Development and validation of a nomogram to predict cancer-specific survival in middle-aged patients with papillary thyroid cancer: A SEER database study

A new Tec family-based clinical model predicts survival in differentiated thyroid cancer patients via machine learning

BACKGROUND

The Tec family of proteins has been identified as a key player in numerous diseases. However, no studies on the associations of Tec family proteins with overall survival (OS) in differentiated thyroid cancer (DTC) patients have been conducted.

METHODS

RNA sequencing (RNA-Seq) and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. LASSO-Cox, random forest, and eXtreme Gradient Boosting (XGBoost) analysis methods were used to screen for the genes encoding Tec family proteins that were most closely associated with DTC. A predictive model was developed to estimate the OS of DTC patients. The validity of the prediction model was evaluated via receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and fivefold and 200-fold cross-validation. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to investigate the biological functions of the most significant genes.

RESULTS

The AC007494.3 and AC019226.2 genes were most strongly associated with the OS of DTC patients. Therefore, the model can be used to predict the OS of DTC patients. Functional annotation analysis revealed characteristics similar to those of other Tec kinases.

CONCLUSIONS

We found that the TEC gene has significant predictive value for the prognosis of DTC patients. The TEC gene has potential value as a target for future drug development. In addition, we recommend more comprehensive treatment and closer monitoring of high-risk populations.

The influence of cancer on the reprogramming of lipid metabolism in healthy thyroid tissues of patients with papillary thyroid carcinoma

BACKGROUND AND OBJECTIVES

Over the years we observed changes in the metabolism of glucose, amino acids, fatty acids (FA) and nucleotides in cancer cells in order to maintain their viability and proliferate. Moreover, as the latest data show, cancer also forces a complete change in the behavior of other tissues. For instance, fat-filled adipocytes are often found in the vicinity of invasive solid human tumors. We investigated the effects of papillary thyroid carcinoma (PTC) on the lipid metabolism of healthy tissue distant from the tumor.

METHOD

Thyroid tissue was collected from female patients immediately after surgical removal of the entire thyroid gland. Blood samples were collected from PTC patients and healthy volunteers. Real-time PCR assays were performed to analyze the expression of lipogenic genes and a broad panel of FA was determined using the gas chromatography-mass spectrometry method.

RESULTS

The concentration of lipids was higher in paratumor tissue than in healthy thyroid tissue (p = 0.005). The lipogenic genes tested were significantly increased in paratumor tissue compared to healthy tissue, especially enzymes related to the synthesis of very long-chain saturated and polyunsaturated FAs (VLCSFAs and PUFAs, respectively) (p < 0.001). The FA profile also showed increased levels of C22-C26, VLCSFAs and almost all PUFAs in paratumor tissue (p < 0.05).

CONCLUSION

Our study suggests that a restructuring of lipid metabolism occurs in the adjacent healthy thyroid gland and that the metabolism of VLCSFAs and PUFAs is higher in the paratumor tissue than in the distant tissue of the healthy thyroid gland.

Long-term survival outcomes of systemic therapy in patients with isolated and mixed medullary thyroid cancer

Background

Medullary thyroid carcinoma (MTC) is an uncommon thyroid cancer with limited treatment options for advanced disease. A small subset exhibits mixed MTC histology with both medullary and well-differentiated components. We investigated survival outcomes with systemic therapy in isolated versus mixed MTC using a large population-based cohort.

Methods

Patients diagnosed with MTC from 2000 to 2019 were identified in the National Cancer Institute's Surveillance, Epidemiology, and End Results database. The overall and thyroid cancer-specific survivals were compared between isolated (n = 1814) and mixed (n = 113) MTC cohorts. The impact of postoperative systemic therapy on survival was analyzed.

Results

No significant difference in 10-year overall survival was observed between isolated (77.4 %) and mixed (75.2 %) MTC in a cohort of 1927 patients. Median overall survival was similar between isolated (136.9 months) and mixed MTC (129.0 months), p = 0.81. While systemic therapy improved 10-year survival in isolated MTC (83.2 % vs. 76.9 %, p < 0.001), no benefit was seen in mixed MTC (76.4 % vs. 74.2 %, p = 0.82). Multivariate analysis confirmed survival gains with systemic therapy for isolated (HR = 0.763, 95%CI = 0.590-0.987, p = 0.040) but not mixed MTC (HR = 0.909, 95%CI = 0.268-3.079, p = 0.88).

Conclusions

In this large population-based study, no significant survival difference was observed between isolated and mixed MTC. Systemic therapy was associated with improved survival in isolated MTC, but not in the mixed subtype. These findings suggest a differential treatment response that warrants further investigation in prospective studies and may inform histology-tailored management strategies for mixed MTC.

Nomogram for predicting the risk of central lymph node metastasis in papillary thyroid microcarcinoma: a combination of sonographic findings and clinical factors

Background

A considerable controversy over performing thyroidectomy and central lymph node dissection in patients with papillary thyroid microcarcinoma (PTMC) remained. However, accurate prediction of central lymph node metastasis (CLNM) is crucial for surgical extent and proper management. The aim of this study was to develop and validate a practical nomogram for predicting CLNM in patients with PTMC.

Methods

A total of 1,029 patients with PTMC who underwent thyroidectomy and central lymph node dissection at Tangdu Hospital (the Second Affiliated Hospital of Air Force Medical University) and Xijing Hospital (the First Affiliated Hospital of Air Force Medical University) were selected. Seven hundred and nine patients were assigned to the training set and 320 patients to the validation set. Data encompassing demographic characteristics, ultrasonography results, and biochemical indicators were obtained. Stepwise backward selection and multiple logistic regression were used to screen the variables and establish the nomogram. Concordance index (C-index), receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA) were employed to evaluate the nomogram's distinguishability, accuracy, and clinical utility.

Results

Young age, multifocality, bigger tumor, presence of microcalcification, aspect ratio (height divided by width) ≥1, loss of fatty hilum, high free thyroxine (FT4), and lower anti-thyroid peroxidase antibody (TPOAb) were significantly associated with CLNM. The nomogram showed strong predictive capacity, with a C-index and accuracy of 0.784 and 0.713 in the training set and 0.779 and 0.703 in the external validation set, respectively. DCA indicated that the nomogram demonstrated strong clinical applicability.

Conclusions

We established a reliable, cost-effective, reproducible, and noninvasive nomogram for predicting CLNM in patients with PTMC. This tool could be a valuable guidance for deciding on management in PTMC.

The Role of Lipid Metabolism Disorders in the Development of Thyroid Cancer

Thyroid cancer (TC) is a neoplasm with an increasing incidence worldwide. Its etiology is complex and based on a multi-layered interplay of factors. Among these, disorders of lipid metabolism have emerged as an important area of investigation. Cancer cells are metabolically reprogrammed to promote their rapid growth, proliferation, and survival. This reprogramming is associated with significant changes at the level of lipids, mainly fatty acids (FA), as they play a critical role in maintaining cell structure, facilitating signaling pathways, and providing energy. These lipid-related changes help cancer cells meet the increased demands of continued growth and division while adapting to the tumor microenvironment. In this review, we examine lipid metabolism at different stages, including synthesis, transport, and oxidation, in the context of TC and the effects of obesity and hormones on TC development. Recent scientific efforts have revealed disturbances in lipid homeostasis that are specific to thyroid cancer, opening up potential avenues for early detection and targeted therapeutic interventions. Understanding the intricate metabolic pathways involved in FA metabolism may provide insights into potential interventions to prevent cancer progression and mitigate its effects on surrounding tissues.

Enhancing clinical decision-making: A novel nomogram for stratifying cancer-specific survival in middle-aged individuals with follicular thyroid carcinoma utilizing SEER data

Background

Thyroid cancer (TC) is the most common malignant tumor in the endocrine system, is also one of the head and neck tumor. Follicular Thyroid Carcinoma (FTC) plays an important role in the pathological classification of thyroid cancer. This study aimed to develop an innovative predictive tool, a nomogram, for predicting cancer specific survival (CSS) in middle-aged FTC patients.

Methods

We collected patient data from the Surveillance, Epidemiology, and End Results (SEER) database. The data from patients between 2004 and 2015 were used as the training set, and the data from patients between 2016 and 2018 were used as the validation set. To identify independent risk factors affecting patient survival, univariate and multivariate Cox regression analyses were performed. Based on this, we developed a nomogram model aimed at predicting CSS in middle-aged patients with FTC. The consistency index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and the calibration curve were used to evaluate the accuracy and confidence of the model.

Results

A total of 2470 patients were enrolled in this study, in which patients from 2004 to 2015 were randomly assigned to the training cohort (N = 1437) and validation cohort (N = 598), and patients from 2016 to 2018 were assigned to the external validation cohort (N = 435) in terms of time. Univariate and multivariate Cox regression analysis showed that marriage, histological grade and TNM stage were independent risk factors for survival. The C-index for the training cohort was 0.866 (95 % CI: 0.805-0.927), for the validation cohort it was 0.944 (95 % CI: 0.903-0.985), and for the external validation cohort, it reached 0.999 (95 % CI: 0.997-1.001). Calibration curves and AUC suggest that the model has good accuracy.

Conclusions

We developed an innovative nomogram to predict CSS in middle-aged patients with FTC. Our model after a rigorous internal validation and external validation process, based on the time proved that the high level of accuracy and reliability. This tool helps healthcare professionals and patients make informed clinical decisions.

Development of a predictive nomogram for intermediate-risk differentiated thyroid cancer patients after fixed 3.7GBq (100mCi) radioiodine remnant ablation

Objectives

The objective of this study was to develop a predictive nomogram for intermediate-risk differentiated thyroid cancer (DTC) patients after fixed 3.7GBq (100mCi) radioiodine remnant ablation (RRA).

Methods

Data from 265 patients who underwent total thyroidectomy with central lymph node dissection (CND) and received RRA treatment at a single institution between January 2018 and March 2023 were analyzed. Patients with certain exclusion criteria were excluded. Univariate and multivariate logistic regression analyses were performed to identify risk factors for a non-excellent response (non-ER) to RRA. A nomogram was developed based on the risk factors, and its performance was validated using the Bootstrap method with 1,000 resamplings. A web-based dynamic calculator was developed for convenient application of the nomogram.

Results

The study included 265 patients with intermediate-risk DTC. Significant differences were found between the ER group and the non-ER group in terms of CLNM>5, Hashimoto's thyroiditis, sTg level, TgAb level (P < 0.05). CLNM>5 and sTg level were identified as independent risk factors for non-ER in multivariate analysis. The nomogram showed high accuracy, with an area under the curve (AUC) of 0.833 (95% CI = 0.770-0.895). The nomogram's predicted probabilities aligned closely with actual clinical outcomes.

Conclusions

This study developed a predictive nomogram for intermediate-risk DTC patients after fixed 3.7GBq (100mCi) RRA. The nomogram incorporates CLNM>5 and sTg levels as risk factors for a non-ER response to RRA. The nomogram and web-based calculator can assist in treatment decision-making and improve the precision of prognosis information. Further research and validation are needed.

Establishment and verification of the first prognostic nomograms in locally advanced thyroid cancer based on the analysis of clinical and follow-up information on 2396 patients

Background and objectives

The purpose of this research was to develop and validate the first prognostic nomograms for 3-, 5-, and 10-year cancer-specific survival (CSS) and overall survival (OS) in patients diagnosed with locally advanced thyroid cancer (LATC) by evaluating independent predictors of prognosis in a population of LATC patients.

Methods

Demographics, clinicopathologic characteristics, treatment, and follow-up of 2396 LATC patients in the surveillance, epidemiology, and end results database from 2004 to 2015 were retrospectively analyzed and compared with patients with LATC according to staging. We randomized all LATC patients into training and validation groups in a 7:3 ratio. Cox regression analyses helped us to derive independent prognostic factors for LATC patients. According to these results, we established and validated the first prognostic nomograms and risk stratification.

Results

In our research, the clinical information of LATC patients was compared and significant differences were found in the relevant variables including CSS and OS (P < 0.05), with CSS of 82.0 % and 49.0 %, and OS of 70.6 % and 40.0 %, respectively. Cox regression analyses showed that age at diagnosis, tumor diameter, presence of DM, extrathyroidal extension sites, histological type, thyroidectomy scope, radiotherapy status, and chronological sequence of radiotherapy and surgery were observably correlated with CSS in LATC patients, and in addition to the above factors, gender, marital status, and chemotherapy status were also observably correlated with OS in LATC patients. The prognostic predictive power of the above factors is visualized by the Kaplan-Meier survival curve. The concordance index of nomograms for CSS and OS were 0.933, 0.925, and 0.926 (CSS), 0.918, 0.909, and 0.906 (OS), respectively, and the time-dependent receiver operating characteristic curve, area under curve, calibration curve and decision curve analysis curve indicate that the nomograms have good discriminatory ability, accuracy and clinical applicability in both the training and validation groups.

Conclusions

In these findings, we drawed a conclusion that there were significant differences in clinical information between patients with T4a and T4b LATC, and we established and validated the first prognostic nomograms and risk stratification of CSS and OS for LATC patients at 3, 5, and 10 years, which will help clinicians to individualize their postoperative treatment and individualized follow-up.