNM) usually occurring after central lymph node metastasis (CLNM).…”

Section: Introductionmentioning

confidence: 99%

“…The CLNM is one of the aggressive variants of PTC ( 3 ). Preoperative analysis of ultrasonographical features is valuable for predicting PTC with CLNM ( 4 ). Furthermore, multifocality and bilaterality can be considered risk factors for CLNM ( 5 ), while four or more tumor foci and younger age at LLNM ( 6 ), younger age, male sex, tumor size >0.65 cm, and capsular invasion and/or multifocality are associated with high-risk papillary thyroid microcarcinoma ( 7 ).…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, multifocality and bilaterality can be considered risk factors for CLNM ( 5 ), while four or more tumor foci and younger age at LLNM ( 6 ), younger age, male sex, tumor size >0.65 cm, and capsular invasion and/or multifocality are associated with high-risk papillary thyroid microcarcinoma ( 7 ). Patients with these characteristics are likely to have a poor prognosis and a high mortality rate, and an urgent surgical plan must be arranged ( 4 – 7 ). According to the currently used Tumor–Node–Metastasis staging system (TNM-8) and the previous TNM-7 of PTC, based on a cohort of 1,148 PTC patients, a prognostic value of the disease-free interval (DFI) was estimated.…”

Section: Introductionmentioning

confidence: 99%

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Nomogram model of serum thymidine kinase 1 combined with ultrasonography for prediction of central lymph node metastasis risk in patients with papillary thyroid carcinoma pre-surgery

Song,

Skog,

Wei

et al. 2024

Front. Endocrinol.

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ObjectiveThe aim of this study was to develop a nomogram, using serum thymidine kinase 1 protein (STK1p) combined with ultrasonography parameters, to early predict central lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC) pre-surgery.MethodsPatients with PTC pre-surgery in January 2021 to February 2023 were divided into three cohorts: the observation cohort (CLNM, n = 140), the control cohort (NCLNM, n = 128), and the external verification cohort (CLNM, n = 50; NCLNM, n = 50). STK1p was detected by an enzyme immunodot-blot chemiluminescence analyzer and clinical parameters were evaluated by ultrasonography.ResultsA suitable risk threshold value for STK1p of 1.7 pmol/L was selected for predicting CLNM risk by receiver operating characteristic (ROC) curve analysis. Multivariate analysis identified the following six independent risk factors for CLNM: maximum tumor size >1 cm [odds ratio (OR) = 2.406, 95% confidence interval (CI) (1.279–4.526), p = 0.006]; capsule invasion [OR = 2.664, 95% CI (1.324–5.360), p = 0.006]; irregular margin [OR = 2.922; 95% CI (1.397–6.111), p = 0.004]; CLN flow signal [OR = 3.618, 95% CI (1.631–8.027), p = 0.002]; tumor-foci number ≥2 [OR = 4.064, 95% CI (2.102–7.859), p < 0.001]; and STK1p ≥1.7 pmol/L [OR = 7.514, 95% CI (3.852–14.660), p < 0.001]. The constructed nomogram showed that the area under the ROC curve for the main dataset was 0.867 and that for the validation dataset was 0.830, exhibiting effectivity, and was recalculated to a total score of approximately 383. Through monitoring the response post-surgery, all patients were assessed as tumor-free at 12 months post-surgery, which was significantly associated with a reduction in STK1p to disease-free levels.ConclusionWe demonstrate for the first time that a novel nomogram including STK1p combined with ultrasonography can assist in the clinical prevention of CLNM, by facilitating timely, individualized prophylactic CLNM dissection, thereby reducing the risk of secondary surgery and the probability of recurrence.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Nomogram model of serum thymidine kinase 1 combined with ultrasonography for prediction of central lymph node metastasis risk in patients with papillary thyroid carcinoma pre-surgery

Song,

Skog,

Wei

et al. 2024

Front. Endocrinol.

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Prediction of lateral lymph node metastasis with short diameter less than 8 mm in papillary thyroid carcinoma based on radiomics

Wang,

Zhang,

Zhang

et al. 2024

Cancer Imaging

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Objective The aim of this study was to establish an ensemble learning model based on clinicopathological parameter and ultrasound radomics for assessing the risk of lateral cervical lymph node with short diameter less than 8 mm (small lymph nodes were used instead) metastasis in patients with papillary thyroid cancer (PTC), thereby guiding the selection of surgical methods. Methods This retrospective analysis was conducted on 454 patients diagnosed with papillary thyroid carcinoma who underwent total thyroidectomy and lateral neck lymph node dissection or lymph node intraoperative frozen section biopsy at the First Hospital of China Medical University between January 2015 and April 2022. In a ratio of 8:2, 362(80%) patients were assigned to the training set and 92(20%) patients were assigned to the test set. Clinical pathological features and radomics features related to ultrasound imaging were extracted, followed by feature selection using recursive feature elimination (RFE). Based on distinct feature sets, we constructed ensemble learning models comprising random forest (RF), extreme gradient boosting (XGBoost), categorical boosting (CatBoost), gradient boosting decision tree (GBDT), and light gradient boosting machine (Lightgbm) to develop clinical models, radiomics models, and clinical-radiomic models. Through the comparison of performance metrics such as area under curve (AUC), accuracy (ACC), specificity (SPE), precision (PRE), recall rate, F1 score, mean squared error (MSE) etc., we identified the optimal model and visualized its results using shapley additive exPlanations (SHAP). Results In this study, a total of 454 patients were included, among whom 342 PTC patients had small lymph node metastasis in the lateral neck region, while 112 did not have any metastasis. A total of 1035 features were initially considered for inclusion in this study, which were then narrowed down to 10 clinical features, 8 radiomics features, and 17 combined clinical-omics features. Based on these three feature sets, a total of fifteen ensemble learning models were established. In the test set, RF model in the clinical model is outperforms other models (AUC = 0.72, F1 = 0.75, Jaccard = 0.60 and Recall = 0.84), while CatBoost model in the radiomics model is superior to other models (AUC = 0.91, BA = 0.83 and SPE = 0.76). Among the clinical-radiomic models, Catboost exhibits optimal performance (AUC = 0.93, ACC = 0.88, BA = 0.87, F1 = 0.91, SPE = 0.83, PRE = 0.88, Jaccard = 0.83 and Recall = 0.92). Using the SHAP algorithm to visualize the operation process of the clinical-omics CatBoost model, we found that clinical omics features such as central lymph node metastasis (CLNM), Origin_Shape_Sphericity (o_shap_sphericity), LoG-sigma3_first order_ Skewness (log-3_fo_skewness), wavelet-HH_first order_Skewness (w-HH_fo_skewness) and wavelet-HH_first order_Skewness (sqr_gldm_DNUN) had the greatest impact on predicting the presence of lateral cervical small lymph node metastasis in PTC patients. Conclusions (1) In this study, among the ensemble learning models established based on clinicopathological features and radiomics features for predicting PTC lateral small lymph node metastasis, the clinical-radiomic CatBoost model has the best performance. (2) SHAP can visualize how the clinical and radiomics features affect the results and realize the interpretation of the model. (3) The combined CatBoost model can improve the diagnostic accuracy of suspicious lymph nodes with short diameter < 8 mm that are difficult to obtain accurate puncture results. The combined application of radiomics features is more accurate and reasonable than the prediction of clinical data alone, which helps to accurately evaluate the surgical scope and provide support for individual clinical decision making.

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Risk factors associated with lymph node metastasis in papillary thyroid cancer: a retrospective analysis based on 2428 cases

Yu,

Wu,

Dai

et al. 2024

Preprint

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Background Papillary thyroid cancer (PTC) with lymph node metastasis (LNM) is associated with an increased risk of postoperative recurrence. Understanding the clinical characteristics of PTC patients can help surgeons assess the likelihood of LNM. This study aims to identify risk factors for LNM in PTC patients. Methods We retrospectively analyzed clinical data from 2,428 patients diagnosed with PTC who underwent initial thyroid surgery in our single centre. Risk factors related to central lymph node metastasis (CLNM), lateral lymph node metastasis (LLNM), and skip metastasis were investigated by univariate and multivariate binary logistic regression analyses. Results Univariate analysis revealed that the following factors were associated with an increased likelihood of CLNM (P < 0.05): male gender, age < 45 years, maximal axial diameter (MAD) > 1 cm, body mass index (BMI) ≥ 28 kg/m² and multifocality. Univariate analysis also revealed that patients with age < 45 years, MAD > 1 cm, BMI ≥ 28 kg/m², multifocality, and CLNM demonstrated a higher propensity for LLNM (P < 0.05). Lower pole tumors were more likely to have CLNM than upper pole tumors, while upper pole tumors were more prone to present LLNM (P < 0.05) and skip metastasis (P < 0.05). Multivariable binary logistic regression analysis identified that gender (odds ratio [OR], 1.732; 95% CI, 2.113–2.577; P < 0.001), age (OR, 1.905; 95% CI, 1.596–2.273; P < 0.001), MAD (OR, 4.639; 95% CI, 3.639–5.913; P < 0.001), and multifocality (OR, 1.860; 95% CI, 1.453–2.381; P < 0.001) were independent risk factors for CLNM and MAD (OR, 5.289; 95% CI, 3.777–7.404; P < 0.001), multifocality (OR, 1.858; 95% CI, 1.248–2.766; P = 0.002), and CLNM (OR, 5.030; 95% CI, 3.347–7.561; P < 0.001) for LLNM. Conclusion Despite the overall postoperative recurrence rate in PTC patients is low, identifying risk factors such as male gender, age < 45 years, MAD > 1 cm, multifocality, and CLNM can help predict LNM. In specific cases, selective lymphadenectomy in the central or lateral neck area may be warranted.

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Risk factors associated with preferential lateral lymph node metastasis in papillary thyroid carcinoma

Cited by 4 publications

References 27 publications

Nomogram model of serum thymidine kinase 1 combined with ultrasonography for prediction of central lymph node metastasis risk in patients with papillary thyroid carcinoma pre-surgery

Nomogram model of serum thymidine kinase 1 combined with ultrasonography for prediction of central lymph node metastasis risk in patients with papillary thyroid carcinoma pre-surgery

Prediction of lateral lymph node metastasis with short diameter less than 8 mm in papillary thyroid carcinoma based on radiomics

Risk factors associated with lymph node metastasis in papillary thyroid cancer: a retrospective analysis based on 2428 cases

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