Papillary Thyroid Carcinoma With Lymphoepithelial Features and Lacking Association With Epstein-Barr Virus (EBV): A Rare Case.

Papillary thyroid carcinoma (PTC) is the most common primary thyroid malignancy. PTC is diagnosed based on its hallmark nuclear characteristics, but a myriad of histological variants has been identified some of which can be diagnostically challenging due to its rarity and overlapping histomorphology with other entities. We report a rare variant of PTC with lymphoepithelial features which lacked association with Epstein-Barr Virus (EBV). In such cases, a thorough workup to rule out metastasis from other sites should be undertaken.

Epidemiological and histopathological characteristics of thyroid carcinoma in a Tunisian health care center.

Background: Thyroid carcinoma (TC) accounts for almost 0.5%-1% of total malignancies. Its incidence is increasing rapidly worldwide. Several studies have drawn up the epidemiological profile of TC and its clinical and pathological features. However, to date, no similar studies have been conducted in Tunisia. Aims: To establish an epidemiological profile of TC in a Tunisian health care institute and to analyze its clinical and histopathological characteristics in our institute. Materials and Methods: We present a retrospective study reviewing the cases of TC diagnosed in our institution in a 4-year period. Results: We collected a sample of 192 cases of TC. It consisted of 31 males and 161 females (83.8%) with a sex-ratio M/F of 0.19. The mean age was 46.4 years. Papillary thyroid carcinoma was the most frequent histological subtype. The multifocality rate was 33.8%. The mean size of TC was 2.2 ± 1.9 cm. 60.9% of TC were staged pT1 and 20.3% had nodal involvement. Papillary thyroid microcarcinomas were noted in 37.5% of cases. Conclusion: Our results were consistent with those of the literature. A high proportion of pT1 and pN0 tumors were noted in our series, suggesting that TC's diagnosis and management was performed at an early stage of the disease in our institution. In addition, our study enabled us to notice the impact of the Coronavirus disease 19 crisis on the management of TC in our institution. Further studies are needed to establish the epidemiological profile of TC in Tunisia and to assess its clinical and pathological features.

Integrated transcriptome sequencing and weighted gene co-expression network analysis reveals key genes of papillary thyroid carcinomas.

Objective: Papillary thyroid carcinoma (PTC) accounts for the majority of thyroid cancers and has a high recurrence rate. We aimed to screen key genes involved in PTC to provide novel insights into the mechanisms of PTC. Methods: Seven microarray datasets of PTC were downloaded from gene expression omnibus database. Differentially expressed genes (DEGs) between PTC and normal samples were screened in the merged dataset. Then, protein-protein interaction (PPIs) functional modules analysis and weighted gene co-expression network analysis (WGCNA) were utilized to identify PTC-associated key genes. The identified key genes were then characterized from various aspects, including gene set enrichment analysis (GSEA) and the associations with immune infiltration, methylation levels and prognosis. Results: A large numbers of DEGs were identified, and these DEGs are involved in several cancer pathways. Nine key genes (including down-regulated genes GNA14, AVPR1A, and WFS1, and up-regulated genes LAMB3, PLAU, MET, MFGE8, PRSS23, and SERPINA1) were identified. Patients in the AVPR1A and GNA14 high expression groups had better disease-free survival (DFS) than those in the low expression group. Key genes were mainly involved in P53 pathway, estrogen response, apoptosis, glycolysis, NOTCH signaling, epithelial mesenchymal transition, WNT_beta catenin signaling, and inflammatory response. The expression of key genes was associated with immune cell infiltration and corresponding methylation levels. The verification results of key gene proteins and mRNA expression levels using external validation datasets were consistent with our expectations, implying the involvements of key genes in PTC. Conclusion: The key genes may serve as potential therapeutic targets for PTC. This study provides novel insights into the mechanisms underlying PTC development.

Clinical features combined with ultrasound characteristics to predict TERT promoter mutations in papillary thyroid carcinoma: a single-center study over the past 5 years.

Purpose: Telomerase reverse transcriptase (TERT) has been reported in papillary thyroid carcinoma (PTC). This study aimed to investigate the correlation of TERT promoter mutations with clinical and ultrasound (US) features in PTC and to develop a model to predict TERT promoter mutations. Methods: Preoperative US images, postoperative pathological features, and TERT promoter mutation information were evaluated in 365 PTC patients confirmed by surgery. Univariate and multivariate factor analyses were performed to identify risk factors for TERT promoter mutations. A predictive model was established to assess the clinical predictive value. Results: Of the 365 patients with PTC (498 nodules), the number of those with TERT promoter mutations was 67 cases (75 nodules), and the number of those without mutations was 298 cases (423 nodules). The median age was 40 years in the wild-type group and 60 years in the mutant group. Male patients made up 35.82% of the mutant group and 22.82% of the wild-type group. Multivariate analysis revealed that the independent risk factors associated with the occurrence of TERT promoter mutation in PTC were as follows: older age (odds ratio (OR) = 1.07; p = 0.002), maximum diameter of ≥ 10 mm (OR = 3.94; p < 0.0001), unilateral (OR = 4.15; p < 0.0001), multifocal (OR = 7.69; p < 0.0001), adjacent to the thyroid capsule (OR = 1.94; p = 0.044), and accompanied by other benign nodules (OR = 1.94, p = 0.039). A predictive model was established, and the area under the curve (AUC) of the receiver operating characteristic was 0.839. TERT promoter mutations were associated with high-risk US and clinical features compared with the wild-type group. Conclusion: TERT promoter mutations were associated with older ages. They were also found to be multifocal, with a maximum diameter of ≥ 10 mm, unilateral, adjacent to the thyroid capsule, and accompanied by other benign nodules. The predictive model was of high diagnostic value.

Predicting central cervical lymph node metastasis in papillary thyroid microcarcinoma using deep learning.

Background: The aim of this study is to design a deep learning (DL) model to preoperatively predict the occurrence of central lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma (PTMC). Methods: This research collected preoperative ultrasound (US) images and clinical factors of 611 PTMC patients. The clinical factors were analyzed using multivariate regression. Then, a DL model based on US images and clinical factors was developed to preoperatively predict CLNM. The model's efficacy was evaluated using the receiver operating characteristic (ROC) curve, along with accuracy, sensitivity, specificity, and the F1 score. Results: The multivariate analysis indicated an independent correlation factors including age ≥55 (OR = 0.309, p < 0.001), tumor diameter (OR = 2.551, p = 0.010), macrocalcifications (OR = 1.832, p = 0.002), and capsular invasion (OR = 1.977, p = 0.005). The suggested DL model utilized US images achieved an average area under the curve (AUC) of 0.65, slightly outperforming the model that employed traditional clinical factors (AUC = 0.64). Nevertheless, the model that incorporated both of them did not enhance prediction accuracy (AUC = 0.63). Conclusions: The suggested approach offers a reference for the treatment and supervision of PTMC. Among three models used in this study, the deep model relied generally more on image modalities than the data modality of clinic records when making the predictions.

Nomogram to predict central lymph node metastasis in papillary thyroid carcinoma.

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.

A prediction model based on random survival forest analysis of the overall survival of elderly female papillary thyroid carcinoma patients: a SEER-based study.

OBJECTIVE: Papillary thyroid carcinoma (PTC) is a common malignancy whose incidence is three times greater in females than in males. The prognosis of ageing patients is poor. This research was designed to construct models to predict the overall survival of elderly female patients with PTC. METHODS: We developed prediction models based on the random survival forest (RSF) algorithm and traditional Cox regression. The data of 4539 patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Twelve variables were analysed to establish the models. The C-index and the Brier score were selected to evaluate the discriminatory ability of the models. Time-dependent receiver operating characteristic (ROC) curves were also drawn to evaluate the accuracy of the models. The clinical benefits of the two models were compared on the basis of the DCA curve. In addition, the Shapley Additive Explanations (SHAP) plot was used to visualize the contribution of the variables in the RSF model. RESULTS: The C-index of the RSF model was 0.811, which was greater than that of the Cox model (0.781). According to the Brier score and the area under the ROC curve (AUC), the RSF model performed better than the Cox model. On the basis of the DCA curve, the RSF model demonstrated fair clinical benefit. The SHAP plot showed that age was the most important variable contributing to the outcome of PTC in elderly female patients. CONCLUSIONS: The RSF model we developed performed better than the Cox model and might be valuable for clinical practice.

Papillae, psammoma bodies, and/or many nuclear pseudoinclusions are helpful criteria but should not be required for a definitive cytologic diagnosis of papillary thyroid carcinoma: An institutional experience of 207 cases with surgical follow up.

BACKGROUND: Noninvasive follicular thyroid neoplasm with papillary-like features (NIFTP) was introduced in 2016 replacing noninvasive follicular variant of papillary thyroid carcinoma, with recommendations to label them "noncancer." To avoid reducing risk of malignancy (ROM) and overdiagnosing NIFTP as malignant, some authors required restricted cytologic criteria (RC) for a definitive diagnosis of papillary thyroid carcinoma (PTC), including papillae, psammoma bodies. or ≥3 nuclear pseudoinclusions. Since then, NIFTP criteria have been revised, biologic behavior better understood, and incidence reported to be much lower than initially anticipated. This study examines the impact of RC on PTC cytologic diagnoses, ROM, and detection of clinically significant carcinomas (CSC). MATERIALS AND METHODS: A total of 207 thyroid FNAs originally diagnosed as PTC and suspicious for PTC (SPTC) with surgical follow-up were evaluated. RC were retrospectively applied to cases as a requirement for diagnosing PTC, and cases that did not meet RC were reclassified as SPTC. ROMs and diagnostic accuracies of pre- and post-RC diagnoses were correlated with followup CSC. RESULTS: RC were met in 118/142 (83%) and 20/65 (31%) of cases originally diagnosed as PTC and SPTC, respectively. Post-RC, 29% (19/65) of CSC originally diagnosed as SPTC were upgraded to PTC, and 17% (24/142) of CSC originally diagnosed as PTC were downgraded to SPTC. No NIFTPs were diagnosed as malignant. CONCLUSIONS: RC should not be required for a definitive diagnosis of PTC when other nuclear features of PTC are diffuse and overt. Applying RC, however, helps the pathologist arrive at a more definitive diagnosis of PTC in suspicious cases.

Papillary Renal Cell Carcinoma: Outcomes for Patients Receiving First-line Immune-based Combinations or Tyrosine Kinase Inhibitors from the ARON-1 Study.

BACKGROUND AND OBJECTIVE: Papillary renal cell carcinoma (pRCC) is the most frequent histological subtype of non-clear cell RCC (nccRCC). Owing to the heterogeneity of nccRCC, patients are often excluded from large phase 3 trials focused on clear cell RCC, so treatment options for nccRCC remain limited. Our aim was to investigate the efficacy of first-line treatment with tyrosine kinase inhibitors (TKIs) or immuno-oncology (IO)-based combinations in patients with pRCC. METHODS: We performed a multicenter retrospective analysis of real-world data collected for patients with advanced pRCC treated in 40 centers in 12 countries as part of the ARON-1 project (NCT05287464). The primary endpoints were overall survival (OS), progression-free survival (PFS), the overall response rate (ORR), and time to second progression (PFS2). OS, PFS, and PFS2 were estimated using the Kaplan-Meier method and results were compared between the treatment groups using a log-rank test. Univariate and multivariable analyses were carried out using Cox proportional-hazard models. KEY FINDINGS AND LIMITATIONS: We included 200 patients with metastatic pRCC, of whom 73 were treated with IO-based combinations and 127 with TKIs. Median OS was 22.5 mo in the TKI group 28.8 mo in the IO group (p = 0.081). Median PFS was 6.4 mo in the TKI group and 17.4 mo in the IO group (p < 0.001). The ORR was higher in the IO group than in the TKI group (41% vs 27%; p = 0.037). CONCLUSIONS AND CLINICAL IMPLICATIONS: Our results show that IO-based combinations have superior efficacy outcomes to TKIs for first-line treatment of metastatic pRCC. PATIENT SUMMARY: The ARON-1 project collects clinical data for patients with kidney cancer treated in multiple centers worldwide to assess outcomes in the real-world setting. We analyzed data for patients with metastatic kidney cancer of a specific subtype to evaluate the efficacy of different first-line treatments. Patients treated with immune-based combinations had better outcomes than patients treated with tyrosine kinase inhibitors.

TERT promoter mutations increase tumor aggressiveness by altering TERT mRNA splicing in papillary thyroid carcinoma.

CONTEXT: Telomerase reverse transcriptase promoter (TERT-p) mutations, which upregulate TERT expression, are strongly associated with tumor aggressiveness and worse prognosis in papillary thyroid carcinomas (PTCs). TERT expression is also observed in a proportion of PTCs without TERT-p mutations, but such tumors show less aggressiveness and better prognosis compared with TERT-p mutation-positive tumors. OBJECTIVE: TERT has multiple splicing variants whose relationships with the TERT-p status and clinicopathological characteristics remain poorly understood. We examined the relationship between the TERT-p mutational status, the TERT splicing pattern, and clinicopathological features. METHODS: We investigated the expression of two major variants, α deletion (dA) and ß deletion (dB), in a series of 207 PTCs operated between November 2001 and March 2020 in Nagasaki University Hospital and Kuma Hospital. RESULTS: The TERT-p mutations were found in 33 cases, and among 174 mutation-negative cases, 24 showed TERT expression. All cases were classified into three groups: the TERT-p mutation-negative/expression-negative group (mut-/exp-), the TERT-p mutation-negative/expression-positive group (mut-/exp+), and the TERT-p mutation-positive group (mut+/exp+). The +A + B/dB ratio in mut+/exp + was significantly higher than that in mut-/exp + PTCs. Analysis with clinicopathological data revealed that +A + B expression was associated with higher PTC aggressiveness, whereas dB expression counteracted this effect. Functional in vitro study demonstrated that dB strongly inhibited cell growth, migration, and clonogenicity, suggesting its tumor suppressive role. CONCLUSION: These results provide evidence that the TERT-p mutations alter the expression of different TERT splice variants, which, in turn, associates with different tumor aggressiveness.

Status of mental and social activities of young and middle-aged patients after papillary thyroid cancer surgery.

Background: Papillary thyroid cancer (PTC) is prevalent among younger populations and has a favorable survival rate. However, a significant number of patients experience psychosocial stress and a reduced quality of life (QoL) after surgical treatment. Therefore, comprehensive evaluations of the patients are essential to improve their recovery. Methods: The present study enrolled 512 young and middle-aged patients diagnosed with PTC who underwent surgery at our institution between September 2020 and August 2021. Each participant completed a series of questionnaires: Generalized Anxiety Disorder 7 (GAD-7), European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), Thyroid Cancer-Specific Quality of Life Questionnaire (THYCA-QoL), and Readiness to Return-to-Work Scale (RRTW). Results: GAD-7 data showed that almost half of the study subjects were experiencing anxiety. Regarding health-related quality of life (HRQoL), participants reported the highest levels of fatigue, insomnia, voice problems, and scarring, with patients in anxious states reporting worse symptoms. Based on RRTW, more than half of the subjects had returned to work and had better HRQoL compared to the others who were evaluating a possible return to work. Age, gender, BMI, education, diet, residence, health insurance, months since surgery, monthly income, and caregiver status were significantly correlated with return to work. Additionally, having a caregiver, higher monthly income, more time since surgery, and living in a city or village were positively associated with return to work. Conclusion: Young and middle-aged patients with PTC commonly experience a range of health-related issues and disease-specific symptoms following surgery, accompanied by inferior psychological well-being, HRQoL, and work readiness. It is crucial to prioritize timely interventions targeting postoperative psychological support, HRQoL improvement, and the restoration of working ability in PTC patients.

Underlying effect of SMAD4 gene polymorphism on risk prediction of papillary thyroid carcinoma in Chinese population.

Objective: This research intends to explore how variations in the SMAD4 gene impact papillary thyroid carcinoma (PTC) among patients in China. Methods: The rs10502913 and rs12968012 polymorphisms were genotyped in 405 subjects using SNP-scan high-throughput technology. Differential mRNA expression of SMAD4 was analyzed using data from TCGA and GSE33630, and protein level expression differences were analyzed using immunohistochemistry. Results: The results showed that SMAD4 mRNA expression was lower in thyroid cancer (THCA) tissues than in normal tissues. Immunohistochemical results showed that the expression level of SMAD4 in normal tissue, thyroid papillary carcinoma tissue and poorly differentiated tissue was significantly different. We found that SMAD4 mismatch variants (rs10502913 and rs12968012) were associated with PTC susceptibility. Specifically, the SMAD4-rs10502913 genotypes (GA and AA) showed a notable correlation with a lower likelihood of PTC in comprehensive and segmented studies (genotype GA: OR (95% CI) = 0.270 (0.077-0.950), p = 0.041; genotype AA: OR (95% CI) = 0.103 (0.025-0.416), p = 0.001). We categorized the immunohistochemical results according to genotype and found that rs10502913-GG protein level was expressed at the lowest level, and both GA and AA were higher than GG (GG vs. AA, P < 0.05), and rs12968012-CG protein level was expressed at the lowest level, and both GG and CC were higher than CG (GG vs. CG, P < 0.01). Conclusion: Two missense variants of SMAD4 (rs10502913 and rs12968012) are associated with reduced risk of papillary thyroid carcinoma, possibly by reducing protein expression leading to susceptibility to papillary thyroid carcinoma.

Risk factors for tumor enlargement in low-risk papillary thyroid microcarcinoma patients: a systematic review and meta-analysis.

PURPOSE: The current management guidelines for low-risk papillary thyroid microcarcinoma (PTMC) do not specify how to screen for growing tumors. We sought to explore the possible risk factors for tumor enlargement in patients with low-risk PTMC under active surveillance (AS). METHODS: We searched the PubMed and Embase databases for high quality studies up to January 10th, 2024. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the included studies, and Review Manager 5.4 was used to analyze possible risk factors and calculate pooled risk ratios (RRs) via the inverse-variance calculation method. RESULTS: Eleven studies were included in our meta-analysis. Among the 8880 participants, 464 experienced tumor growth, and the incidence of tumor growth varied from 3.4% to 19.4%. The results of the meta-analysis showed that tumor enlargement was associated with younger age (pooled RR = 2.32, 95% CI = 1.85-2.90, p < 0.00001; 8 studies), and higher serum thyroid-stimulating hormone (TSH) levels (pooled RR = 2.28, 95% CI = 1.19-4.37, p = 0.01; 6 studies), and could be related to pregnancy (pooled RR = 2.54, 95% CI = 1.17-5.52, p = 0.02; 2 studies). However, these following factors showed no significant association with tumor growth: sex (pooled RR = 1.07, 95% CI = 0.63-1.84, p = 0.79; 7 studies), tumor size at diagnosis (pooled RR = 1.08, 95% CI = 0.63-1.85, p = 0.77; 5 studies), and Hashimoto's thyroiditis (HT) (pooled RR = 1.56, 95% CI = 0.93-2.60, p = 0.09; 2 studies). CONCLUSION: Our analysis identified that younger age and higher serum TSH levels were higher risk factors for tumor enlargement in low-risk PTMC patients. Pregnancy is a suspected risk factor.

Cost-Utility Analysis of Early Detection with Ultrasonography of Differentiated Thyroid Cancer: A Retrospective Study on a Korean Population.

Background: There is debate about ultrasonography screening for thyroid cancer and its cost-effectiveness. This study aimed to evaluate the cost-effectiveness of early screening (ES) versus symptomatic detection (SD) for differentiated thyroid cancer (DTC) in Korea. Methods: A Markov decision analysis model was constructed to compare the cost-effectiveness of ES and SD. The model considered direct medical costs, health outcomes, and different diagnostic and treatment pathways. Input data were derived from literature and Korean population studies. Incremental cost-effectiveness ratio (ICER) was calculated. Willingness-to-pay (WTP) threshold was set at USD 100,000 or 20,000 per quality-adjusted life year (QALY) gained. Sensitivity analyses were conducted to address uncertainties of the model's variables. Results: In a base case scenario with 50 years of follow-up, ES was found to be cost-effective compared to SD, with an ICER of $2,852 per QALY. With WTP set at $100,000, in the case with follow-up less than 10 years, the SD was cost-effective. Sensitivity analysis showed that variables such as lobectomy probability, age, mortality, and utility scores significantly influenced the ICER. Despite variations in costs and other factors, all ICER values remained below the WTP threshold. Conclusion: Findings of this study indicate that ES is a cost-effective strategy for DTC screening in the Korean medical system. Early detection and subsequent lobectomy contribute to the cost-effectiveness of ES, while SD at an advanced stage makes ES more cost-effective. Expected follow-up duration should be considered to determine an optimal strategy for DTC screening.

Bergapten attenuates human papillary thyroid cancer cell proliferation by triggering apoptosis and the GSK-3ß, P13K and AKT pathways.

BACKGROUND: Over the past few decades, thyroid cancer (TC) incidence has steadily increased globally. The most common TC is human papillary thyroid carcinoma (PTC), which is poorly responsive to the current treatments. Hence, finding a successful therapeutic is urgently required. OBJECTIVES: Bergapten (BG) is a furanocoumarin, a natural psoralen derivative isolated from numerous species of citrus and bergamot oil that has demonstrated anti-tumor activity. However, there are no reports available on the efficacy of BG on PTC cells. MATERIAL AND METHODS: The current research investigated the anti-cancer activity of BG on human BCPAP cells, with cytotoxicity and apoptosis evaluated using MTT assay, AO/EB, DAPI, PI, ELISA, mRNA, and western blot. RESULTS: Bergapten (control group, 10 µM/mL and 15 µM/mL) inhibited PTC cell proliferation and stimulated apoptosis by enhancing Bax and caspase and reducing Bcl-2, cyclin-D1, c-myc, and survivin in a dose-dependent manner. Furthermore, BG expressively attenuated PI3K/AKT/GSK-3ß signaling, creating an uneven Bax/Bcl-2 ratio that triggered Cyt-c, caspase cascade and apoptosis in human PTC cells. CONCLUSIONS: Our findings emphasize that BG has the potential to be used as a protective natural remedy for human PTC cells.

Predictors of recurrence after total thyroidectomy in 1,611 patients with papillary thyroid carcinoma: postoperative stimulated serum thyroglobulin and ATA initial and dynamic risk assessment.

Objective: Despite a favorable prognosis, some patients with papillary thyroid carcinoma (PTC) develop recurrence. The objective of this study was to examine the impact of the combination of initial American Thyroid Association (ATA) risk stratification with serum level of postoperative stimulated thyroglobulin (s-Tg) in predicting recurrence in patients with PTC and compare the results with an assessment of response to initial therapy (dynamic risk stratification). Subjects and methods: We retrospectively analyzed 1,611 patients who had undergone total thyroidectomy for PTC, followed in most cases (87.3%) by radioactive iodine (RAI) administration. Clinicopathological features and s-Tg levels obtained 3 months postoperatively were evaluated. The patients were stratified according to ATA risk categories. Nonstimulated thyroglobulin levels and imaging studies obtained during the first year of follow-up were used to restage the patients based on response to initial therapy. Results: After a mean follow-up of 61.5 months (range 12-246 months), tumor recurrence was diagnosed in 99 (6.1%) patients. According to ATA risk, recurrence was identified in 2.3% of the low-risk, 9% of the intermediate-risk, and 25% of the high-risk patients (p < 0.001). Using a receiver operating characteristic curve approach, a postoperative s-Tg level of 10 ng/mL emerged as the ideal cutoff value, with positive and negative predictive values of 24% and 97.8%, respectively (p < 0.001). Patients with low to intermediate ATA risk with postoperative s-Tg levels < 10 ng/mL and excellent response to treatment had a very low recurrence rate (<0.8%). In contrast, higher recurrence rates were observed in intermediate-riskto high-risk patients with postoperative s-Tg > 10 ng/mL and indeterminate response (25%) and in those with incomplete response regardless of ATA category or postoperative s-Tg value (38.5-87.5%). Using proportion of variance explained (PVE), the predicted recurrence using the ATA initial risk assessment alone was 12.7% and increased to 29.9% when postoperative s-Tg was added to the logistic regression model and 49.1% with dynamic risk stratification. Conclusion: The combination of ATA staging system and postoperative s-Tg can better predict the risk of PTC recurrence. Initial risk estimates can be refined based ondynamic risk assessment following response to therapy, thus providing a useful guide for follow-up recommendations.

Clinical value of ultrasound parameters PI, TTP, and MTT in assessing cervical lymph node metastasis of papillary thyroid carcinoma.

OBJECTIVE: To determine the clinical value of ultrasound in assessing cervical lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC). METHODS: The medical records of 179 PTC patients treated in Shandong Provincial Qianfoshan Hospital between March 2016 and March 2019 were collected. The patients were assigned to a transfer group (54 cases) and a non-transfer group (125 cases) according to their pathologic results. The ultrasound parameters (peak intensity (PI), time to peak (TTP), and mean transit time (MTT)) of the two groups were compared. Then, multivariate logistic regression was used to analysis the results, and receiver operating characteristic (ROC) curves were plotted to evaluate the value of risk factors in predicting CLNM. RESULTS: The transfer group showed notably lower PI, TTP and MTT than the non-transfer group (P<0.001), and focus diameter, microcalcification, multiple foci, PI, TTP, and MTT were identified as independent risk factors for LNM in patients (P<0.05). According to the ROC curve, the areas under the curves (AUCs) of microcalcification, multiple foci, and PI were all smaller than 0.7; the AUCs of focus diameter and MTT were smaller than 0.8, and the AUC of TTP was 0.855. CONCLUSION: PI, TTP, and MTT all decrease in PTC patients with CLNM, and TTP has a strong predictor for CLNM in them, with an AUC of 0.855.

Development and validation of prediction models for papillary thyroid cancer structural recurrence using machine learning approaches.

BACKGROUND: Although papillary thyroid cancer (PTC) patients are known to have an excellent prognosis, up to 30% of patients experience disease recurrence after initial treatment. Accurately predicting disease prognosis remains a challenge given that the predictive value of several predictors remains controversial. Thus, we investigated whether machine learning (ML) approaches based on comprehensive predictors can predict the risk of structural recurrence for PTC patients. METHODS: A total of 2244 patients treated with thyroid surgery and radioiodine were included. Twenty-nine perioperative variables consisting of four dimensions (demographic characteristics and comorbidities, tumor-related variables, lymph node (LN)-related variables, and metabolic and inflammatory markers) were analyzed. We applied five ML algorithms-logistic regression (LR), support vector machine (SVM), extreme gradient boosting (XGBoost), random forest (RF), and neural network (NN)-to develop the models. The area under the receiver operating characteristic (AUC-ROC) curve, calibration curve, and variable importance were used to evaluate the models' performance. RESULTS: During a median follow-up of 45.5 months, 179 patients (8.0%) experienced structural recurrence. The non-stimulated thyroglobulin, LN dissection, number of LNs dissected, lymph node metastasis ratio, N stage, comorbidity of hypertension, comorbidity of diabetes, body mass index, and low-density lipoprotein were used to develop the models. All models showed a greater AUC (AUC = 0.738 to 0.767) than did the ATA risk stratification (AUC = 0.620, DeLong test: P < 0.01). The SVM, XGBoost, and RF model showed greater sensitivity (0.568, 0.595, 0.676), specificity (0.903, 0.857, 0.784), accuracy (0.875, 0.835, 0.775), positive predictive value (PPV) (0.344, 0.272, 0.219), negative predictive value (NPV) (0.959, 0.959, 0.964), and F1 score (0.429, 0.373, 0.331) than did the ATA risk stratification (sensitivity = 0.432, specificity = 0.770, accuracy = 0.742, PPV = 0.144, NPV = 0.938, F1 score = 0.216). The RF model had generally consistent calibration compared with the other models. The Tg and the LNR were the top 2 important variables in all the models, the N stage was the top 5 important variables in all the models. CONCLUSIONS: The RF model achieved the expected prediction performance with generally good discrimination, calibration and interpretability in this study. This study sheds light on the potential of ML approaches for improving the accuracy of risk stratification for PTC patients. TRIAL REGISTRATION: Retrospectively registered at www.chictr.org.cn (trial registration number: ChiCTR2300075574, date of registration: 2023-09-08).

Analysis of risk factors for lateral lymph node metastasis in T1 stage papillary thyroid carcinoma: a retrospective cohort study.

Background: The occurrence of cervical lymph node metastasis in T1 stage papillary thyroid carcinoma (PTC) is frequently observed. Notably, lateral lymph node metastasis (LLNM) emerges as a critical risk factor adversely affecting prognostic outcomes in PTC. The primary aim of this investigation was to delineate the risk factors associated with LLNM in the initial stages of PTC. Methods: This retrospective analysis encompassed 3,332 patients diagnosed with T1 stage PTC without evident LLNM at the time of diagnosis. These individuals underwent primary surgical intervention at West China Hospital, Sichuan University between June 2017 and February 2023. The cohort was divided into two groups: patients manifesting LLNM and those without metastasis at the time of surgery. Additionally, T1 stage PTC patients were subdivided into T1a and T1b categories. Factors influencing LLNM were scrutinized through both univariate and multivariate analyses. Results: The incidence of LLNM was observed in 6.2% of the cohort (206 out of 3,332 patients). Univariate analysis revealed significant correlations between LLNM and male gender (P<0.001), tumor localization in the upper lobe (P<0.001), maximal volume of the primary tumor (P<0.001), largest tumor diameter (P<0.001), multifocality (P<0.001), and bilaterality (P<0.001), with the exception of age (P=0.788) and duration of active surveillance (AS) (P=0.978). Multivariate logistic regression analysis identified male gender (P<0.001), upper lobe tumor location (P<0.001), maximal primary tumor volume (P<0.001), and multifocality (P<0.001) as independent predictors of LLNM. However, age categories (≤55, >55 years), maximum tumor diameter, bilaterality, and surveillance duration did not exhibit a significant impact. Comparative analyses between T1a and T1b subgroups showed congruent univariate results but revealed differences in multivariate outcomes. In the T1a subgroup, gender, tumor location, and multifocality (all P<0.05) were associated with elevated LLNM risk. Conversely, in the T1b subgroup, tumor location, dimensions, and multifocality (all P<0.05) were significant predictors of LLNM risk, whereas gender (P=0.097) exerted a marginal influence. Conclusions: The investigation highlights several key risk factors for LLNM in T1 stage PTC patients, including gender, upper lobe tumor location, larger tumor size, and multifocality. Conversely, prolonged AS and younger age did not significantly elevate LLNM risk, suggesting the viability of AS as a strategic option in selected cases.

Prediction of lymph node metastasis in patients with papillary thyroid cancer based on radiomics analysis and intraoperative frozen section analysis: A retrospective study.

INTRODUCTION: To evaluate the diagnostic efficiency among the clinical model, the radiomics model and the nomogram that combined radiomics features, frozen section (FS) analysis and clinical characteristics for the prediction of lymph node (LN) metastasis in patients with papillary thyroid cancer (PTC). METHODS: A total of 208 patients were randomly divided into two groups randomly with a proportion of 7:3 for the training groups (n = 146) and the validation groups (n = 62). The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for the selection of radiomics features extracted from ultrasound (US) images. Univariate and multivariate logistic analyses were used to select predictors associated with the status of LN. The clinical model, radiomics model and nomogram were subsequently established by logistic regression machine learning. The area under the curve (AUC), sensitivity and specificity were used to evaluate the diagnostic performance of the different models. The Delong test was used to compare the AUC of the three models. RESULTS: Multivariate analysis indicated that age, size group, Adler grade, ACR score and the psammoma body group were independent predictors of lymph node metastasis (LNM). The results showed that in both the training and validation groups, the nomogram showed better performance than the clinical model, albeit not statistically significant (p > .05), and significantly outperformed the radiomics model (p < .05). However, the nomogram exhibits a slight improvement in sensitivity that could reduce the incidence of false negatives. CONCLUSION: We propose that the nomogram holds substantial promise as an effective tool for predicting LNM in patients with PTC.