Construction of a nomogram for central lymph node metastasis in papillary thyroid cancer based on gender grouping.

BACKGROUND: The status of central lymph nodes is crucial for determining the surgical approach to papillary thyroid carcinoma (PTC). Because of the differences between genders in central lymph node metastasis (CLNM), we aimed to construct separate predictive models for CLNM according to gender. METHODS: In our study, a total of 1258 PTC patients who underwent thyroid cancer surgery from September 2021 to March 2023 were analyzed retrospectively. The data were analysed univariately and multivariately using SPSS software grouped according to gender and nomograms of CLNM were plotted using R software. The variables included in this study were sex, Age, body mass index, Diabetes, chronic lymphocytic thyroiditis (CLT), Suspicious central lymph node (SCLN), A/T, Margin, Microcalcification (MC), BRAF, Number, Location, CLNM. RESULTS: The preoperative nomogram in male patients included four clinical variables: CLT, Margin, Number, Size. The preoperative nomogram of female patients included six clinical variables: Age, SCLN, Margin, MC, Number, Size. The calibration curves showed great agreement in both the training group and the validation group. The decision curve analysis showed the feasibility of nomogram in predicting CLNM in both man and woman. CONCLUSION: Based on the successful establishment of nomogram, we can analyze the variability of CLNM between male and female, which may provide clinicians with personalized clinical schemes in the treatment of PTC.

Construction of prediction models for determining the risk of lateral lymph node metastasis in patients with thyroid papillary carcinoma based on gender stratification.

BACKGROUND: Lateral lymph node metastasis (LLNM) is associated with poor prognosis in patients with papillary thyroid cancer (PTC). The purpose of this study was to determine the risk factors for LLNM and establish prediction models that could individually assessed the risk of LLNM. METHODS: A total of 619 PTC patients were retrospectively analyzed in our study. Univariate and multivariate analysis were performed for male and female patients, respectively, to assess relationships between clinicopathological features and LLNM. By integrating independent predictors selected by binary logistic regression modeling, preoperative and postoperative nomograms were developed to estimate the risk of LLNM. RESULTS: LLNM was detected in 80 of 216 male patients. Of 403 female patients, 114 had LLNM. The preoperative nomogram of male patients included three clinical variables: the number of foci, tuner size, and echogenic foci. In addition to the above three variables, the postoperative nomogram of male patients included extrathyroidal extension (ETE) detected in surgery, central lymph node metastasis (CLNM) and high-volume CLNM. The preoperative nomogram of female patients included the following variables: age, chronic lymphocytic thyroiditis (CLT), BRAF V600E, the number of foci, tumor size and echogenic foci. Variables such as CLT, BRAF V600E, the number of foci, tumor size, ETE detected in surgery, CLNM, high-volume CLNM and central lymph node ratio were included in the postoperative nomogram. Above Nomograms show good discrimination. CONCLUSIONS: Considering the difference in the incidence rate of LLNM between men and women, a separate prediction system should be established for patients of different genders. These nomograms are helpful in promoting the risk stratification of PTC treatment decision-making and postoperative management.

Prediction model of lymph node metastasis posterior to the right recurrent laryngeal nerve.

BACKGROUND: At present, it is still controversial whether lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLN) in papillary thyroid carcinoma (PTC) patients should be dissected. Failure to dissect metastatic lymph nodes results in continued metastasis from the positive lymph nodes to other regions. Our study aimed to establish a predictive model and predict the probability of metastasis of the lymph nodes posterior to the right recurrent laryngeal nerve (LNM-prRLN) in patients. METHODS: A total of 309 patients underwent surgery for thyroid cancer between May 2019 and September 2022. The risk factors were identified by univariate and multivariate analyses, and statistically significant risk factors identified in the multivariate analysis were included in the nomogram. We used the calibration curve and the receiver operating characteristic (ROC) curve to verify the accuracy of the prediction model. RESULTS: Multivariate analysis showed that irregular tumor margins (OR: 3.549, 95% CI 1.294-9.733, P = 0.014), extrathyroidal extension (OR: 4.507, 95% CI 1.694-11.993, P = 0.003), maximum tumor diameter > 1 cm (OR: 5.729, 95% CI 2.617-12.542, P < 0.001), overweight status (OR: 2.296, 95% CI 1.057-4.987, P = 0.036), high total cholesterol level (OR: 5.238, 95% CI 2.304-11.909, P < 0.001), and multifocality (OR: 11.954, 95% CI 5.233-27.305, P < 0.001) were independent risk factors for LNM-prRLN. The area under the ROC curve was 0.927. The calibration curve showed good agreement between the predicted and observed rates of LNM-prRLN. CONCLUSION: The probability of LNM-prRLN could be predicted by a nomogram based on the statistically significant risk factors identified in the multivariate analysis. This nomogram can guide clinicians when preoperatively evaluating the status of the LN-prRLN with regard to LNM-prRLN in PTC patients. For patients at high risk for LNM-prRLN, the preventive dissection of LN-prRLNs can be considered.

Identification of ENTPD8 and cytidine in pancreatic cancer by metabolomic and transcriptomic conjoint analysis.

To identify metabolic pathways that were perturbed in pancreatic cancer (PC), we investigated gene-metabolite networks by integration of metabolomic and transcriptomic. In this research, we undertook the metabolomic study of 43 paired human PC samples, aiming to identify key metabolic alterations in PC. We also carried out in vitro experiments to validate that the key metabolite cytidine and its related gene ENTPD8 played an important role in PC cell proliferation. We screened out 13 metabolites differentially expressed in PC tissue (PCT) by liquid chromatography/mass spectrometry analysis on 34 metabolites, and the partial least square discrimination analysis results revealed that 9 metabolites among them were remarkably altered in PCT compared to adjacent noncancerous tissue (variable importance in projection >1, P < .05). Among the 9 metabolites, 7 might be potential biomarkers. The most significantly enriched metabolic pathway was pyrimidine metabolism. We analyzed 351 differentially expressed genes from The Cancer Genome Atlas and intersected them with Kyoto Encyclopedia of Genes and Genomes metabolic pathways. We found that ENTPD8 had a gene-metabolite association with cytidine in the CTP dephosphorylation pathway. We verified by in vitro experiments that the CTP dephosphorylation pathway was changed in PCT compared with adjacent noncancerous tissue. ENTPD8 was downregulated in PCT, causing a reduction in cytidine formation and hence weakened CTP dephosphorylation in pyrimidine metabolism.

circZMYM2 Competed Endogenously with miR-335-5p to Regulate JMJD2C in Pancreatic Cancer.

BACKGROUND/AIMS: We aimed to study the involvement of circZMYM2 (hsa_circ_0099999) in pancreatic cancer (PC) cell proliferation, apoptosis and invasion and to figured out the underlying mechanism of circZMYM2 regulating miR-335-5p and JMJD2C. METHODS: CircRNA differential expressions in twenty PC samples and paired normal tissue samples were analyzed using Arraystar Human CircRNA microarray V1. CircZMYM2 expression level was determined via qRT-PCR. The effects of circZMYM2 inhibition and overexpression on cell proliferation, cell apoptosis and cell invasion were investigated by CCK-8 assays, Flow cytometry assays and Transwell assays. An animal experiment on nude mice was put forward to test the influence of circZMYM2 knockdown on tumor growth. The relationship between circZMYM2, miR-335 and JMJD2C was verified by RNA pull down, dual-luciferase reporter assays and rescue experiment. The effect of circZMYM2 and miR-335-5p on the expression of JMJD2C protein was detected by western blot. RESULTS: CircZMYM2 overexpression was observed in both PC tissues and cells. Knockdown of circZMYM2 inhibited proliferation, induced apoptosis, and weakened invasion ability of cancer cells. Tumor growth was restrained in vivo. CircZMYM2 repressed the expression of its target miR-335-5p. MiR-335-5p attenuated pancreatic cancer development via inhibition of JMJD2C. CONCLUSION: Our study demonstrated that circZMYM2 promoted PC progression. CircZMYM2 had a sponge effect on miR-335-5p and modulated the downstream oncogene JMJD2C.

Dynamics analysis of building block synthesis reactions for virus assembly in vitro.

Virus assembly from structural protein monomers to virus shells is a key step of virus replication. Some drug targets were found in this process. It consists of two steps. Virus structural protein monomers firstly polymerize to building blocks, then these building blocks assemble into virus shells. So, these building block synthesis reactions in the first step are fundamental for virus assembly. Typically, virus building blocks are made up of less than six monomers. They are of five types, including dimer, trimer, tetramer, pentamer and hexamer. In this work, we develop five synthesis reaction dynamical models for these five types, respectively. Then, we prove the existence and uniqueness of the positive equilibrium solution for these dynamical models one by one. Subsequently, we also analyze the stability of the equilibrium states, respectively. We got the function of monomer and dimer concentrations for dimer building blocks in the equilibrium state. We also got the function of all intermediate polymers and monomers for trimer, tetramer, pentamer and hexamer building blocks in the equilibrium state, respectively. Based on our analysis, dimer building blocks in the equilibrium state will decrease as the ratio of the off-rate constant to the on-rate constant increases. Trimer building blocks in the equilibrium state will decrease with the increasing ratio of the off-rate constant to the on-rate constant of trimers. These results may provide further insight into the virus-building block synthesis dynamic property in vitro.

A fluorescent controllable supramolecular crosslinked polymer constructed by complementary metal coordination interaction.

In this work, two different monomers M1 and M2 were designed and synthesized. M1 + M2 + Zn(OTf)2 could self-assemble to form a supramolecular crosslinked polymer (SCP) based on complementary terpyridine-based metal coordination interaction. The self-assembly of M1 + M2 + Zn(OTf)2 was studied by various techniques, such as 1H NMR, 2D COSY NMR, 2D NOESY NMR, UV-Vis analysis, fluorescence analysis, viscosity measurement, and TEM. The experimental result indicated that the molecular weight of the SCP depended on the initial monomer concentration. The SCP could further turn into supramolecular polymer gel at high concentrations, and the reversible gel-sol transformation could be realized by heating/cooling. Moreover, the fluorescence quenching/enhancement of the SCP could be adjusted by adding base/acid.

Nomograms for Prediction of High-Volume Lymph Node Metastasis in Papillary Thyroid Carcinoma Patients.

OBJECTIVE: The coexistence rate between chronic lymphocytic thyroiditis (CLT) and papillary thyroid carcinoma (PTC) is quite high. Whether CLT influences metastatic lymph nodes remains uncertain. High-volume lymph node metastasis is recommended as an unfavorable pathological feature. We aimed to investigate risk factors for high-volume central lymph node metastasis (CLNM) and lateral lymph node metastasis (LLNM) in PTC patients. STUDY DESIGN: Retrospective cohort study. SETTING: Changzhou First People's Hospital. METHODS: Clinicopathological characteristics of 1094 PTC patients who underwent surgery in our center from January 2019 to November 2021 were analyzed. RESULTS: The number of metastatic lymph nodes in the central compartment and lateral compartment were lower in the CLT group. We demonstrated that age, BRAF V600E, shape, and the number of foci were risk factors for high-volume CLNM in patients with CLT. For patients without CLT, sex, age, tumor size, number of foci, and margin were risk factors for high-volume CLNM. Tumor size, number of foci, location, and CLNM were all risk factors for high-volume LLNM in patients with or without CLT. Body mass index was only associated with high-volume LLNM in CLT patients. All the above factors were incorporated into nomograms, which showed perfect discriminative ability. CONCLUSION: Separate predictive systems should be used for CLT and non-CLT patients for a more accurate clinical assessment of lymph node status. Our nomograms of predicting high-volume CLNM and LLNM could facilitate risk-stratified management of PTC recurrence and treatment decisions.

Triggering photo fermentative biohydrogen production through NiFe2O4 photo nanocatalysts with various excitation sources.

The triggering effects of nickel ferrite (NiFe2O4) photo nanocatalysts on photo fermentative hydrogen production (PFHP), and metabolic pathways under various excitation sources (incandescent lamp, Xenon lamp, and 532 laser) have been investigated. Compare to the control group (CG) highest cumulative hydrogen volume (CHV) and the maximum hydrogen production rate (HPR) of 568.8 mL and 9.17 mL/h, respectively were achieved at a loading centration of 150 mg/L excited with an incandescent lamp. The change in metabolites with NiFe2O4 incorporation suggests that bacterial activity is significantly affected by photo nanocatalysts. Triggering of NiFe2O4 by laser excitation showed the highest HPR of 7.83 mL /h within 24 h, which greatly reduces the lag time. The microbial community investigation showed that the addition of NiFe2O4 photo nanocatalysts and the change of light source effectively improved the microbial community structure and increased the abundance of hydrogen-producing bacteria (HPB) which leads to enhanced hydrogen production.

Multistep sequence-controlled supramolecular polymerization by the combination of multiple self-assembly motifs.

The precise sequence control of polymer chain is an important research topic of polymer chemistry. Although some methods such as iterative synthesis and supramolecular polymerization have been developed to fabricate sequence-controllable polymer, it is still a great challenge to consecutively prepare multiple supramolecular polymers with different sequence structures. In this work, through the reasonable utilization of assembly motifs, we integrated multiple host-guest recognitions and metal coordination interactions to prepare different sequence-controlled supramolecular polymers by a multistep assembly strategy. This research provides inspiration for the design and preparation of supramolecular polymers with different sequence structures.

Depolymerization of lignin: Recent progress towards value-added chemicals and biohydrogen production.

The need for alternative sources of energy became increasingly urgent as demand for energy and the use of fossil fuels both soared. When processed into aromatic compounds, lignin can be utilized as an alternative to fossil fuels, however, lignin's complex structure and recalcitrance make depolymerization impractical. This article presented an overview of the most recent advances in lignin conversion, including process technology, catalyst advancement, and case study-based end products. In addition to the three established methods (thermochemical, biochemical, and catalytic depolymerization), a lignin-first strategy was presented. Depolymerizing different forms of lignin into smaller phenolic molecules has been suggested using homogeneous and heterogeneous catalysts for oxidation or reduction. Limitations and future prospects of lignin depolymerization have been discussed which suggests that solar-driven catalytic depolymerization through photocatalysts including quantum dots offers a unique pathway to obtain the highly catalytic conversion of lignin.

Nomograms for the prediction of lateral lymph node metastasis in papillary thyroid carcinoma: Stratification by size.

Background: Lateral lymph node metastasis (LLNM) is a risk factor of poor prognosis in papillary thyroid cancer (PTC). We aimed to determine predictive factors and develop the nomograms for LLNM in patients with papillary thyroid microcarcinoma (PTMC) and macro-PTC. Methods: We reviewed the medical records of 1,106 patients who underwent surgery between January 2019 and January 2022. Patients were divided into a PTMC and a macro-PTC group. We developed preoperative and postoperative nomograms for predicting LLNM based on results of multivariate analysis. Internal calibration was performed for these models. Results: The number of metastatic lymph nodes in lateral compartment was higher in macro-PTC patients. LLNM was independently associated with gender, the number of foci, location, shape, and central lymph node metastasis (CLNM) in PTMC patients. For macro-PTC patients, chronic lymphocytic thyroiditis, the number of foci, location, margin, CLNM, and central lymph node ratio were all independent predictors for LLNM. All the above factors were incorporated into nomograms, which showed the perfect discriminative ability. Conclusion: The diameter of the tumor has an impact on the rate of LLNM. Separate predictive systems should be used for PTMC and macro-PTC patients for more accurate clinical assessment of lateral lymph node status. Through these nomograms, we can not only detect high-risk patients with occult LLNM preoperatively, but also form appropriate treatment protocols for postoperative management of PTC patients with different risks.

Insight into derivative Weibull mixture model in describing simulated distributed activation energy model and distillers dried grains with solubles pyrolysis processes.

The kinetics of biomass pyrolysis is fundamental for exploring its mechanisms and optimizing its processes, which is helpful for designing its systems. The derivative Weibull mixture model was proposed for kinetic description of the simulated distribution energy model (DAEM) processes and distillers dried grains with solubles (DDGS) pyrolysis processes. The conversion rate data of these processes at different heating rates could be accurately described by the derivative Weibull mixture model. Moreover, the proposed model could effectively smooth the noises contained in the experimental conversion rate data of DDGS pyrolysis. The derivative Weibull mixture model separated DDGS pyrolysis reactions into several individual processes, and provided some data required for further isoconversional kinetic analysis. The predicted curves from the derivative Weibull mixture model allowed us to obtain the effective activation energies of DDGS pyrolysis, which varied significantly from 170 to 330 kJ mol-1 in the conversion range between 0.1 and 0.9.

A comparative analysis of eight machine learning models for the prediction of lateral lymph node metastasis in patients with papillary thyroid carcinoma.

Background: Lateral lymph node metastasis (LLNM) is a contributor for poor prognosis in papillary thyroid cancer (PTC). We aimed to develop and validate machine learning (ML) algorithms-based models for predicting the risk of LLNM in these patients. Methods: This is retrospective study comprising 1236 patients who underwent initial thyroid resection at our institution between January 2019 and March 2022. All patients were randomly split into the training dataset (70%) and the validation dataset (30%). Eight ML algorithms, including the Logistic Regression, Gradient Boosting Machine, Extreme Gradient Boosting, Random Forest (RF), Decision Tree, Neural Network, Support Vector Machine and Bayesian Network were used to evaluate the risk of LLNM. The performance of ML models was evaluated by the area under curve (AUC), sensitivity, specificity, and decision curve analysis. Results: Among the eight ML algorithms, RF had the highest AUC (0.975), with sensitivity and specificity of 0.903 and 0.959, respectively. It was therefore used to develop as prediction model. The diagnostic performance of RF algorithm was dependent on the following nine top-rank variables: central lymph node ratio, size, central lymph node metastasis, number of foci, location, body mass index, aspect ratio, sex and extrathyroidal extension. Conclusion: By combining clinical and sonographic characteristics, ML algorithms can achieve acceptable prediction of LLNM, of which the RF model performs best. ML algorithms can help clinicians to identify the risk probability of LLNM in PTC patients.

Influence of Obesity Parameters on Different Regional Patterns of Lymph Node Metastasis in Papillary Thyroid Cancer.

Objective: Obesity increases risk of thyroid cancer. However, the association between obesity and the progression of papillary thyroid cancer (PTC) remains controversial. This retrospective study aimed to explore the relationship between obesity and regional patterns of lymph node metastasis (LNM) in PTC. Methods: We retrospectively reviewed data from 1015 patients with PTC. We calculated obese parameters, such as body mass index (BMI), body fat percentage (BFP), and body surface area (BSA). Logistic regression models were used to assess associations between obese parameters and the rate of lymph node metastasis (LNM), number of LNM, pattern of LNM, and lymph node ratio (LNR). Results: Higher BMI was not associated with different regional patterns of LNM in PTC. In men with PTC, high BFP was an independent predictor of total LNM, central lymph node metastasis (CLNM), total lateral lymph node metastasis (LLNM), multiple lateral lymph node metastasis, and simultaneous metastasis in lateral compartment. In addition, male patients with high BFP had higher central LNR and higher number of CLNM. For women, high BSA was an independent predictor of LLNM and level IV metastasis. Female patients with high BSA had higher number of CLNM. Conclusion: BFP and BSA, possibly influenced by gender, were positively associated with the number and risk of LNM in different regions of PTC patients. However, BMI was not the predictor for aggressiveness of PTC in terms of LNM. Clinical decision-making for regional LNM in PTC patients should consider the factor of obesity.

LASSO-based machine learning models for the prediction of central lymph node metastasis in clinically negative patients with papillary thyroid carcinoma.

Background: The presence of central lymph node metastasis (CLNM) is crucial for surgical decision-making in clinical N0 (cN0) papillary thyroid carcinoma (PTC) patients. We aimed to develop and validate machine learning (ML) algorithms-based models for predicting the risk of CLNM in cN0 patients. Methods: A total of 1099 PTC patients with cN0 central neck from July 2019 to March 2022 at our institution were retrospectively analyzed. All patients were randomly split into the training dataset (70%) and the validation dataset (30%). Eight ML algorithms, including the Logistic Regression, Gradient Boosting Machine, Extreme Gradient Boosting (XGB), Random Forest (RF), Decision Tree, Neural Network, Support Vector Machine and Bayesian Network were used to evaluate the risk of CLNM. The performance of ML models was evaluated by the area under curve (AUC), sensitivity, specificity, and decision curve analysis (DCA). Results: We firstly used the LASSO Logistic regression method to select the most relevant factors for predicting CLNM. The AUC of XGB was slightly higher than RF (0.907 and 0.902, respectively). According to DCA, RF model significantly outperformed XGB model at most threshold points and was therefore used to develop the predictive model. The diagnostic performance of RF algorithm was dependent on the following nine top-rank variables: size, margin, extrathyroidal extension, sex, echogenic foci, shape, number, lateral lymph node metastasis and chronic lymphocytic thyroiditis. Conclusion: By incorporating clinicopathological and sonographic characteristics, we developed ML-based models, suggesting that this non-invasive method can be applied to facilitate individualized prediction of occult CLNM in cN0 central neck PTC patients.

Suppression of epidermal growth factor receptor (EGFR) expression by small hairpin RNA inhibits the growth of human nonsmall cell lung cancers bearing wild-type and mutant EGFR.

In the present study, we have used plasmid-based RNA interference (RNAi) strategy to downregulate the expression of epidermal growth factor receptor (EGFR) in EGFR wild-type (H292) and mutant (H1975) lung tumor models. The targeted knockdown of EGFR by small hairpin RNA not only inhibited growth of H292 xenograft but also inhibited H1975 lung cancer cell and xenograft, which bore L858R/T790M EGFR and was resistant to EGFR tyrosine kinase inhibitors. These data demonstrated that small hairpin RNA was an effective therapy against mutant EGFR-expressing cancer cells and thus considered to be a promising strategy in the treatment of lung cancers.

RNA interference-mediated silencing of focal adhesion kinase inhibits growth of human malignant glioma xenograft in nude mice.

FAK (focal adhesion kinase), which plays a pivotal role in mediating cell proliferation, survival and migration, is frequently overexpressed in human malignant glioma. The expression of FAK increases with the advance of tumour grade and stage. Based on these observations, we hypothesized that attenuation of FAK expression may have inhibitory effects on the growth of malignant glioma. In the present study, human glioma cell line U251 was transfected with plasmids containing U6 promoter-driven shRNAs (small-hairpin RNAs) against human FAK using cationic liposome. The effects of FAK knockdown in U251 cells in vitro were analysed by using flow cytometry and PI (propidium iodide)-staining assays. Based on the encouraging in vitro results with FAK silencing, plasmids encoding FAK-targeted shRNA were encapsulated by DOTAP (dioleoyltrimethylammonium propane):Chol (cholesterol) cationic liposome and injected via tail vein to evaluate its therapeutic efficiency on suppressing tumour growth in a human glioma xenograft model. PCNA (proliferating-cell nuclear antigen), CD34 immunostaining and TUNEL (terminal deoxynucleotidyl transferase-mediated dUTP nick-end labelling) assay were used to assess the changes in tumour angiogenesis, apoptosis and proliferation respectively. The results indicated that DOTAP:Chol cationic liposome could deliver therapeutic plasmids systemically to tumour xenografts, resulting in suppression of tumour growth. Treatment with plasmid encoding FAK-targeted shRNA reduced mean tumour volume by approx. 70% compared with control groups (P<0.05), accompanied with angiogenesis inhibition (P<0.05), tumour cell proliferation suppression (P<0.05) and apoptosis induction (P<0.05). Taken together, our results demonstrated that shRNA-mediated silencing of FAK might be a potential therapeutic approach against human malignant glioma.

A Nomogram Based on Clinical and Ultrasound Characteristics to Predict Central Lymph Node Metastasis of Papillary Thyroid Carcinoma.

Background: The status of lymph nodes in the central compartment is crucial to determining the surgical strategies for papillary thyroid carcinoma (PTC). We aimed to develop a nomogram for predicting central lymph node metastasis (CLNM). Methods: A total of 886 PTC patients who underwent total thyroidectomy or lobectomy with central neck dissection (CND) from July 2019 to June 2020 were retrospectively retrieved. Clinical and ultrasound features were collected. Univariate and multivariate analysis were performed to determine risk factors of CLNM. A nomogram for predicting CLNM was developed, internal and external calibration was performed for the established model. Results: Variables (sex, chronic lymphocytic thyroiditis, tumor size, the number of foci, tumor location, margin) significantly associated with CLNM were included in the nomogram. The nomogram showed excellent calibration in the training group and validation group, with area under curves of 0.806 (95% CI, 0.771 to 0.825), and 0.799 (95% CI, 0.778-0.813) respectively. Conclusion: Through this accurate and easy-to-use nomogram, the possibility of CLNM can be objectively quantified preoperatively. Clinicians can use this nomogram to evaluate the status of lymph nodes in PTC patients and consider prophylactic CND for those with high scores.

Nomograms to predict ipsilateral and contralateral central lymph node metastasis in clinically lymph node-negative patients with solitary isthmic classic papillary thyroid carcinoma.

BACKGROUND: Isthmus-originating papillary thyroid carcinoma has unique clinicopathological characteristics. There are no specific guidelines regarding the extent of surgery for isthmic papillary thyroid carcinoma. We aimed to evaluate the characteristics of clinically lymph node-negative patients with solitary isthmic papillary thyroid carcinoma and to determine the best surgical protocol for these patients. METHODS: A total of 904 patients diagnosed with solitary papillary thyroid carcinoma who underwent surgery were retrospectively reviewed. These patients were divided into the isthmic group (246 patients) or lobar group (658 patients). We compared the 2 groups and conducted a multivariate analysis to assess risk factors for ipsilateral and contralateral central lymph node metastasis in isthmic papillary thyroid carcinoma patients. Nomograms for predicting central lymph node metastasis in isthmic papillary thyroid carcinoma patients were developed and internal calibration was performed for these models. RESULTS: Isthmic papillary thyroid carcinoma patients have a significantly higher incidence of extrathyroidal extension and central lymph node metastasis than do lobar papillary thyroid carcinoma patients. For isthmic papillary thyroid carcinoma patients, sex, BRAF V600E mutation, chronic lymphocytic thyroiditis, tumor size, margin, and extrathyroidal extension were independent risk factors of ipsilateral central lymph node metastasis. Body mass index, BRAF V600E mutation, tumor size, location, and extrathyroidal extension were independent risk factors of contralateral central lymph node metastasis. All the above factors were incorporated into nomograms, which showed the perfect discriminative ability. CONCLUSION: Based on the predictive nomograms, we proposed a risk stratification scheme and corresponding individualized surgical treatment based on different nomogram scores. In the debate about prophylactic central neck dissection among clinically lymph node-negative patients with solitary isthmic papillary thyroid carcinoma, our nomograms provide the balance to avoid overtreatment and undertreatment through personal risk assessment.