UNASSIGNED: The prevalence of thyroid malignancies has sharply elevated in the past few years, and a large number of newly diagnosed thyroid malignancies was papillary thyroid microcarcinomas (PTMC). The efficacy of prophylactic central lymph node dissection (PCLND) in patients with clinical lymph node-negative (cN0) PTMC is still debatable. In this study, we aimed to create a predictive model to assess the likelihood of central lymph node metastasis (CLNM) in cN0 PTMC.
UNASSIGNED: Two hundred and fifty three patients diagnosed with cN0 PTMC who received surgery in the First People\'s Hospital of Kunshan from October 2018 to June 2023 were enrolled. Multivariate logistic regression was employed to evaluate the patient\'s clinical and ultrasonographic information to determine independent factors. Two prediction models were generated and their ability to evaluate the likelihood of CLNM in cN0 PTMC was determined and compared.
UNASSIGNED: Multivariate analysis based on clinical characteristics revealed that, CLNM was markedly linked to age, tumor size, and extrathyroidal infiltration in cN0 PTMC. Multivariate analysis utilizing clinical and ultrasound features demonstrated that age, tumor size, extrathyroidal infiltration, shape, microcalcification were independent risk factors for CLNM. The analysis of the receiver operating characteristic curve demonstrated that the predictive nomogram utilizing clinical and ultrasound features was more beneficial for predicting CLNM. And decision curve demonstrates the same. The model\'s calibration curve exhibited strong consistency.
UNASSIGNED: Age, tumor size, extrathyroidal infiltration, shape, microcalcification are significant independent factors of CLNM in cN0 PTMC. A predictive model derived from these independent clinical and ultrasound factors has a good value, but further validation is still required.

OBJECTIVE: Mono-focal papillary thyroid carcinoma (PTC) patients with encapsulated tumor have traditionally been considered as low central lymph node metastasis (CLNM) risk subgroup. The aim of the research was to quantitatively predict the probability of CLNM for mono-focal PTC patients with encapsulated tumor as confirmed by preoperative ultrasound based on pre- and post-operative indexes respectively to guide the selection of prophylactic central lymph node dissection (CLND) and follow-up strategies.
METHODS: A total of 1014 mono-focal PTC patients with encapsulated tumor as confirmed by preoperative ultrasound from three medical centers were retrospectively analyzed, with 534 patients served as Training group and 480 patients as Validation group.
RESULTS: Multivariate analyses showed that age < 55 years old, male, clinical maximum tumor diameter (cMTD) > 0.5 cm, pathological maximum tumor diameter (pMTD) > 0.5 cm, and the presence of microscopic thyroid capsular invasion (mTCI) were independent CLNM risk factors. These were used to construct two nomograms that can effectively predict the central neck involvement in mono-focal PTC patients with encapsulated tumor. The first nomogram (pre-model) provides quantitative assessment on the necessity of prophylactic CLND, while the second nomogram (post-model) informs postoperative follow-up strategies.
CONCLUSIONS: Meticulous and comprehensive stratification flow charts that quantitatively evaluate the risk of central lymph node metastasis both pre- and post-operatively were constructed for mono-focal PTC patients with encapsulated tumor as confirmed by preoperative ultrasound, which may benefit both clinical decision-making of prophylactic CLND and postoperative follow-up strategies for the management of neck regions.

The central lymph node metastasis (CLNM) status in the cervical region serves as a pivotal determinant for the extent of surgical intervention and prognosis in papillary thyroid carcinoma (PTC). This paper seeks to devise and validate a predictive model based on clinical parameters for the early anticipation of high-volume CLNM (hv-CLNM, > 5 nodes) in high-risk patients. A retrospective analysis of the pathological and clinical data of patients with PTC who underwent surgical treatment at Medical Centers A and B was conducted. The data from Center A was randomly divided into training and validation sets in an 8:2 ratio, with those from Center B serving as the test set. Multifactor logistic regression was harnessed in the training set to select variables and construct a predictive model. The generalization ability of the model was assessed in the validation and test sets. The model was evaluated through the receiver operating characteristic area under the curve (AUC) to predict the efficiency of hv-CLNM. The goodness of fit of the model was examined via the Brier verification technique. The incidence of hv-CLNM in 5897 PTC patients attained 4.8%. The occurrence rates in males and females were 9.4% (128/1365) and 3.4% (156/4532), respectively. Multifactor logistic regression unraveled male gender (OR = 2.17, p < .001), multifocality (OR = 4.06, p < .001), and lesion size (OR = 1.08 per increase of 1 mm, p < .001) as risk factors, while age emerged as a protective factor (OR = 0.95 per an increase of 1 year, p < .001). The model constructed with four predictive variables within the training set exhibited an AUC of 0.847 ([95%CI] 0.815-0.878). In the validation and test sets, the AUCs were 0.831 (0.783-0.879) and 0.845 (0.789-0.901), respectively, with Brier scores of 0.037, 0.041, and 0.056. Subgroup analysis unveiled AUCs for the prediction model in PTC lesion size groups (≤ 10 mm and > 10 mm) as 0.803 (0.757-0.85) and 0.747 (0.709-0.785), age groups (≤ 31 years and > 31 years) as 0.778 (0.720-0.881) and 0.837 (0.806-0.867), multifocal and solitary cases as 0.803 (0.767-0.838) and 0.809 (0.769-0.849), and Hashimoto\'s thyroiditis (HT) and non-HT cases as 0.845 (0.793-0.897) and 0.845 (0.819-0.871). Male gender, multifocality, and larger lesion size are risk factors for hv-CLNM in PTC patients, whereas age serves as a protective factor. The clinical predictive model developed in this research facilitates the early identification of high-risk patients for hv-CLNM, thereby assisting physicians in more efficacious risk stratification management for PTC patients.

UNASSIGNED: To assess the risk factors of cervical lymph node metastasis in elderly patients aged 65 years and older diagnosed with papillary thyroid cancer (PTC).
UNASSIGNED: In this retrospective analysis, we included a total of 328 elderly patients aged 65 years and older diagnosed with PTC. We thoroughly examined clinical features from these patients. Utilizing univariate and multivariate logistic regression analyses, we aimed to identify factors contributing to the risk of central and lateral lymph node metastasis (CLNM/LLNM) in this specific population of PTC patients aged 65 years and older.
UNASSIGNED: In the univariate analysis, CLNM was significantly associated with tumor size, multifocality, bilaterality, and microcalcification, while only tumor size ≥ 1cm (OR = 0.530, P = 0.019, 95% CI = 0.311 - 0.900) and multifocality (OR = 0.291, P < 0.001, 95% CI = 0.148 - 0.574) remained as risk factors in the multivariate analysis. LLNM was confirmed to be associated with male (OR = 0.454, P < 0.020, 95% CI = 0.233 - 0.884), tumor size ≥ 1cm (OR = 0.471, P = 0.030, 95% CI = 0.239 - 0.928), age ≥ 70 (OR = 0.489, P = 0.032, 95% CI = 0.254 - 0.941), and microcalcification (OR = 0.384, P = 0.008, 95% CI = 0.189 - 0.781) in the multivariate analysis. In elderly PTC patients with CLNM, male gender (OR = 0.350, P = 0.021, 95% CI = 0.143 - 0.855), age ≥ 70 (OR = 0.339, P = 0.015, 95% CI = 0.142 - 0.810), and bilaterality (OR = 0.320, P = 0.012, 95% CI = 0.131 - 0.779) were closely associated with concomitant LLNM in both univariate and multivariate analyses.
UNASSIGNED: For elderly PTC patients aged 65 and older, tumor size ≥ 1cm and multifocality are significant risk factors for CLNM. Meanwhile, male, tumor size ≥ 1cm, age ≥ 70, and microcalcification are crucial predictors for LLNM. In patients already diagnosed with CLNM, male, age ≥ 70, and bilaterality increase the risk of LLNM.

OBJECTIVE: The aim of this study is to investigate the risk factors for lateral cervical lymph node metastasis in papillary thyroid carcinoma (PTC).
METHODS: Clinicopathological data (age, gender, Hashimoto\'s thyroiditis, preoperative circulating tumor cells (CTCs), multifocal, maximum lesion diameter, invaded capsule, T stage, and lymph node metastasis) of 830 PTC patients diagnosed and treated in Meizhou People\'s Hospital from June 2021 to April 2023 were collected. The related factors of lateral cervical lymph node metastasis were analyzed.
RESULTS: There were 334 (40.2%), and 103 (12.4%) PTC patients with central lymph node metastasis, and lateral cervical lymph node metastasis, respectively. Compared with patients without lateral cervical lymph node metastasis, PTC patients with lateral cervical lymph node metastasis had a higher proportion of multifocal, maximum lesion diameter > 1 cm, invaded capsule, T3-T4 stage. Regression logistic analysis showed that male (odds ratio (OR): 2.196, 95% confidence interval (CI): 1.279-3.769, p = 0.004), age < 55 years old (OR: 2.057, 95% CI: 1.062-3.988, p = 0.033), multifocal (OR: 2.759, 95% CI: 1.708-4.458, p < 0.001), maximum lesion diameter > 1 cm (OR: 5.408, 95% CI: 3.233-9.046, p < 0.001), T3-T4 stage (OR: 2.396, 95% CI: 1.241-4.626, p = 0.009), and invaded capsule (OR: 2.051, 95% CI: 1.208-3.480, p = 0.008) were associated with lateral cervical lymph node metastasis.
CONCLUSIONS: Male, age < 55 years old, multifocal, maximum lesion diameter > 1 cm, T3-T4 stage, and invaded capsule were independent risk factors for lateral cervical lymph node metastasis in PTC.

UNASSIGNED: The relationship between Hashimoto\'s thyroiditis (HT) and papillary thyroid microcarcinoma (PTMC) is controversial. These include central lymph node metastasis (CLNM), which affects the prognosis of PTMC patients. This study aimed to establish a predictive model combining ultrasonography and clinicopathological features to accurately evaluate latent CLNM in PTMC patients with HT at the clinical lymph node-negative (cN0) stage.
UNASSIGNED: In this study, 1102 PTMC patients who received thyroidectomy and central cervical lymph node dissection (CLND) from the First Affiliated Hospital of Shandong First Medical University from January 2021 to December 2022 and the 960th Hospital of PLA from January 2021 to December 2022 were jointly collected. The clinical differences between PTMCs with HT and those without HT were compared. A total of 373 PTMCs with HT in cN0 were randomly divided into a training cohort and a validation cohort. By analyzing and screening the risk factors of CLNM, a nomogram model was established and verified. The predictive performance was measured by the receiver operating characteristic (ROC) curve, calibration curve, and clinical decision curve analysis (DCA).
UNASSIGNED: The ratio of central lymph node metastasis (CLNMR) in PTMCs with HT was 0.0% (0.0%, 15.0%) and 7.7% (0.0%, 40.0%) in the non-HT group (P<0.001). Multivariate logistic regression analysis showed that age, gender, calcification, adjacent to trachea or capsule, and TPOAB were predictors of CLNM in PTMCs with HT. The areas under the curve (AUC) of the prediction models in the training cohort and the validation cohort were 0.835 and 0.825, respectively, which showed good differentiation ability. DCA indicates that the prediction model also has high net benefit and clinical practical value.
UNASSIGNED: This study found that CLN involvement was significantly reduced in PTMC patients with HT, suggesting that different methods should be used to predict CLNM in PTMC patients with HT and without HT, to more accurately assist preoperative clinical evaluation. The actual CLNM situation of PTMCs with HT in cN0 can be accurately predicted by the combination of ultrasonography and clinicopathological features.

OBJECTIVE: The characteristics of cervical lymph node involvement in papillary thyroid carcinoma (PTC) patients with different degree of capsular invasion remains unclear, especially for those with mono-focal lesion who have traditionally been considered as low neck metastasis risk subgroup.
METHODS: Retrospective cohort study.
METHODS: Three academic teaching hospital.
METHODS: A total of 1276 mono-focal PTC patients were retrospectively analyzed.
RESULTS: Mono-focal PTC patients with extrathyroidal extension (ETE) showed significantly higher central lymph node metastasis (CLNM) rate than those without. For patients with no gross ETE (gETE), those with minimal ETE (mETE) also showed more commonly CLNM than those with encapsulated lesions. However, the lateral lymph node metastasis (LLNM) rates of patients with mETE and encapsulated tumors were comparable, both lower than that of patients with gETE. Age ≥40, male, and MTD ≥0.5 cm were identified as independent risk factors of CLNM for those with encapsulated tumors and were enrolled for creating a prediction model. In terms of LLNM, only MTD ≥1.0 cm was confirmed as independent risk factors of LLNM for patients with positive gETE.
CONCLUSIONS: The presence and degree of ETE may have different effects on the risk of central and lateral lymph node metastasis. gETE demonstrates a strong correlation with both CLNM and LLNM while mETE is only associated with CLNM in mono-focal PTC patients. A comprehensive model is established in the aim of predicting neck involvement according to the capsular status and the corresponding stratified risk factors, which may aid clinical decision-making for the management of neck regions.

OBJECTIVE: This retrospective study involving a large dataset of unilateral multifocal papillary thyroid carcinoma (UM-PTC) sought to identify factors that predict central lymph node metastases (CLNM) in patients.
METHODS: We identified a cohort of 158 patients who underwent cervical ultrasonography followed by UM-PTC diagnosis based on postoperative pathology. The relationship between CLNM and UM-PTC clinical ultrasound features was evaluated using univariate and multivariate analyses. Receiver operating characteristic (ROC) curve analysis was used to determine the ability of total tumor diameter (TTD) to predict CLNM.
RESULTS: Among the 158 UM-PTC patients, the incidence of CLNM was 29.7% (47/158). Univariate and multivariate analyses revealed that a number of similarity of sonographic features (NSSF) ≥4 (odds ratio [OR] = 11.335, 95% confidence interval [CI]: 3.95-32.50, p = 0.000), microcalcifications (OR = 3.54, 95% CI: 1.30-9.70, p = 0.014), a TTD of ≥2 cm (OR = 4.48, 95% CI: 1.62-12.34, p = 0.004), number of nodules ≥3 (OR = 13.17, 95% CI: 3.24-53.52, p = 0.000), and Lateral cervical lymph node metastasis (LLNM) (OR = 5.57, 95% CI: 1.59-19.48, p = 0.007) were independently associated with CLNM in UM-PTC. ROC curve analysis revealed that the TTD cut-off of 1.795 cm had a sensitivity of 0.723 and a specificity of 0.676 for predicting CLNM.
CONCLUSIONS: Patients with UM-PTC are at high risk of CLNM. NSSF ≥4, microcalcifications, TTD of ≥2 cm, LLNM, and a number of nodules ≥3 were independently associated with CLNM. Our data show that ultrasound may guide surgical decisions in the treatment of UM-PTC.

UNASSIGNED: In papillary thyroid carcinoma (PTC) patients with Hashimoto\'s thyroiditis (HT), preoperative ultrasonography frequently reveals the presence of enlarged lymph nodes in the central neck region. These nodes pose a diagnostic challenge due to their potential resemblance to metastatic lymph nodes, thereby impacting the surgical decision-making process for clinicians in terms of determining the appropriate surgical extent.
UNASSIGNED: Logistic regression analysis was conducted to identify independent risk factors associated with central lymph node metastasis (CLNM) in PTC patients with HT. Then a prediction model was developed and visualized using a nomogram. The stability of the model was assessed using ten-fold cross-validation. The performance of the model was further evaluated through the use of ROC curve, calibration curve, and decision curve analysis.
UNASSIGNED: A total of 376 HT PTC patients were included in this study, comprising 162 patients with CLNM and 214 patients without CLNM. The results of the multivariate logistic regression analysis revealed that age, Tg-Ab level, tumor size, punctate echogenic foci, and blood flow grade were identified as independent risk factors associated with the development of CLNM in HT PTC. The area under the curve (AUC) of this model was 0.76 (95% CI [0.71-0.80]). The sensitivity, specificity, accuracy, and positive predictive value of the model were determined to be 88%, 51%, 67%, and 57%, respectively.
UNASSIGNED: The proposed clinic-ultrasound-based nomogram in this study demonstrated a favorable performance in predicting CLNM in HT PTCs. This predictive tool has the potential to assist clinicians in making well-informed decisions regarding the appropriate extent of surgical intervention for patients.

Central lymph node metastasis (CLNM) of papillary thyroid carcinoma (PTC) is common. In our study, we built a nomogram to predict CLNM. We retrospectively analyzed 1,392 PTC patients. This group of patients was divided into a training cohort (including 1,009 patients) and a validation cohort (including 383 patients). Analyses of the correlation between inflammatory indicators, ultrasonic characteristics, pathological characteristics and CLNM were conducted. In the training cohort and validation cohort, the metastatic rates of CLNM were 60.16% and 64.23%, respectively. Univariate and multivariate logistic regression analyses demonstrated that Hashimoto\'s thyroiditis (HT), calcification, multifocality, capsule invasion, PLR (platelet-lymphocyte ratio) ≤ 130.34, large tumors and middle and lower positions were independent risk factors for CLNM. Then, we constructed a nomogram. The nomogram had good discrimination regardless of whether there was CLNM, with a C-index of 0.809. The calibration curve indicated that the nomogram had good visual and quantitative consistency (p = 0.213). Decision curve analysis showed that the nomogram improved the net clinical benefit with a threshold probability of 0-82% in the training cohort and 0-71% in the validation cohort. We constructed a nomogram to predict CLNM in PTC and assist surgeons in making personalized clinical decisions for PTC.