Lymph node metastasis-dependent molecular classification in papillary thyroid carcinoma defines aggressive metastatic outgrowth.
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ABSTRACT:
SUBMITTER: Seo DH
PROVIDER: S-EPMC10019769 | biostudies-literature | 2023 Mar
REPOSITORIES: biostudies-literature
Publications
Lymph node metastasis-dependent molecular classification in papillary thyroid carcinoma defines aggressive metastatic outgrowth.
Seo Dong Hyun DH Lee Seul Gi SG Lee Hwa Young HY Jeong Seonhyang S Park Sunmi S Lee Jandee J Jo Young Suk YS
Clinical and translational medicine 20230301 3
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Project description: Not available
| S-EPMC10681174 | biostudies-literature
Project description:BackgroundThe objective of this study is to develop a predictive model for the assessment of cervical lymph node metastasis risk in papillary thyroid carcinoma (PTC).MethodsA retrospective study was conducted on 212 patients with PTC who underwent initial surgical treatment from August 2022 to April 2023 in 2 hospitals. Data were randomly split into 7:3 training-validation sets. Logistic regression was used for feature selection and predictive model creation. Model performance was assessed using receiver operating characteristic (ROC) and calibration curves. Clinical utility was determined using decision curves.ResultsAmong the 212 patients with PTC, 104 cases (49.1%) exhibited cervical lymph node metastasis, while 108 cases (50.9%) did not. Multivariate logistic regression analysis revealed that age (OR = 0.95), FT3 (OR = 0.41), tumor maximum diameter ≥0.9 cm (OR = 1.85), intratumoral microcalcifications (OR = 1.84), and suspicious lymph node on ultrasound (OR = 2.96) were independent risk factors for lymph node metastasis in PTC patients (P < 0.05). The constructed model for predicting the risk of cervical lymph node metastasis demonstrated a training set ROC curve area under the curve (AUC) of 0.742 (95% CI: 0.664 - 0.821), with a cut-off value of 0.615, specificity of 87.8%, and sensitivity of 51.4%. The validation set exhibited an AUC of 0.648 (95% CI: 0.501 - 0.788), with a cut-off value of 0.644, specificity of 91.2%, and sensitivity of 43.3%. Including the BRAF V600 E mutation did not improve the model's diagnostic performance significantly. Decision curve analysis indicated clinical feasibility of the model.ConclusionThe predictive model developed in this study effectively predicts lymph node metastasis risk in PTC patients by incorporating ultrasound features, demographic characteristics, and serum parameters. However, including the BRAF V600 E mutation does not significantly improve the model's diagnostic performance.
| S-EPMC11497514 | biostudies-literature
Project description:Lin28 is involved in the progression of several types of tumors. Data collected from clinical trials have suggested that Lin28 expression is correlated with poor prognosis in thyroid carcinoma. The present study was conducted to investigate the association between Lin28 expression and the clinicopathological parameters of papillary thyroid carcinoma (PTC). Accordingly, the clinical data and diagnostic results from 237 patients with PTC were collected. Immunohistochemical staining was performed to evaluate the Lin28 expression levels in thyroid tissue samples. Associations between the expression levels and clinicopathological parameters were evaluated. Lin28 was expressed in 96/237 (40.5%) of PTC specimens. Compared with patients with no Lin28 expression, patients with expression had higher rates of lymph node metastasis (P<0.001) and larger tumors (P=0.011). Multivariate analysis revealed that Lin28 was associated with lymph node metastasis. Next, bioinformatics analysis was performed based using the Gene Expression Omnibus database and The Cancer Genome Atlas database. Lin28 expression was associated with aggressive tumor characteristics, such as lymph node metastasis and larger tumors. In conclusion, the present study revealed that Lin28 expression served as a risk factor for lymph node metastasis. Accordingly, Lin28 expression may be used as a prognostic marker to predict lymph node metastasis in patients with PTC. In addition, Lin28 may serve as a therapeutic target in the management of this tumor type, which may help improve patient outcomes.
| S-EPMC7751344 | biostudies-literature
Project description:ObjectivesPrecise determination of cervical lymph node metastasis (CLNM) involvement in patients with early-stage thyroid cancer is fairly significant for identifying appropriate cervical treatment options. However, it is almost impossible to directly judge lymph node metastasis based on the imaging information of early-stage thyroid cancer patients with clinically negative lymph nodes.MethodsPreoperative US images (BMUS and CDFI) of 1031 clinically node negative PTC patients definitively diagnosed on pathology from two independent hospitals were divided into training set, validation set, internal test set, and external test set. An ensemble deep learning model based on ResNet-50 was built integrating clinical variables, BMUS, and CDFI images using a bagging classifier to predict metastasis of CLN. The final ensemble model performance was compared with expert interpretation.ResultsThe ensemble deep convolutional neural network (DCNN) achieved high performance in predicting CLNM in the test sets examined, with area under the curve values of 0.86 (95% CI 0.78-0.94) for the internal test set and 0.77 (95% CI 0.68-0.87) for the external test set. Compared to all radiologists averaged, the ensemble DCNN model also exhibited improved performance in making predictions. For the external validation set, accuracy was 0.72 versus 0.59 (p = 0.074), sensitivity was 0.75 versus 0.58 (p = 0.039), and specificity was 0.69 versus 0.60 (p = 0.078).ConclusionsDeep learning can non-invasive predict CLNM for clinically node-negative PTC using conventional US imaging of thyroid cancer nodules and clinical variables in a multi-institutional dataset with superior accuracy, sensitivity, and specificity comparable to experts.Critical relevance statementDeep learning efficiently predicts CLNM for clinically node-negative PTC based on US images and clinical variables in an advantageous manner.Key points• A deep learning-based ensemble algorithm for predicting CLNM in PTC was developed. • Ultrasound AI analysis combined with clinical data has advantages in predicting CLNM. • Compared to all experts averaged, the DCNN model achieved higher test performance.
| S-EPMC10733258 | biostudies-literature
Project description: Not available
| S-EPMC9701902 | biostudies-literature
Project description:BackgroundDistant 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.MethodsA 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.ResultsLung 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).ConclusionOverall, 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.
| S-EPMC9263207 | biostudies-literature
Project description:BackgroundPapillary thyroid microcarcinoma (PTMC) is characterized by its favorable prognosis and potential for active surveillance (AS) as a management option. However, the presence of cervical lymph node (LN) metastasis, especially lateral LN metastasis, significantly impacts management and prognosis. Previous studies have focused on post-surgery risk factors for cervical LN metastasis. This study aims to identify predictors of lateral LN metastasis by analyzing pre-operative ultrasonographic findings alongside clinicopathological factors.MethodsA retrospective review of medical records was conducted for patients with PTMC who underwent surgery at Chonnam National University Hwasun Hospital between 2004 and 2013. This is a case-control study that compares patients with lateral LN metastasis (N1b) to age- and sex-matched patients without LN metastasis (N0). Subgroup analysis was performed to evaluate risk factors of skip metastasis.ResultsThe study included 90 patients with PTMC with lateral LN metastasis (N1b) and 268 age- and sex-matched patients without LN metastasis (N0). The mean age was 49.3 years, and female patients were dominant in both groups. Structural recurrences of 4.4% (4/90) were observed only in the N1b group. The N1b group exhibited a higher frequency of upper lobe tumor location compared to the N0 group (38.9% vs. 16.0%, p < 0.001). There was no significant difference in the locations with the presence of invasion to adjacent organs. A higher proportion of non-parallel shape was observed in the N1b group than the N0 group (80.0% vs. 66.0%, p = 0.013). There were no differences in echogenicity, sonographic feature, margin, and AP diameter of the thyroid gland between the two groups. In multivariate analysis, independent risk factors for lateral LN metastasis included extrathyroidal extension, multiplicity, upper lobe tumor location, and non-parallel shape. Skip metastasis in patients with PTMC was associated with upper lobe tumor location.ConclusionDetailed ultrasound examinations, evaluating tumor location, number, orientation, and the presence of ETE, are crucial in accurately predicting lateral LN metastasis especially when primary tumor was in the upper lobe to avoid missing skip metastasis. These evaluations can help guide the decision between AS and immediate surgery in patients with PTMC.
| S-EPMC11250241 | biostudies-literature
Project description:BackgroundWhether Hashimoto's thyroiditis (HT) affects the lymph node metastasis of papillary thyroid carcinoma (PTC) remains uncertain. The diagnostic criteria for HT differed in previous studies. Our study focused on analysing the influence of HT on PTC lymph node metastasis (LNM) with stringent diagnostic criteria for HT.MethodsA total of 444 patients diagnosed with PTC from 2019 to 2020 were enrolled and divided into two groups: HT group and non-HT group. Diagnostic criteria of HT were as follows: thyroid peroxidase antibody (+) and postoperative histopathology of Hashimoto's disease.ResultsThere was no significant difference in the LNM rate between HT group and non-HT group. Patients in the HT group had fewer numbers of metastatic LNs and lower metastatic LNs ratio in central region. In the HT group, age < 55 and tumor size ≥10 mm were independent risk factors for central LNM.ConclusionThe autoimmune response of HT seems to reduce the central lymph node metastasis of HT PTCs. Age < 55 and tumor size ≥10 mm were independent risk factors of central lymph node metastasis in HT PTCs.
| S-EPMC8734374 | biostudies-literature
Project description:Non-invasive assessment of the risk of lymph node metastasis (LNM) in patients with papillary thyroid carcinoma (PTC) is of great value for the treatment option selection. The purpose of this paper is to develop a transfer learning radiomics (TLR) model for preoperative prediction of LNM in PTC patients in a multicenter, cross-machine, multi-operator scenario. Here we report the TLR model produces a stable LNM prediction. In the experiments of cross-validation and independent testing of the main cohort according to diagnostic time, machine, and operator, the TLR achieves an average area under the curve (AUC) of 0.90. In the other two independent cohorts, TLR also achieves 0.93 AUC, and this performance is statistically better than the other three methods according to Delong test. Decision curve analysis also proves that the TLR model brings more benefit to PTC patients than other methods.
| S-EPMC7511309 | biostudies-literature
Project description:PurposeTreatment protocols for occult central lymph node metastasis (LNM) associated with papillary thyroid cancer (PTC) located in the isthmus are debatable. We aimed to analyze the pattern of occult central LNM in isthmic PTC, including risk factors for bilateral paratracheal LNM.Patients and MethodsConsecutive patients with PTC were recruited to this study. All patients underwent total thyroidectomy and prophylactic bilateral central neck dissection. The clinicopathologic features and distribution of central LNM were compared between the two groups, and risk factors for bilateral paratracheal LNM were analyzed.ResultsA total of 174 patients with PTC were enrolled in this study, of whom 87 patients had isthmic PTC (study group) and 87 patients had lobe-originating PTC (control group). The two groups had comparable demographics and tumor features. There were higher frequencies of pretracheal LNM (P =0.001) and bilateral paratracheal LNM (P = 0.002) in the isthmic PTC group. Bilateral paratracheal LNM was significantly associated with age <55 years (P = 0.037), capsular invasion (P = 0.034), tumor location (isthmus) (P < 0.001), BRAF gene mutation (P = 0.013), and pretracheal LNM (P < 0.001). Isthmus location (odds ratio [OR]: 4.116, 95% confidence interval [CI]: 1.264–13.433, P = 0.019) and pretracheal LNM (OR: 3.422, 95% CI: 1.214–9.642, P = 0.020) were independent risk factors for bilateral paratracheal LNM.ConclusionBecause of its unique anatomic location, isthmic PTC differs from PTC in the lobe with respect to pretracheal and bilateral paratracheal LNM, even in patients of comparable age, sex, tumor size, extrathyroidal extension, BRAF mutation, and pathologic TNM staging. The isthmus location was found to be an independent risk factor for bilateral paratracheal LNM. This information may contribute to the development of an appropriate surgical protocol for isthmic PTC.
| S-EPMC7245435 | biostudies-literature