cN0 Papillary Thyroid Microcarcinoma Research Articles

Artificial neural network prediction of postoperative complications in papillary thyroid microcarcinoma based on preoperative ultrasonographic features.

To predict post-thyroidectomy complications in papillary thyroid microcarcinoma (PTMC) patients using a deep learning model based on preoperative ultrasonographic features. This study addresses the global rise in PTMC incidence and the challenges in treatment decision-making with high-resolution ultrasonography. This study enrolled 1638 patients with clinically staged cN0 PTMC who received surgical treatment from 1997 to 2019 at Beijing Friendship Hospital. Deep learning model was developed using fully connected neural network. Feature selection included 1000 iterations of Bootstrap sampling and Recursive Feature Elimination (RFE) to identify the top 10 features. Data preprocessing involved normalization and imputation for missing values. SMOTE addressed class imbalance. The model was trained and tested on random data split, with performance metrics including Accuracy (ACC), Area Under the Curve (AUC), Sensitivity (SEN), and Specificity (SPE), visualized through a ROC curve and confusion matrix. The fully connected deep neural network model demonstrated high accuracy (ACC 0.81), Area Under the Curve (AUC 0.74), sensitivity (SEN 0.65), and specificity (SPE 0.83) and visualized by ROC curve and confusion matrix. These results highlight the model's reliability and potential as an effective tool in predicting postoperative complications and assisting in clinical decision-making for PTMC patients. This study highlights the potential of deep learning in enhancing medical predictions and personalized healthcare. Despite promising results, limitations include a single-center data source and unconsidered factors like lifestyle and genetics. Future research should expand data sources, include more influencing factors, and refine algorithms to improve accuracy and applicability in thyroid cancer treatment.

A model based on ultrasound and clinical factors to predict central lymph node metastasis in cN0 papillary thyroid microcarcinoma

ObjectiveThe 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. MethodsTwo 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. ResultsMultivariate 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. ConclusionsAge, 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.

The role of intraoperative central lymph node biopsy in the treatment of clinically low-risk PTMC.

To evaluate the role of intraoperative frozen biopsy of central lymph nodes in central neck dissection and thyroidectomy in patients of unilateral, clinically negative nodes (cN0) papillary thyroid microcarcinoma (PTMC) without extra-glandular invasion. The clinical data of 465 patients were collected retrospectively. Part of prelaryngeal, pretracheal and ipsilateral paratracheal lymph nodes were taken for frozen pathological examination during the operation. Then the thyroid lobe on the tumor side and isthmus were excised, and central neck dissection of the affected side was performed in all patients. The number of metastases in entire central lymph nodes of the affected side can be obtained by postoperative paraffin pathology. If the number of positive lymph nodes during surgery is ≥3, contralateral gland resection was performed. In this group of 465 patients, there were 186 cases with central lymph node metastasis. The Kappa coefficient of consistency between frozen pathology and paraffin pathology in central lymph nodes was 0.605. The ROC curve for the number of intraoperative frozen metastases-postoperative pathological metastases over 5 showed that the AUC of the curve was 0.793, while the maximum Youden index was 0.5259, whose corresponding number of positive lymph nodes was 3. Intraoperative central lymph nodes biopsy can be used as an important indicator for the status of central lymph node metastasis in unilateral cN0 PTMC patients without extra-glandular invasion and a determinant for central lymph node dissection. While the number of positive lymph nodes intraoperatively is ≥3, total thyroidectomy should be considered.

The model for predicting the central lymph node metastasis in cN0 papillary thyroid microcarcinoma with Hashimoto's thyroiditis.

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. 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). 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. 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.

Characteristics and risk factors of cervical lymph node metastasis in cN0 papillary thyroid microcarcinoma of the isthmus.

The surgical resection range of papillary thyroid microcarcinoma of the isthmus (PTMCI) is controversial, and the guidelines do not fully guide the central lymph node dissection (CLND).We retrospectively studied the comparison of PTMCI (Group A, n = 65 cases) and non-PTMCI (Group B, n = 80 cases). Based on whether central lymph node metastasis (CLNM) was further detected, they were further divided into the PTMCI with CLNM (group C, n = 42 cases), the PTMCI without CLNM (group D, n = 23 cases), the non-PTMCI with CLNM (group E, n = 45 cases), the non-PTMCI without CLNM (group F, n = 35 cases). All patients underwent total thyroidectomy and CLND. The CLNM pathological examination was divided into right recurrent laryngeal nerve superficial lymph nodes (Right VI a), right recurrent laryngeal nerve deep lymph nodes (Right VI b), left VI area lymph nodes (Left VI), prelaryngeal lymph node, and pretracheal lymph node. The extent of lymph node metastasis and risk factors of PTMCI were analyzed by univariate and multivariate analysis. The ROC curve was used to calculate the maximum diameter of the tumor and the Youden index was calculated to analyze the impact of diameter on the risk factors for CLNM in PTMCI. To construct a prediction model of transfer risk of high risk factors by Nomogram, there were significant differences in prelaryngeal lymph nodes (p = 0.034) and pretracheal lymph nodes ( n = 0.035) between group A and group B, and the risk factors of lymph node metastasis were tumor invasion (p = 0.003), multifocality (p = 0.001), and the maximum tumor diameter≧6.5mm. PTMCI is more prone to metastasis of pretracheal lymph nodes and prelaryngeal lymph nodes, and the presence of tumor invasion, multifocality, and tumor diameter≧6.5mm are high risk factors for metastasis in PTMCI. According to the prediction model, with all risk factors the risk of cervical lymph node metastasis is up to 90%.

Development of a nomogram for prediction of central lymph node metastasis of papillary thyroid microcarcinoma

BackgroundPapillary thyroid carcinoma (PTC) is the most frequent malignant tumor in thyroid carcinoma. The aim of this study was to explore the risk factors associated with central lymph node metastasis in papillary thyroid microcarcinoma (PTMC) and establish a nomogram model that can assess the probability of central lymph node metastasis (CLNM).MethodsThe clinicopathological data of 377 patients with cN0 PTMC were collected and analyzed from The Second Affiliated Hospital of Fujian Medical University from July 1st, 2019 to December 30th, 2021. All patients were examined by underwent ultrasound (US), found without metastasis to central lymph nodes, and diagnosed with PTMC through pathologic examination. All patients received thyroid lobectomy or total thyroidectomy with therapeutic or prophylactic central lymph node dissection (CLND). R software (Version 4.1.0) was employed to conduct a series of statistical analyses and establish the nomogram.ResultsA total of 119 patients with PTMC had central lymph node metastases (31.56%). After that, age (P < 0.05), gender (P < 0.05), tumor size (P < 0.05), tumor multifocality (P < 0.05), and ultrasound imaging-suggested tumor boundaries (P < 0.05) were identified as the risk factors associated with CLNM. Subsequently, multivariate logistic regression analysis indicated that the area under the receiver operating characteristic (ROC) curve (AUC) of the training cohort was 0.703 and that of the validation cohort was 0.656, demonstrating that the prediction ability of this model is relatively good compared to existing models. The calibration curves indicated a good fit for the nomogram model. Finally, the decision curve analysis (DCA) showed that a probability threshold of 0.15–0.50 could benefit patients clinically. The probability threshold used in DCA captures the relative value the patient places on receiving treatment for the disease, if present, compared to the value of avoiding treatment if the disease is not present.ConclusionCLNM is associated with many risk factors, including age, gender, tumor size, tumor multifocality, and ultrasound imaging-suggested tumor boundaries. The nomogram established in our study has moderate predictive ability for CLNM and can be applied to the clinical management of patients with PTMC. Our findings will provide a better preoperative assessment and treatment strategies for patients with PTMC whether to undergo central lymph node dissection.

Ultrasound radiomics signature for predicting central lymph node metastasis in clinically node-negative papillary thyroid microcarcinoma

BackgroundWhether prophylactic central lymph node dissection is necessary for patients with clinically node-negative (cN0) papillary thyroid microcarcinoma (PTMC) remains controversial. Herein, we aimed to establish an ultrasound (US) radiomics (Rad) score for assessing the probability of central lymph node metastasis (CLNM) in such patients.Methods480 patients (327 in the training cohort, 153 in the validation cohort) who underwent thyroid surgery for cN0 PTMC at two institutions between January 2018 and December 2020 were included. Radiomics features were extracted from the US images. Least absolute shrinkage and selection operator logistic regression were utilized to generate a Rad score. A nomogram consisting of the Rad score and clinical factors was then constructed for the training cohort. Both cohorts assessed model performance using discrimination, calibration, and clinical usefulness.ResultsBased on the six most valuable radiomics features, the Rad score was calculated for each patient. A multivariate analysis revealed that a higher Rad score (P < 0.001), younger age (P = 0.006), and presence of capsule invasion (P = 0.030) were independently associated with CLNM. A nomogram integrating these three factors demonstrated good calibration and promising clinical utility in the training and validation cohorts. The nomogram yielded areas under the curve of 0.795 (95% confidence interval [CI], 0.745–0.846) and 0.774 (95% CI, 0.696–0.852) in the training and validation cohorts, respectively.ConclusionsThe radiomics nomogram may be a clinically useful tool for the individual prediction of CLNM in patients with cN0 PTMC.

The effect of central lymph node dissection on the prognosis of cN0 papillary thyroid microcarcinoma: a mid-term follow-up study

BackgroundTo investigate the effect of central lymph node dissection on the prognosis of patients with papillary thyroid microcarcinoma (PTMC) without clinical lymph node metastasis (cN0).MethodsAccording to the inclusion and exclusion criteria, 462 patients with cN0 PTMC underwent surgery in the Second Department of General Surgery, Zhongshan City People’s Hospital from January 1, 2007, to June 31, 2017. They were divided into two groups: the undissection group (262 cases) and the dissection group (170 cases). A comparison was made between the two groups in terms of postoperative complications, recurrences, metastases, etc., as well aslymph node metastasis risk factors in the central region of cN0 PTMC.ResultsThere was no lymphatic leakage or death in all patients after the operation. In the dissection group, 64 cases (37.6%) of central lymph node metastasis were found after the postoperative pathological examination. The undissection group was followed up for (92 ± 28.7) months, and the dissection group was followed up for (86 ± 25.4) months (t=-2.165, P = 0.031). In the two groups, there were no lung metastases, bone metastases, or other distant metastases during the follow-up period. In the undissection group, there were 7 cases, while in the dissection group, there were just 2. Recurrence rates between the two groups did not differ significantly (χ2 = 0.126, P = 0.169); Similarly, disease-free survival curves did not differ significantly (χ2 = 2.565, P = 0.708). Hypoparathyroidism and Hypocalcemia also had no difference between the group. In comparison to the undissection group, the capsular invasion rate (P = 0.026), calcification rate(P < 0.001) incidence of postoperative hoarseness (P = 0.017), and hand and foot numbness rate (P < 0.001) were all considerably greater in the dissection group. Multivariate research revealed that capsular invasion (OR = 9.42, P = 0.002), multifocal (OR = 24.57, P < 0.001), and tumor diameter > 5 mm (OR = 5.46, P = 0.019) were the independent risk factors for central lymph node metastasis in cN0 PTMC.ConclusionsThyroidectomy alone is safe for cN0 PTMC, but longer-term follow-up is still required for changes in central lymph nodes. For cN0 PTMC patients with tumor diameter > 5 mm, multifocal, and capsular invasion, central lymph node metastasis is more likely to occur. Comprehensive evaluation and individualized and precise treatment are essential.

A clinical and molecular pathology prediction model for central lymph node metastasis in cN0 papillary thyroid microcarcinoma.

The frequency of thyroid cancer has rapidly increased in recent years globally. Thus, more papillary thyroid microcarcinoma (PTMC) patients are being diagnosed, including clinical lymph node-negative (cN0) patients. Our study attempted to develop a prediction model for assessing the probability of central lymph node metastasis (CLNM) in cN0 PTMC patients. A total of 595 patients from the Affiliated Hospital of Qingdao University (training cohort: 456 patients) and the Affiliated Hospital of Jining Medical University (verification cohort: 139 patients) who underwent thyroid surgery between January 2020 and May 2022 were enrolled in this study. Their clinical and molecular pathology data were analyzed with multivariate logistic regression to identify independent factors, and then we established a prediction model to assess the risk of CLNM in cN0 PTMC patients. Multivariate logistic regression analysis revealed that sex, Hashimoto's thyroiditis (HT), tumor size, extrathyroidal extension, TERT promoter mutations and NRAS mutation were independent factors of CLNM. The prediction model demonstrated good discrimination ability (C-index: 0.757 and 0.753 in the derivation and validation cohorts, respectively). The calibration curve of the model was near the optimum diagonal line, and decision curve analysis (DCA) showed a noticeably better benefit. CLNM in cN0 PTMC patients is associated with male sex, tumor size, extrathyroidal extension, HT, TERT promoter mutations and NRAS mutation. The prediction model exhibits good discrimination, calibration and clinical usefulness. This model will help to assess CLNM risk and make clinical decisions in cN0 PTMC patients.

Clinical and ultrasonic risk factors for high-volume central lymph node metastasis in cN0 papillary thyroid microcarcinoma: A retrospective study and meta-analysis.

Papillary thyroid microcarcinoma (PTMC) comprises more than 50% of all newly detected cases of papillary thyroid carcinoma (PTC). High-volume lymph node metastasis (involving >5 lymph nodes) (hv-LNM) is associated with PTMC recurrence. In half of the clinically node-negative (cN0) PTMC patients, central lymph node metastasis (CLNM) is pathologically present. However, clinical risk factors for high-volume CLNM (hv-CLNM) in cN0 PTMC have not been defined well. Therefore, we aimed to obtain evidence for hv-CLNM risk factors in cN0 PTMC. Data on patients who visited our hospital between January 2020 and December 2021 were collected; a preoperative diagnosis of cN0 and a postoperative pathological confirmation of PTMC were obtained. After filtering by inclusion versus exclusion criteria, the obtained data (N = 2268) were included in the meta-analysis. Relevant studies published as of 10 April 2022, were identified from the Web of Science, PubMed, WANFANG, and CNKI databases. These eligible studies were included in the meta-analysis and the association between clinicopathological factors and hv-CLNM in cN0 PTMC was assessed. SPSS and MetaXL were used for statistical analyses. The meta-analysis included 10 previous studies (11,734 patients) and 2268 patients enroled in our hospital for a total of 14,002 subjects. The results of which suggested that younger age (<40, odds ratio [OR] = 3.28, 95% confidence interval [CI] = 2.75-3.92, p < .001 or <45 odds ratio [OR] = 2.93, 95%CI = 2.31-3.72, p < .001), male sex (OR = 2.81, 95% CI = 2.25-3.52, p < .001), tumour size >5 mm (OR = 1.85, 95%CI = 1.39-2.47, p < .001), multifocality (OR = 1.88, 95%CI = 1.56-2.26, p < .001), extrathyroidal extension (OR = 2.58, 95%CI = 2.02-3.30, p < .001), capsule invasion (OR = 2.02, 95%CI = 1.46-2.78, p < .001), microcalcification (OR = 3.25, 95%CI = 2.42-4.36, p < .001)and rich blood flow (OR = 1.65, 95%CI = 1.21-2.25, p = .002) were the significant factors related to an elevated hv-CLNM risk in cN0 PTMC patients. Hashimoto thyroiditis (OR = 0.76, 95%CI = 0.55-1.07, p = .114), irregular margin (versus regular margin, OR = 0.96, 95%CI = 0.68-1.33, p = .787)and hypoechoic (versus nonhypoechoic, OR = 1.27, 95%CI = 0.84-1.92, p = .261) showed no significant association with hv-CLNM. Younger age, tumour size >5 mm, males, extrathyroidal extension, multifocality, microcalcification, capsular invasion, and rich blood flow were the significant clinicopathological risk factors for hv-CLNM risk in cN0 PTMC patients. These predictors may compensate for the sensitivity of imaging diagnosis in the preoperative period, thus helping in the effective identification of PTMCs with an invasive phenotype.

Model development to predict central lymph node metastasis in cN0 papillary thyroid microcarcinoma by machine learning.

BackgroundWhether prophylactic central lymph node dissection is necessary for cN0 papillary thyroid microcarcinoma (PTMC) patients remains highly debatable. Surgeons desperately need a way to help with surgical decision-making. While traditional predictive models can better explain changes in variables, machine learning (ML) models may have better predictive performance. This study aims to develop models for predicting the risk of central lymph node metastasis (CLNM) by utilizing ML algorithms.MethodsThe clinical records of 1,121 patients with cN0 PTMC who underwent initial thyroid resection at our hospital between January 2014 and December 2018 were retrospectively retrieved. Univariate and multivariate analyses were performed to examine risk factors associated with CLNM. Six ML algorithms for predicting CLNM were established and internally validated. Indices including the area under the receiver operating characteristic (AUROC), sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were calculated to test the performance of the model.ResultsThe results showed 33.5% (376 out of 1,121) of patients had CLNM. In multivariate logistic regression (LR) analyses, gender, age, tumor size, multifocal lesions, and extrathyroidal extension (ETE) were all independent predictors of CLNM. The AUROC predictive values of the six ML algorithms were between 0.664 and 0.794, with the random forest (RF) model performing the best with an AUROC of 0.794. Therefore, we used the RF model and uploaded the results to a web-based risk calculator to predict an individual’s probability of CLNM (https://xijing-thyroid.shinyapps.io/ptmc_clnm).ConclusionsDeveloping predictive models of CLNM in cN0 PTMC patients using the ML algorithm is a feasible method. Our online risk calculator based on the RF model may be a useful tool for surgical decisions.

Development of an Active Surveillance or Surgery Model to Predict Lymph Node Metastasis in cN0 Papillary Thyroid Microcarcinoma

ObjectiveInvolvement of multiple lymph node (LN) metastasis in papillary thyroid microcarcinoma (PTMC) may indicate a progressive disease. To assist treatment decision, we conducted a clinical study to develop and validate a prediction model for the preoperative evaluation of LN metastasis involving more than five lymph nodes in patients with clinical N0 (cN0) PTMC.Material and MethodsUsing data from 6,337 patients with cN0 PTMCs at Tianjin Medical University Cancer Institute and Hospital from 2013 to 2017, we identified and integrated risk factors for the prediction of multiple LN metastasis to build a nomogram. The predictive accuracy and discriminative ability of the nomogram were evaluated by the concordance index (C-index) and calibration curve. The model was validated using bootstrap resampling of the training cohort and an independent temporal validation cohort at the same institution.ResultsIn the training cohort (n = 3,209 patients), six independent risk factors were identified and included the prediction model (PTMC Active Surveillance or Surgery (ASOS) Model), including age, gender, multifocality, tumor size, calcification, and aspect ratio. The PTMC ASOS model was validated both internally and through the temporal validation cohort (n = 3,128 patients) from the same institute. The C-indexes of the prediction model in the training cohort were 0.768 (95% CI, 0.698–0.838), 0.768 and 0.771 in the internal validation and external validation cohorts, respectively. The area under the receiver operating characteristic curve (AUC) was 0.7068 and 0.6799. The calibration curve for probability of large-LN metastasis showed good agreement between prediction by nomogram and actual observation. DCA curves were used for comparison with another model, and IDI and NRI were also calculated. The cutoff value of our model was obtained by the ROC curve. Based on this model and cut point, a web-based dynamic nomogram was developed (https://tjmuch-thyroid.shinyapps.io/PTMCASOSM/).ConclusionWe established a novel nomogram that can help to distinguish preoperatively cN0 PTMC patients with or without metastasis of multiple lymph nodes. This clinical prediction model may be used in decision making for both active surveillance and surgery.

Clinicopathologic predictors of central lymph node metastases in clinical node-negative papillary thyroid microcarcinoma: a systematic review and meta-analysis

BackgroundThe presence of central lymph node metastases (CLNM) has been suggested as a risk factor for poorer prognosis and recurrence in papillary thyroid microcarcinoma (PTMC). However, the clinicopathologic factors for CLNM in clinical node-negative (CN0) PTMC were not well defined. This study aimed to perform a systematic review and meta-analysis to investigate the significant clinicopathologic predictors of CLNM in CN0 PTMC.MethodsA systematic literature search was performed in PubMed, Embase, Cochrane Library, and Web of Science. Case-control studies on the association of clinicopathologic risk factors with CLNM in CN0 PTMC were included.ResultsThirteen eligible studies involving 6068 patients with CN0 PTMC were included. From the pooled analyses, male (odds ratio [OR]: 2.07, 95% CI: 1.49–2.87, P < 0.001), multifocality (OR: 1.88, 95% CI: 1.54–2.29, P < 0.001), tumor size > 5 mm (OR: 1.84, 95% CI: 1.55–2.18, P < 0.001), and extrathyroidal extension (OR: 1.96, 95% CI: 1.30–2.95, P = 0.001) are significantly associated with increased risk of CLNM in CN0 PTMC. A sample size with a cutoff point of 200 was identified as the source of heterogeneity for sex according to meta-regression (t = 3.18, P = 0.033). Then, the subgroup analysis of male was performed, which illustrated that male increased the risk of CLNM in the small sample group (SG) and the large sample group (LG) by 6.11-folds and 2.01-folds, respectively (SG: OR, 6.11, 95% CI, 3.16–11.81, P < 0.001; LG: OR, 2.01, 95% CI, 1.65–2.46, P < 0.001).ConclusionsMale, multifocality, tumor size > 5 mm, and extrathyroidal extension may be reliable clinical predictors of CLNM in CN0 PTMC. Moreover, prophylactic central lymph node dissection should be considered in surgical decision-making for CN0 PTMC patients, who are male, multifocal, with tumor size > 5 mm, and with extrathyroidal extension.Trial registrationCRD42021242211 (PROSPERO)

A Nomogram Based on Clinicopathological and Ultrasound Imaging Characteristics for Predicting Cervical Lymph Node Metastasis in cN0 Unilateral Papillary Thyroid Microcarcinoma.

Objective: The aim of this study was to establish a practical nomogram for preoperatively predicting the possibility of cervical lymph node metastasis (CLNM) based on clinicopathological and ultrasound (US) imaging characteristics in patients with clinically node-negative (cN0) unilateral papillary thyroid microcarcinoma (PTMC) in order to determine a personal surgical volume and therapeutic strategy.Methods: A total of 269 consecutive patients diagnosed with cN0 unilateral PTMC by postoperative pathological examination from January 2018 to December 2020 were retrospectively analyzed. All the patients underwent lobectomy or thyroidectomy with routine prophylactic central lymph node dissection (CLND) and were divided into a CLNM group and a non-CLNM group. Using logistic regression, the least absolute shrinkage and selection operator (LASSO) regression analysis was applied to determine the risk factors for CLNM in patients with unilateral cN0 PTMC. A nomogram including risk-factor screening using LASSO regression for predicting the CLNM in patients with cN0 unilateral PTMC was further developed and validated.Results: Risk factors identified by LASSO regression, including age, sex, tumor size, presence of extrathyroidal extension (ETE), tumor diameter/lobe thickness (D/T), tumor location, and coexistent benign lesions, were potential predictors for CLNM in patients with cN0 unilateral PTMC. Meanwhile, age (odds ratio [OR] = 0.261, 95% CI.104–0.605; P = 0.003), sex (men: OR = 3.866; 95% CI 1.758–8.880; P < 0.001), ETE (OR = 3.821; 95% CI 1.168–13.861; P = 0.032), D/T (OR = 72.411; 95% CI 5.483–1212.497; P < 0.001), and coexistent benign lesions (OR = 3.112 95% CI 1.407–7.303; P = 0.007) were shown to be significantly related to CLNM by multivariant logistic regression. A nomogram for predicting CLNM in patients with cN0 unilateral PTMC was established based on the risk factors identified by the LASSO regression analysis. The receiver operating characteristic (ROC) curve for predicting CLNM by nomogram showed that the area under the curve (AUC) was 0.777 and exhibited an excellent consistency.Conclusions: A nomogram based on clinical and US imaging characteristics for predicting the probability of CLNM in patients with cN0 unilateral PTMC was developed, which showed a favorable predictive value and consistency. Further prospective research to observe the oncological outcomes is necessary to determine whether the nomogram could potentially guide a personalized surgical volume and surgical approach.

Effect of Prophylactic Central Lymph Node Dissection on Locoregional Recurrence in Patients with Papillary Thyroid Microcarcinoma.

There is a consensus that central compartment lymph node dissection or modified radical lateral neck dissection should be performed in papillary thyroid microcarcinoma (PTMC) patients with lymph node metastases. Prophylactic central lymph node dissection (PCLND) in patients with clinically node-negative (cN0) PTMC to reduce locoregional recurrence (LRR) rate and improve prognosis remains controversial. The present study aimed to analyze the effect of PCLND on LRR and postoperative complications of PTMC in cN0 patients. We reviewed a cohort of patients with cN0 PTMC who underwent surgery between January 1997 and October 2019. The patients were divided into the PCLND and no lymph node dissection (NLND) groups. Kaplan–Meier curves were constructed to estimate 15-year locoregional recurrence-free survival rate of the two groups, and the difference was compared by the log-rank test. Three Cox regression models were performed to evaluate the correlation between PCLND and LRR. All patients underwent thyroidectomy, and 25 patients developed LRR; of whom, 23 underwent PCLND at initial surgery and 2 went without lymph node dissection. Cox regression analysis showed that PCLND had no effect on LRR. Postoperative hematoma and permanent recurrent laryngeal nerve injury did not occur in the NLND group, and their incidences were 0.5% and 0.3% in the PCLND group, respectively. PCLND had no significant correlation with LRR in patients with cN0 PTMC, and the absolute benefit for PTMC was small.

Analysis of the risk factors for central lymph-node metastasis of cN0 papillary thyroid microcarcinoma: A retrospective study

Cervical lymph node (CLN) metastasis (CLNM) can be found in some patients with CLN-negative (cN0) papillary thyroid microcarcinoma (PTMC), while the risk factors are still unknown. This study aimed to examine the risk factors of CLNM in patients with cN0 PTMC, contributing to screening cN0 PTMC patients with high risk in CLNM for preventive CLN dissection (CLND). This retrospective study included consecutive patients pathologically diagnosed with cN0 PTMC and who underwent surgery at the General Surgery Department of China-Japan Friendship Hospital between 07/2016 and 01/2020. The patients were grouped according to whether CLNM was present. Factors associated with CLNM were analyzed, and a risk prediction model was established in logistic regression analysis, and their predictive power was evaluated by receiver operating characteristic curves (ROC). Finally, 171 patients were included; among them, 71 (41.5%) had CLNM. There were 32 males and 139 females. The multivariable analysis showed that males (OR=5.619, 95%CI: 2.186-14.446; P<0.001), age ≤45 years (OR=2.982, 95%CI: 1.446-6.151; P=0.003), adjacent to dorsal membrane (OR=3.022, 95%CI: 1.430-6.387; P=0.004), and irregular borders (OR=4.332, 95%CI: 1.104-17.000; P=0.036) were independent risk factors of CLNM. The risk prediction model composed of the four risk factors showed a relatively high AUC, at 0.760. When the cut-off was 0.38, the sensitivity was 67.6%, and the specificity was 73.0%. Male sex, age ≤45 years, adjacent to dorsal membranes, and irregular borders are independent risk factors for CLNM in patients with cN0 PTMC. This might help identify cN0 PTMC patients needing preventive CLND.

Correlation analysis of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio and central cervical lymph node metastasis of papillary thyroid microcarcinoma

Objective: To investigate the correlation between neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and central lymph node metastasis (CLNM) in patients with cN0 papillary thyroid microcarcinoma (PTMC). Methods: The clinicopathological data of PTMC patients confirmed by surgery and pathology in the 81st Military Hospital of People's Liberation Army from 2016 to 2019 were collected, and the relationship between preoperative NLR, PLR levels and postoperative PTMC CLNM were analyzed. Logistic regression analysis was used for multivariate analysis. Receiver operating characteristic (ROC) curve was used to determine the cutoff value of NLR and PLR. The interaction relative excess risk was used to analyze the relationship between NLR, PLR and CLNM. Results: Among 220 patients with cN0 stage PTMC, 92 were CLNM. The ROC curve showed that when the cutoff value of NLR was 2.5 and the cutoff value of PLR was 175, the highest Youden index was 0.318 and 0.264, respectively. NLR and PLR were both related to CLNM (P<0.05). The tumor long diameter, multifocality, NLR≥2.5 and PLR≥175 were independent impact factors of CLNM (P<0.05). The results of the interaction showed that the relative excess risk of the interaction was 5.531 (95%CI: 0.160, 10.901, P=0.016), the attribution ratio was 0.512 (95%CI: 0.230, 0.794, P=0.009), and the synergy index was 2.294 (95%CI: 1.492, 4.579, P=0.022), suggested that NLR and PLR had an interactive effect, and these two synergistically promoted CLNM. Conclusions: NLR and PLR are independent risk factors for cN0 stage PTMC CLNM. When NLR≥2.5 and PLR≥175, preventive central lymph node dissection should be routinely performed.

Predictive Factor of Large-Volume Central Lymph Node Metastasis in Clinical N0 Papillary Thyroid Carcinoma Patients Underwent Total Thyroidectomy.

Large‐volume central lymph node metastasis (large-volume CLNM) is associated with high recurrence rate in papillary thyroid carcinoma (PTC) patients. However, sensitivity in investigating large-volume CLNM on preoperative ultrasonography (US) is not high. The aim of this study is to investigate the clinical factors associated with large-volume CLNM in clinical N0 PTC patients. We reviewed 976 PTC patients undergoing total thyroidectomy with central lymph node dissection during 2017 to 2019. The rate of large-volume LNM was 4.1% (40 of 967 patients). Multivariate analysis showed that male gender and young age (age<45 years old) were independent risk factors for large-volume CLNM with odds ratios [(OR), 95% confidence interval (CI)] of 2.034 (1.015-4.073) and 2.997 (1.306–6.876), respectively. In papillary thyroid microcarcinoma (PTMC), capsule invasion was associated with large-volume CLNM with OR (95% CI) of 2.845 (1.110–7.288). In conventional papillary thyroid cancer (CPTC), tumor diameter (>2cm) was associated with large-volume CLNM, with OR (95% CI) 3.757 (1.061–13.310), by multivariate analysis. In ROC curve analysis on the diameter of the CPTC tumor, the Area Under Curve (AUC) =0.682(p=0.013), the best cut-off point was selected as 2.0cm. In conclusion, male gender and young age were predictors for large-volume CLNM of cN0 PTC. cN0 PTMC patient with capsule invasion and cN0 CPTC patient with tumor diameter >2cm were correlated with large-volume CLNM. Total thyroidectomy with central lymph node dissection may be a favorable primary treatment option for those patients.

Preoperative risk factors and recommendations for surgical intervention in cN0 papillary thyroid microcarcinoma.

The evaluation and management of papillary thyroid microcarcinoma (PTMC) have always been challenging and controversial. Our retrospective study aimed to investigate the metastatic trend and risk factors of cN0 papillary thyroid microcarcinoma patients and provide advice for surgical strategies. The clinicopathological features of 556 cN0 PTMC patients undergoing thyroidectomy combined with central compartment dissection (CCD) were compared by the χ2 test and risk factors were identified by binary logistic regression analysis. Numbers of dissected lymph nodes (DLN) and metastatic lymph nodes (MLN) were analyzed using the Mann-Whitney U test to compare metastatic trends between different lobes. Male gender, tumor maximum diameter (TMD) larger than 5 mm, multifocality, and capsular/extracapsular invasion were metastatic risk factors of central compartment metastasis (CCM) (p<0.05). The number of DLN in the right level VI was larger than in the left (p<0.05), while the number of MLN was similar (p>0.05). The chance of CCM was higher when the number of DLN was larger than 5 (p<0.05). After identified metastatic trends and risk factors, we recommend surgery for patients deciding on aggressive treatment, especially for cases where a combination of risk factors is present. And to ensure no residual metastatic lymph nodes and reduce secondary surgery rates, adequate lymphadenectomy on the diseased side would be a better choice considering the standard of care.

Predicting non-small-volume central lymph node metastases (>5 or ≥2 mm) preoperatively in cN0 papillary thyroid microcarcinoma without extrathyroidal extension.

The ability to identify patients with aggressive papillary thyroid microcarcinoma (PTMC) from the low-risk patients is critical to planning proper management of PTMC. Lymph node metastases showed association with recurrence and low survival rate, especially in patients with >5 or ≥2 mm metastatic lymph nodes. Therefore, this study aimed to investigate the preoperatively predictive factors of non-small-volume (metastatic lymph nodes >5 or ≥2 mm in size) central lymph node metastases (NSVCLNM) in PTMC patients. A total of 420 patients with clinically node-negative (cN0) PTMC without extrathyroidal extension underwent thyroidectomy plus central neck dissection (CND) between January 2013 and December 2015, were retrospectively analyzed. Of the 420 patients, 33 (7.9%) had NSVCLNM. The 5-year recurrence-free survival was significantly less in cN0 PTMC patients with NSVCLNM, when compared with patients without NSVCLNM (80.8% vs 100%, P < .001). Multivariate logistic regression revealed age ≤36 years (P < .001), male sex (P = .002), ultrasonic tumor sizes of >0.65 cm (P < .001), and ultrasonic multifocality (P = .039) were independent predictive factors of NSVCLNM. A prediction equation (Y = 1.714 × age + 1.361 × sex + 1.639 × tumor size + 0.842 × multifocality −5.196) was developed, with a sensitivity (69.7%) and a specificity (84.0%), respectively, at an optimal cutoff point of −2.418. In conclusion, if the predictive value was >−2.418 according to the equation, immediate surgery including CND rather than active surveillance might be considered for cN0 PTMC patients.