The influence of nodule size on the aggressiveness of thyroid carcinoma varies with patient's age

Risk factors and nomogram to predict skip metastasis in papillary thyroid carcinoma

Background

Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy. Skip metastases of PTCs are easily misdiagnosed before surgery, and it could lead to re-operation and affect the prognosis. Although there are a few studies about nomograms for predicting central lymph node metastases (CLNM) or lateral lymph node metastases (LLNM) of PTCs, there are few studies about nomograms for skip metastases. Based on the clinical and ultrasonographic characteristics of patients with PTCs, the aim of our study was to investigate the risk factors and establish a nomogram for predicting the risk of skip metastases in PTCs.

Methods

This study enrolled 218 PTCs patients with lateral cervical lymph node metastases and their data were analyzed retrospectively. According to the postoperative pathological results, the patients were divided into skip-positive group and skip-negative group. In order to establish the nomogram, univariate and multivariate analyses were used to estimate risk factors of skip metastases. The receiver operating characteristic (ROC) curve, internal calibration plot and decision curve analysis (DCA) were used to evaluate the nomogram model's efficacy.

Results

There were statistical differences between skip-positive group and skip-negative group in tumor location, the maximum diameter (D) and capsule invasion (P<0.05). No statistical differences were observed in sex, age, Hashimoto's thyroiditis, multifocality, anteroposterior diameter/transverse diameter (A/T) ratio, shape, margin, microcalcification, intra-nodular vascularity and preoperative serum thyroglobulin (Tg) (P≥0.05). The risk factors of skip metastases in PTCs were D ≤10 mm, location in the upper portion and capsule invasion. The area under the curve (AUC) of nomogram was 0.877, the accuracy was 85.32%, the sensitivity was 60.98%, and the specificity was 90.96%. The calibration curve and the Hosmer-Lemeshow goodness of fit test showed that the consistency between the nomogram and the actual observation was good. The DCA showed that most PTC patients might benefit from the predictive nomogram model.

Conclusions

A nomogram for predicting skip metastases in PTCs may be useful in clinical diagnosis and treatment.

The Impact of BRAF V600E Mutation Allele Frequency on the Histopathological Characteristics of Thyroid Cancer

BACKGROUND

A BRAF V600E mutation in papillary thyroid cancer (PTC) has been shown to be associated with aggressive behavior. Nevertheless, not all BRAF V600E PTCs behave aggressively. Allele frequency (AF) is the number of mutated molecules divided by the total number of wild-type molecules at a specific location in the genome. The relationship between BRAF V600E AF and the histopathological features of thyroid malignancies is not well understood. We hypothesized that the BRAF V600E AF will correlate directly with aggressive histopathological behavior. The aim of this study was to examine this relationship.

METHODS

A retrospective chart review was performed for patients treated for BRAF V600E thyroid malignancies from 2019 to 2022 at McGill University tertiary care hospitals (n = 317). Patients with BRAF V600E-positive malignancies that included information on AF were included (n = 44). The correlation between AF and tumor histopathological features was analyzed.

RESULTS

Out of the 44 nodules with a BRAF V600E mutation, those with aggressive features of PTC had a mean AF of 25.8%, which was significantly higher than the non-aggressive group with a mean AF of 10.25% (p = 0.020). Additionally, there was a statistically significant difference in mean AF between patients with a positive sentinel LN (29%) and those with a negative sentinel LN (17.8%) (p = 0.021). Classical PTC was present in 29.5% (13/44) of nodules, with a mean AF of 15.6%. The tall cell subtype was found in 64% (28/44) of nodules, with a mean AF of 23%. Solid and hobnail subtypes were less common in this study, and there was no statistically significant relationship between AF and histopathological subtypes (p = 0.107). Nodules smaller than 1cm had a mean AF of 13.3%, while nodules ranging from 1 2cm had a mean AF of 20.6%, and those larger than 2cm had a mean AF of 27.7%. However, no statistical difference was observed between AF and nodule size (p = 0.160).

CONCLUSION

In this study, BRAF V600E mutations in conjunction with AF help to determine whether thyroid malignancies will display aggressive behavior. This pre-operative finding can help thyroid specialists to determine the extent of thyroidectomy and whether lymph node dissection is required.

Differentiating pathologic parathyroid glands from thyroid nodules on neck ultrasound: the PARATH-US cross-sectional study

Background

Neck ultrasound (US) is a widely used and accessible operator-dependent technique that helps characterize thyroid nodules and pathologic parathyroid glands (PPGs). However, thyroid nodules may sometimes be confused with PPGs. PARATH-US study aims at identifying US characteristics to differentiate PPGs from thyroid nodules, as there is no study, at present, which directly compares the US features of these two common neoplasms.

Methods

PARATH-US is a single-center study that was conducted at a tertiary referral center, including consecutive lesions from patients undergoing neck US examination from 2016 to 2022.

Findings

176 PPGs (158 patients: serum calcium levels 2.91 [IQR 2.74-3.05] mmol/L, PTH levels 173 [112-296] ng/L) were compared to 232 size- and volume-matched thyroid nodules (204 age- and sex-matched patients). The morphologic patterns, echoic content and vascular status were all different between PPGs and thyroid neoplasms (p < 0.01 for all comparisons). The combined parameters maximally discriminated PPGs from thyroid nodules (OR, 7.6; 95% CI: 3.4, 17.1, p < 0.0001). When applying risk stratification systems developed for thyroid malignancies, 58-63% of PPGs were classified as high-risk lesions. Parathyroid adenomas had larger sizes and volumes than hyperplasias (p = 0.013 and p = 0.029). Serum calcium and PTH levels were significantly correlated with PPG size and volume (p < 0.0001 for all comparisons).

Interpretation

We demonstrate the presence of distinct US characteristics in PPGs, which help differentiate them from thyroid nodules. When mistaken for thyroid nodules, PPGs bear high-risk US features. When dealing with high-risk cervical lesions detected on US, a PPG should be suspected, and an assessment of calcium levels recommended to avoid unnecessary invasive procedures.

Funding

CYTO-TRAIN, C2022DOSRH053, funded by the French Regional Health Agency.

Prediction of papillary thyroid metastases to the central compartment: proposal of a model taking into consideration other thyroid conditions

Objective

To construct risk prediction models for cervical lymph node metastasis (CLNM) of papillary thyroid carcinoma (PTC) under different thyroid disease backgrounds and to analyze and compare risk factors among different groups.

Methods

This retrospective study included 518 patients with PTC that was pathologically confirmed post-operatively from January 2021 to November 2021. Demographic, ultrasound and pathological data were recorded. Univariate and multivariate logistic regression analyses were performed to identify factors associated with CLNM in the whole patient cohort and in patients grouped according to diagnoses of Hashimoto's thyroiditis (HT), nodular goiter (NG), and no background disease. Prediction models were constructed for each group, and their performances were compared.

Results

Analysis of the whole PTC patient cohort identified NG as independently associated with CLNM. The independent risk factors for patients with no background disease were the maximum thyroid nodule diameter and American College of Radiology Thyroid Imaging Reporting & Data System score; those for patients with HT were the maximum thyroid nodule diameter, ACR TI-RADS score, and multifocality; and those for patients with NG were the maximum thyroid nodule diameter, ACR TI-RADS score, multifocality and gender.

Conclusion

Background thyroid disease impacts CLNM in PTC patients, and risk factors for CLNM vary among PTC patients with different background diseases. Ultrasound is useful for diagnosing background thyroid disease, which can inform treatment planning. Different prediction models are recommended for PTC cases with different thyroid diseases.

Interpretable machine learning model based on the systemic inflammation response index and ultrasound features can predict central lymph node metastasis in cN0T1-T2 papillary thyroid carcinoma

Background

It is arguable whether individuals with T1-T2 papillary thyroid cancer (PTC) who have a clinically negative (cN0) diagnosis should undergo prophylactic central lymph node dissection (pCLND) on a routine basis. Many inflammatory indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and systemic immune-inflammatory index (SII), have been reported in PTC. However, the associations between the systemic inflammation response index (SIRI) and the risk of central lymph node metastasis (CLNM) remain unclear.

Methods

Retrospective research involving 1,394 individuals with cN0T1-T2 PTC was carried out, and the included patients were randomly allocated into training (70%) and testing (30%) subgroups. The preoperative inflammatory indices and ultrasound (US) features were used to train the models. To assess the forecasting factors as well as drawing nomograms, the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were utilized. Then eight interpretable models based on machine learning (ML) algorithms were constructed, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost). The performance of the models was evaluated by incorporating the area under the precision-recall curve (auPR) and the area under the receiver operating characteristic curve (auROC), as well as other conventional metrics. The interpretability of the optimum model was illustrated via the shapley additive explanations (SHAP) approach.

Results

Younger age, larger tumor size, capsular invasion, location (lower and isthmus), unclear margin, microcalcifications, color Doppler flow imaging (CDFI) blood flow, and higher SIRI (≥0.77) were independent positive predictors of CLNM, whereas female sex and Hashimoto thyroiditis were independent negative predictors, and nomograms were subsequently constructed. Taking into account both the auROC and auPR, the RF algorithm showed the best performance, and superiority to XGBoost, CatBoost and ANN. In addition, the role of key variables was visualized in the SHAP plot.

Conclusions

An interpretable ML model based on the SIRI and US features can be used to predict CLNM in individuals with cN0T1-T2 PTC.

Patient's age with papillary thyroid cancer: Is it a key factor for cervical lymph node metastasis?

BACKGROUND

Age is one of the important prognostic indicators of papillary thyroid cancer (PTC). However, the distinct metastatic patterns and prognosis of age-related lymph node metastasis (LNM) are unclear. This study aims to investigate the impact of age on LNM.

METHODS

We conducted two independent cohort studies to assess age-nodal disease association using logistic regression analysis and a restricted cubic splines model. A multivariable Cox regression model was utilized to test the impact of nodal disease on cancer-specific survival (CSS) after age stratification.

RESULTS

For this study, we included 7572 and 36,793 patients with PTC in Xiangya and SEER cohorts, respectively. After adjustment, advanced age was linearly associated with decreasing risk of central LNM. Patients of age ≤18 years (OR = 4.41, P < 0.001) and 19-45 years (OR = 1.97, P = 0.002) had a higher risk of developing lateral LNM than patients of age >60 years in both cohorts. Furthermore, CSS is significantly reduced in N1b disease (P < 0.001), not N1a disease, regardless of age. The incidence of high-volume LNM (HV-LNM) was significantly higher in patients of age ≤18 years and 19-45 years than in those of age >60 years (P < 0.001), in both cohorts. In addition, CSS was compromised in patients with PTC of age 46-60 years (HR = 1.61, P = 0.022) and those of age >60 (HR = 1.40, P = 0.021) after developing HV-LNM.

CONCLUSIONS

Patient age is significantly associated with LNM and HV-LNM. Patients with N1b disease or patients with HV-LNM of age >45 years have significantly shorter CSS. Age can, thus, be a useful guide for determining treatment strategies in PTC.

Can Cervical Lymph Node Metastasis Increase the Risk of Distant Metastasis in Papillary Thyroid Carcinoma?

BACKGROUND

Distant metastasis (DM) is a rare event and has a negative effect on the prognosis for papillary thyroid carcinoma (PTC). The relationship between cervical lymph node metastasis and DM is complicated and unclear. This study aimed to evaluate the impact of N stage subclassification on different distant metastasis sites based on age stratification, especially for patients with papillary thyroid microcarcinoma.

METHODS

A total of 28,712 patient with PTC cases between 2010 and 2018 were extracted from the Surveillance, Epidemiology, and End Results database. Multivariable logistic regression analysis was utilized to adjust for confounding variables. Risk stratification, including positive lymph node number and lymph node ratio, was established by receiver operating characteristic curves to help predict DM.

RESULTS

Lung was the most common metastatic site regardless of N0, N1a disease, or N1b disease. As the N stage increased, the higher the rate of DM identified. After age stratification, only N1b disease significantly increased the risk of lung metastasis (LM; odds ratio, OR = 20.45, P < 0.001) rather than bone metastasis (BM; OR = 3.46, P > 0.05) in younger patients. However, in older patients, N1b disease significantly increased the risk of both LM (OR = 4.10, P < 0.001) and BM (OR = 2.65, P = 0.007). In patients with papillary thyroid microcarcinoma (PTMC), N1a disease did not increase the risk of DM, LM, and BM compared with N0 disease (P > 0.05). Furthermore, combined N stage with risk stratification has well performance in predicting DM (area under the curve, AUC = 0.761). Similar results were shown in PTC patients with LM (AUC = 0.770) and BM (AUC = 0.729).

CONCLUSION

Overall, the incidence of DM significantly increased with the progress of N disease after age stratification. N1a disease did not increase the risk of DM in PTMC patients, regardless of LM or BM. Combined N stage with risk stratification may be beneficial for DM prediction.

A critical analysis of the current TNM classification for differentiated thyroid carcinoma in young patients: Time for a change?

BACKGROUND

The current TNM classification that simply classifies differentiated thyroid carcinoma (DTC) patients younger than 55 years into stage I and stage II based on the presence or absence of distant metastases has been questioned. In this study, we reexamined the impact of T status and N status on prognosis and then developed a new prediction model to improve the predictability of cancer-specific survival (CSS) in young patients.

MATERIALS AND METHODS

Kaplan-Meier method was applied to calculate the CSS. Multivariable Cox proportional hazards models were used to assess the impact of T status and N status on CSS after adjustment for known covariates. The area under the receiver operating characteristic curve (AUC), C-index, Bayesian information criterion (BIC), and Akaike information criterion (AIC) were calculated to compare model performance.

RESULTS

A total of 9,242 DTC patients younger than 55 years were enrolled in the study. After adjusting for gender, age at diagnosis, race, pathology subtype, N stage, and M stage, T3 disease [hazard ratio (HR): 3.78, P = 0.006] and T4 disease (HR: 7.96, P < 0.001) remain independent predictors of CSS. Similarly, the 10-year CSS rate of N1b disease (HR: 3.78, P < 0.001) was significantly higher than that of N0 disease after adjustment. Moreover, Kaplan-Meier survival analysis showed that the 10-year CSS of stage II disease in younger patients with DTC showed a sharp decrease compared with that in older patients with DTC (74.47% vs. 98.43%, P < 0.001). Furthermore, a modified TNM staging system based on significantly prognostic T stage and N stage was established, which showed better performance than the current TNM staging system (P < 0.05). The new prediction model is also applicable to papillary thyroid carcinoma patients and follicular thyroid carcinoma patients.

CONCLUSIONS

This is the first study to question the rationality of the current TNM staging system for patients younger than 55 years and successfully develop a new prognostic model, which improves prognostic stratification and guides individualized management.