Prognosis Of Thyroid Cancer Research Articles

A novel signature to predict thyroid cancer prognosis and immune landscape using immune-related LncRNA pairs

BackgroundThyroid cancer (TC) is the most common endocrine malignancy worldwide. The incidence of TC is high and increasing worldwide due to continuous improvements in diagnostic technology. Therefore, identifying accurate prognostic predictions to stratify TC patients is important.MethodsRaw data were downloaded from the TCGA database, and pairwise comparisons were applied to identify differentially expressed immune-related lncRNA (DEirlncRNA) pairs. Then, we used univariate Cox regression analysis and a modified Lasso algorithm on these pairs to construct a risk assessment model for TC. We further used qRT‒PCR analysis to validate the expression levels of irlncRNAs in the model. Next, TC patients were assigned to high- and low-risk groups based on the optimal cutoff score of the model for the 1-year ROC curve. We evaluated the signature in terms of prognostic independence, predictive value, immune cell infiltration, immune status, ICI-related molecules, and small-molecule inhibitor efficacy.ResultsWe identified 14 DEirlncRNA pairs as the novel predictive signature. In addition, the qRT‒PCR results were consistent with the bioinformatics results obtained from the TCGA dataset. The high-risk group had a significantly poorer prognosis than the low-risk group. Cox regression analysis revealed that this immune-related signature could predict prognosis independently and reliably for TC. With the CIBERSORT algorithm, we found an association between the signature and immune cell infiltration. Additionally, immune status was significantly higher in low-risk groups. Several immune checkpoint inhibitor (ICI)-related molecules, such as PD-1 and PD-L1, showed a negative correlation with the high-risk group. We further discovered that our new signature was correlated with the clinical response to small-molecule inhibitors, such as sunitinib.ConclusionsWe have constructed a prognostic immune-related lncRNA signature that can predict TC patient survival without considering the technical bias of different platforms, and this signature also sheds light on TC’s overall prognosis and novel clinical treatments, such as ICB therapy and small molecular inhibitors.

Epithelial-to-mesenchymal transition of circulating tumor cells and CD133 expression on predicting prognosis of thyroid cancer patients.

The present study aimed to explore the epithelial-to-mesenchymal transition of circulating tumor cells (CTCs) and CD133 expression in determining the prognosis of patients with thyroid cancer. It enumerated different CTC subtypes and analyzed CD133 gene expression in patients with thyroid cancer to evaluate the relationship between CTC number and thyroid cancer prognosis. In total 394 patients with thyroid cancer were enrolled. Among these, 270 cases had papillary thyroid cancer (PTC), 60 had follicular thyroid cancer (FTC), 30 had medullary thyroid cancer (MTC), 15 had poorly differentiated thyroid cancer, 19 had anaplastic thyroid cancer and 10 had non-malignant thyroid nodules based on their histopathological characteristics. CTC cell counts were determined by CanPatrol CTC capture technique before treatment. The present study also performed reverse transcription-quantitative PCR for CD133 gene expression and evaluated the relationship between CD133 expression and clinical pathology. A total of 330 cases of enrolled patients were classified as differentiated thyroid cancer, which included PTC and FTC. Their prognosis was excellent. The positivity rate of CTCs at diagnosis was 95.5%. The data of the present study showed that early recurrence and metastasis rates in PTC and FTC patients with >6 CTCs and positive mesenchymal circulating tumor cells (MCTCs) were significantly higher than those in patients with <6 CTCs and MCTCs. It was also found that those patients with >6 CTCs and MCTCs had shorter overall survival. In addition, CD133 levels in patients with thyroid cancer were strongly associated with the differentiation grades of thyroid cancers. The detection of >6 CTCs and positive MCTCs in patients with differentiated thyroid cancer was an excellent biomarker for predicting the prognosis of patients. CD133 expression was also identified as a good biomarker for thyroid cancer differentiation.

Metformin and thyroid carcinoma incidence and prognosis: A systematic review and meta-analysis.

Metformin has been suggested to reduce thyroid cancer incidence and to improve thyroid cancer prognosis. We aimed to evaluate the associations between metformin and thyroid cancer incidence and prognosis (metastasis/recurrence/progression-free survival). Cochrane Library, PubMed, ClinicalTrials.gov, and U.S. National Library of Medicine Clinical Trials were searched through the end of December 2021. Data were collected from original observational studies or clinical trials on the incidence or prognosis of thyroid carcinoma outcomes in type 2 diabetes mellitus (T2DM) patients with and without metformin use. Risk of bias in non-randomized studies of interventions (ROBINS-I) tool and Grading of Recommendations, and Assessment, Development and Evaluations (GRADE) approach were used to evaluate the risk of bias and quality of the body of evidence, respectively. In general, 4 studies were related to the thyroid cancer incidence, including 1,705,123 participants metformin users and non-users and yielding a total of 3,238 thyroid cancer events; 3 studies reported the prognosis of thyroid carcinoma based on a total of 4,972 individuals with primary thyroid carcinoma and comorbid type 2 diabetes, and the number of thyroid cancer prognosis cases ranged from 3 to 79. The overall risk of bias of the included studies ranged from moderate to serious. In the random-effects model, the summary relative risk (SRR) for thyroid cancer incidence was 0.743 (95% CI: 0.453–1.220; I2 = 88.7%, low certainty) comparing metformin users to non-users; and SRR for the prognosis of thyroid cancer was 0.504 (95% CI: 0.178–1.430; I2 = 57.5%, low certainty). Non-statistically significant negative associations between metformin use and incidence and prognosis of thyroid cancer were found in the current analysis, although the quantity and quality of the evidence were limited. Futher investigation is needed to evaluate the clinical benefits of metformin on thyroid cancer prevention and treatments.

Elevated LINC00894 relieves the oncogenic properties of thyroid cancer cell by sponging let-7e-5p to promote TIA-1 expression

LINC00894 plays an important role in cancer cell proliferation and invasion in breast and kidney cancer. However, its role in thyroid cancer proliferation and metastasis remains unclear. In this study, data on LINC00894 expression in thyroid cancer tissues were obtained from GEPIA2. miRNA expression in thyroid cancer tissues was obtained from starBase 3.0 and OncomiR. Cell proliferation was evaluated using CCK-8, and Transwell chambers were used for the migration and invasion assays. LINC00894 and let-7e-5p expressions in thyroid cancer cells were measured using qRT–PCR. Meanwhile, TIA-1 expression in thyroid cancer cells was analyzed via western blotting. We found that LINC00894 expression was markedly reduced in thyroid cancer tissues and cells, and low expression of LINC00894 was associated with poor prognosis in thyroid cancer. LINC00894 overexpression inhibited the proliferation, migration, and invasion of CAL-62 and TPC-1 cells. Additionally, let-7e-5p expression was substantially enhanced in CAL-62 and TPC-1 cells. LINC00894 overexpression promoted TIA-1 expression by acting as a sponge of let-7e-5p. Finally, let-7e-5p weakened the function of LINC00894 in thyroid cancer cells via reduction in TIA-1 levels. In conclusion, our data suggest that increased LINC00894 expression reduces the oncogenic properties of thyroid cancer cells by sponging let-7e-5p to promote TIA-1 expression.

Epidemiology of Thyroid Cancer.

Epidemiology of Thyroid Cancer.

Surgical Methods and Social Factors Are Associated With Long-Term Survival in Follicular Thyroid Carcinoma: Construction and Validation of a Prognostic Model Based on Machine Learning Algorithms.

BackgroundThis study aimed to establish and verify an effective machine learning (ML) model to predict the prognosis of follicular thyroid cancer (FTC), and compare it with the eighth edition of the American Joint Committee on Cancer (AJCC) model.MethodsKaplan-Meier method and Cox regression model were used to analyze the risk factors of cancer-specific survival (CSS). Propensity-score matching (PSM) was used to adjust the confounding factors of different surgeries. Nine different ML algorithms,including eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Random Forests (RF), Logistic Regression (LR), Adaptive Boosting (AdaBoost), Gaussian Naive Bayes (GaussianNB), K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP),were used to build prognostic models of FTC.10-fold cross-validation and SHapley Additive exPlanations were used to train and visualize the optimal ML model.The AJCC model was built by multivariate Cox regression and visualized through nomogram. The performance of the XGBoost model and AJCC model was mainly assessed using the area under the receiver operating characteristic (AUROC).ResultsMultivariate Cox regression showed that age, surgical methods, marital status, T classification, N classification and M classification were independent risk factors of CSS. Among different surgeries, the prognosis of one-sided thyroid lobectomy plus isthmectomy (LO plus IO) was the best, followed by total thyroidectomy (hazard ratios: One-sided thyroid LO plus IO, 0.086[95% confidence interval (CI),0.025-0.290], P<0.001; total thyroidectomy (TT), 0.490[95%CI,0.295-0.814], P=0.006). PSM analysis proved that one-sided thyroid LO plus IO, TT, and partial thyroidectomy had no significant differences in long-term prognosis. Our study also revealed that married patients had better prognosis than single, widowed and separated patients (hazard ratios: single, 1.686[95%CI,1.146-2.479], P=0.008; widowed, 1.671[95%CI,1.163-2.402], P=0.006; separated, 4.306[95%CI,2.039-9.093], P<0.001). Among different ML algorithms, the XGBoost model had the best performance, followed by Gaussian NB, RF, LR, MLP, LightGBM, AdaBoost, KNN and SVM. In predicting FTC prognosis, the predictive performance of the XGBoost model was relatively better than the AJCC model (AUROC: 0.886 vs. 0.814).ConclusionFor high-risk groups, effective surgical methods and well marital status can improve the prognosis of FTC. Compared with the traditional AJCC model, the XGBoost model has relatively better prediction accuracy and clinical usage.

Abstract 767: Role of COL26A1 in papillary thyroid cancer invasion

Abstract Papillary thyroid cancer (PTC) accounts for 70-80% of all thyroid cancer cases and has been increasing in incidence over the last few decades. It is now the 8th most common cancer in women in the United States and the most common cancer in women under 25 years of age. PTC is often curable, as the tumors are most often slow-growing and surgically resectable and lymphatic spread does not worsen the generally favorable prognosis. However, there are aggressive forms of PTC that are not adequately treated by current therapeutic modalities and invasion into surrounding tissue next to the thyroid worsens the prognosis. Utilizing the NYMC biobank of PTC patient samples, meta-analysis of RNASeq data was performed, ranking differentially expressed genes between invasive vs noninvasive and lymph node positive vs lymph node negative samples. These genes were analyzed in conjunction with the GDC’s The Cancer Genome Atlas (TCGA) Thyroid Cancer (THCA) study, in which the Kaplan Meier survival curve identified genes with a significant impact on survival and those that were increased in metastatic tissue samples. Of the top differentially expressed genes that were increased in patients with extrathyroidal extension and lymph node metastasis, COL26A1 significantly inversely associated with survival (p = 0.0086). COL26A1 codes for collagen type XXVI α1 chain with known roles in degradation of the ECM and collagen chain trimerization. In TCGA datasets, COL26A1 expression was significantly correlated with clinical attributes including MACIS score (q = .001), differentiation score (q = 0.025), and tumor stage (q = 0.025). COL26A1 expression was increased 3-fold in papillary thyroid cancer cell line K1 when compared to normal thyroid cancer cells, NThy-ori 3-1. Two CRISPR guides designed to target COL26A1 were introduced into K1 resulting in repression of COL26A1 by 50% in both knockdowns. COL26A1 repression decreased the proliferation (33%), tumorigenicity (86%), invasion (33%), and migration capacity (73%). Furthermore, knockdown of COL26A1 leads to decreased cell-to-cell adhesion in culture. Thus, COL26A1 may have potential use as a prognostic marker and actionable therapeutic target for small molecule inhibitors. Long noncoding RNAs (lncRNAs) have vast implications in different cancer types with roles in gene expression via modulation of coding and noncoding RNAs. lncRNAs are tissue- and stage- specific and stable in serum alluding to their ability to be used in thyroid cancer prognosis and diagnosis. Therefore, we investigated the mRNA-miRNA-lncRNA axis involved in regulation of COL26A1 utilizing Qiagen Ingenuity Pathway Analysis (IPA). We have identified potential pathways linking COL26A1 with PTC, highlighting those involved in proliferation, migration, invasion, and adhesion. Investigation into these molecular interactions and pathways can elucidate the role of COL26A1 and allow for its optimal targeting for treatment of invasive papillary thyroid cancer. Citation Format: Michelle Carnazza, Danielle Quaranto, Nicole DeSouza, Sina Dadafarin, Augustine Moscatello, Raj K. Tiwari, Jan Geliebter. Role of COL26A1 in papillary thyroid cancer invasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 767.

Current status and temporal trend of disease burden of thyroid cancer in China from 1990 to 2019.

Thyroid cancer has been an increasingly high-profile public health issue. Comprehensive assessment for its disease burden seems particularly important for understanding health priorities and hinting high-risk populations. We estimated the age-sex-specific thyroid cancer burden and its temporal trend in China from 1990 to 2019 by following the general methods from the global burden of disease (GBDs) 2019 Study. And Joinpoint regression model, the Cox-Stuart trend test, and Cochran-Armitage test were applied for the analysis of temporal and age trend. The Mantel-Haenszel statistical method was used to compare the gender difference. From 1990 to 2019, the age-standardized incidence rate of thyroid cancer in China has almost doubled to 2.05 per 100,000. Although the mortality rate and DALY rate kept leveling off, they presented a downtrend among females, while an upward trend in males. While the average annual percentage changes of those metrics all became deline since 2010 than the previous years. With age advancing, the rates of incidence, mortality, and DALYs for both sexes all presented linear fashion increases, which was particularly typical among males. Given the serious trend and gender-age heterogeneity of Chinese thyroid cancer burden, male gender and advanced age may be related to poor prognosis of thyroid cancer, and strengthening primary prevention and exploring the underlying risk factors should be among the top priorities.

Machine learning reveals salivary glycopatterns as potential biomarkers for the diagnosis and prognosis of papillary thyroid cancer

The diagnosis of thyroid cancer, especially papillary thyroid cancer (PTC), is increasing rapidly worldwide. In this study, we aimed to study the glycosylation of salivary proteins associated with PTC and assess the likelihood that salivary glycopatterns may be a potential biomarker of PTC diagnosis. Firstly, 22 benign thyroid nodule (BTN) samples, 27 PTC samples, and 30 healthy volunteers (HV) samples were collected to probe the difference of salivary glycopatterns associated with PTC using lectin microarrays. Then, five machine learning models including K-Nearest Neighbor (KNN), Multilayer Perceptron (MLP), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) were established to distinguish HV, BTN and PTC based on the changes of salivary glycopatterns. As a result, SVM had the best diagnostic effect with an accuracy rate of 92 % in testing set. Besides, lectin microarrays were used to explore the differences in salivary glycopatterns of 26 paired salivary samples of PTC patients before and after operation in order to probe into salivary glycopatterns as potential biomarkers for prognosis of PTC patients. The results showed that the levels of salivary glycopatterns recognized by 6 different lectins in patients after the operation almost convergenced with HVs. This study could help to screen and assess patients with PTC and their prognosis based on precise changes of salivary glycopatterns.

Identification of Three Prognosis-Related Differentially Expressed lncRNAs Driven by Copy Number Variation in Thyroid Cancer.

Thyroid cancer as the malignant tumor with the highest incidence in the endocrine system also shows a fast growth and development. In this work, we developed a new method to identify copy number variation– (CNV–) driven differentially expressed lncRNAs in thyroid cancer for predicting cancer prognosis. The data of RNA sequencing, CNV, methylation, mutation, and clinical details of thyroid cancer were obtained from the Cancer Genome Atlas database (TCGA). Molecular subtypes were clustered by iClusterPlus. Weighted gene co-expression network analysis (WGCNA) was employed to show co-expression modules. DEseq2 was conducted to identify protein coding genes (PCGs) and differentially expressed lncRNAs. CNV was detected using GISTIC 2.0. Three molecular subtypes were identified, and 68 differentially expressed lncRNAs (DElncRNAs) related to cancer were found among different molecular subtypes. CNV of FOXD2-AS1, FAM181A-AS1, and RNF157-AS1 was associated with overall survival and was involved in cancer-related pathways. These three DElncRNAs discovered based on CNV could serve as prognostic biomarkers to predict prognosis for thyroid cancer and new targets to explore molecular drugs.

Survival and Prognosis of Anaplastic Thyroid Cancer: A 15-year Observation at a Single Asian Institute

Survival and Prognosis of Anaplastic Thyroid Cancer: A 15-year Observation at a Single Asian Institute

Looking at Thyroid Cancer from the Tumor-Suppressor Genes Point of View.

Simple SummaryThyroid cancer is the most common endocrine cancer. As tumor-suppressor genes (TSGs) are implicated in many different functions in the organism, their loss in cells in a normal tissue may drive their transformation into cancer cells. TSGs are generally classified into three subclasses: (i) gatekeepers that encode proteins involved in the control of cell cycle and apoptosis; (ii) caretakers that produce proteins implicated in maintaining genomic stability; and (iii) landscapers that, when mutated, create a suitable environment for neoplastic growth. Different inactivation mechanisms may suppress TSG function. Understanding these mechanisms and TSG alterations in thyroid tumors is of great importance for thyroid cancer prognosis, diagnosis, and therapy. The present review paper discusses TSG inactivation mechanisms and alterations in order to help to identify more efficient therapeutic modalities for thyroid cancer management.Thyroid cancer is the most frequent endocrine malignancy and accounts for approximately 1% of all diagnosed cancers. A variety of mechanisms are involved in the transformation of a normal tissue into a malignant one. Loss of tumor-suppressor gene (TSG) function is one of these mechanisms. The normal functions of TSGs include cell proliferation and differentiation control, genomic integrity maintenance, DNA damage repair, and signaling pathway regulation. TSGs are generally classified into three subclasses: (i) gatekeepers that encode proteins involved in cell cycle and apoptosis control; (ii) caretakers that produce proteins implicated in the genomic stability maintenance; and (iii) landscapers that, when mutated, create a suitable environment for malignant cell growth. Several possible mechanisms have been implicated in TSG inactivation. Reviewing the various TSG alteration types detected in thyroid cancers may help researchers to better understand the TSG defects implicated in the development/progression of this cancer type and to find potential targets for prognostic, predictive, diagnostic, and therapeutic purposes. Hence, the main purposes of this review article are to describe the various TSG inactivation mechanisms and alterations in human thyroid cancer, and the current therapeutic options for targeting TSGs in thyroid cancer.

Management and prognosis of anaplastic thyroid cancer

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

Male gender is independent factor of poor prognosis in medullary thyroid cancer

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

Development of a Colloidal Gold Immunochromatographic Strip for Rapid Detection of Cyfra 21-1 in Lymph Node Metastasis of Thyroid Cancer.

Thyroid cancer is the most common endocrine tumor, and the rate of early lymph node metastasis may be as high as 60%. Currently, detection of lymph node metastasis of thyroid cancer during surgery is limited and time-consuming. Elevated levels of Cyfra 21-1, the proteolytic portion of cytokeratin, are associated with the metastasis and progression of thyroid cancer and are an effective biomarker for the prognosis and diagnosis of thyroid cancer. In this study, an immunochromatographic strip test based on colloidal gold nanoparticles was developed to semi-quantitatively detect the levels of Cyfra 21-1 in lymph nodes within 15 min. The standard (calibration) curve equation was Y = 0.003708 × X + 0.1101, and the detection limit was 0.55–1.14 ng mL−1. The strip did not detect other protein markers of epithelial cells at a concentration of 500 ng mL−1, including cytokeratin 8, cytokeratin 18, epithelial membrane antigen, and epidermal surface antigen. The ability of the strip to differentiate positive from negative metastasis in 40 lymph node specimens was 100% concordant with that of immunohistochemical staining for Cyfra 21-1. In an assessment of 20 lymph node specimens that had been determined by postoperative histopathology to be positive for lymph node metastasis and 20 specimens that were negative, the sensitivity and specificity of the strip were 100% and 95%, respectively. The sensitivity of the strip remained stable when stored at room temperature for 6 months. Together, these results indicated that although further testing using a larger sample size will be required, this immunochromatographic strip test may be useful for rapid intraoperative detection of thyroid cancer metastasis to lymph nodes.

A diagnostic and predictive lncRNA lnc-MPEG1-1 promotes the proliferation and metastasis of papillary thyroid cancer cells by occupying miR-766-5p

Long non-coding RNAs (lncRNAs) act as important biological regulators in human cancers. The purpose of this study was to identify promising biomarkers for improved diagnosis and prognosis of papillary thyroid cancer (PTC). We analyzed the lncRNA expression profile of PTC patients and identified five upregulated and three downregulated lncRNAs as diagnostic biomarkers for PTC in our cohorts, which were confirmed using The Cancer Genome Atlas (TCGA) data. Several lncRNAs have been linked with lymph node (LN) metastasis in patients with PTC. A nomogram combining two lncRNAs, lnc-MPEG1-1:1 and lnc-ABCA12-5:2, with age, T stage, histological type, and predicted LN metastasis was developed. The area under the curve of the developed nomogram was 0.77 (0.73–0.81) in the TCGA training cohort and 0.88 (0.79–0.96) in our validation cohort. In particular, in vivo and in vitro experiments showed that overexpression of lnc-MPEG1-1:1 in PTC cell lines promoted the proliferation and migration of PTC. lnc-MPEG1-1:1 is overexpressed in the cytoplasm of PTC cells and functionally promotes cellular proliferation and migration and functions as a competitive endogenous RNA (ceRNA) by competitively occupying the shared binding sequences of miR-766-5p. lnc-MPEG1-1:1 knockdown suppressed epithelial-mesenchymal transition by miR-766-5p in PTC cells. Collectively, these results revealed a lnc-MPEG1-1:1/miR-766-5p pathway for thyroid cancer progression and suggest that a nomogram effectively predicted the LN metastasis in PTC.

Differentiated Thyroid Cancer Genetic Mechanisms - Focus on Vitamin D Receptor and Methylenetetrahydrofolate Reductase Gene Polymorphisms

Thyroid cancer is the most frequent endocrine cancer representing 1-1.5% of all cancers. Approximately 90% of these are differentiated thyroid carcinomas (DTC) with a favorable prognosis and cure rate. DTC has recently witnessed an increase in incidence with a relatively stable mortality rate, mostly due to intensive screening. Despite being considered indolent and the 10-year survival rate being above 90%, local or distant recurrence can be observed in up to 20% of cases. Mutations in BRAF, RET, RAS, NTRK1, PAX8-PPARG are commonly found in DTC but studies show that genetic alterations with apparently no correlation to DTC might improve or aggravate prognosis. Vitamin D deficiency and vitamin D receptor (VDR) gene polymorphisms is consider to be one of these factors, due to the fact that it exerts immunological and antineoplastic functions throught its antiproliferative and prodifferentiating actions. FokI gene polymorphism has been associated with later stage and negative prognosis in different studies. Also, polymorphisms of genes involved in folate metabolism (MTHFR, MTR, RFC1) may be incriminated in carcinogenesis, folate being an extremely important factor in DNA synthesis. Studies suggest that through correction and avoidance of incriminated neoplastic agents, thyroid cancer incidence, evolution and prognosis might improve significantly. For this to be possible we need to be aware of the molecular pathways these environmental factors use to exert their carcinogenic effects.

The Effect of Molecular Markers in Advanced Thyroid Cancers

Molecular markers play an important role in the diagnosis, prognosis and treatment of thyroid cancers, as in many types of cancer.&#x0D; Our aim in this study is to investigate the effect of molecular markers in the follow-up and treatment of advanced thyroid cancers.&#x0D; For this purpose, the results obtained in recent articles investigating molecular markers in the follow-up and treatment of advanced thyroid cancers were evaluated and new findings were presented. The databases from which the references are obtained are Google Scholar, Scopus, Pubmed, Web of Science.&#x0D; According to the results of our study, molecular markers have very important effects in the treatment of advanced thyroid cancers. It can already be said that future studies on this subject will further increase the treatment possibilities and prolong survival in advanced thyroid cancers.

Sarcopenia increases the risk of major organ or vessel invasion in patients with papillary thyroid cancer

While sarcopenia is associated with poor overall survival and cancer-specific survival in solid cancer patients, the impact of sarcopenia on clinicopathologic features that can influence conventional papillary thyroid cancer (PTC) prognosis remains unclear. To investigate the impact of sarcopenia on aggressive clinicopathologic features in PTC patients, prospectively collected data on 305 patients who underwent surgery for PTC with preoperative staging ultrasonography and bioelectrical impedance analysis were retrospectively analyzed. Nine sarcopenia patients with preoperative sarcopenia showed more patients aged 55 or older (p = 0.022), higher male proportion (p < 0.001), lower body-mass index (p = 0.015), higher incidence of major organ or vessel invasion (p = 0.001), higher T stage (p = 0.002), higher TNM stage (p = 0.007), and more tumor recurrence (p = 0.023) compared to the non-sarcopenia patients. Unadjusted and adjusted logistic regression analyses showed that sarcopenia (odds ratio (OR) 9.936, 95% confidence interval (CI) 2.052–48.111, p = 0.004), tumor size (OR 1.048, 95% CI 1.005–1.093, p = 0.027), and tumor multiplicity (OR 3.323, 95% CI 1.048–10.534, p = 0.041) significantly increased the risk of T4 cancer. Sarcopenia patients showed significantly lower disease-free survival probability compared to non-sarcopenia patients. Therefore, preoperative sarcopenia in PTC patients should raise clinical suspicion for a more locally advanced disease and direct appropriate management and careful follow-up.

Influence of Incidental Detection of Thyroid Nodule on Thyroid Cancer Risk and Prognosis – A Systematic Review and Meta-analysis

Abstract Background Clinically inapparent thyroid nodules discovered serendipitously on imaging for non-thyroid indications are termed as thyroid incidentalomas. It is unclear whether these incidentalomas have a lower prevalence of malignancy or slower tumour progression compared to symptomatic nodules. The aim of this systematic review were to determine the impact of incidental detection of thyroid nodules on both the risk of malignancy and on prognosis in patients with thyroid cancer. Methods PubMed and MEDLINE® on Web of Science databases were searched from inception to April 2021 for English language articles reporting on human studies of thyroid cancer risk and/or prognosis in incidental and non-incidental nodules. Results Eighteen observational studies published between 1998 and 2020 were eligible for analysis; 4 studies reported on risk, 9 on prognosis and 5 studies reported on both risk and prognosis. When comparing the incidental and non-incidental groups in the risk study, the odds ratios calculated from the case control studies (n=6) ranged from 0.64 to 2.86; the relative risks calculated from the cohort studies (n=3) ranged from 0.13 to 6.27. A meta-analysis of the eligible case control studies (n=3) showed a non-significant summated odds ratio of 1.04 (95% CI=0.63–1.70, p=0.88). In the prognosis study, five direct and thirteen indirect markers of prognosis were compared between the incidental and non-incidental groups. A meta-analysis was not possible but incidentally detected thyroid cancer had better progression-free and overall survival. Conclusion Current evidence suggests that investigation and management of thyroid nodules should not be influenced by the mode of detection. However, incidentally detected nodules appear to have a better prognosis.