scholarly journals Blood-Rich Enhancement in Ultrasonography Predicts Worse Prognosis in Patients With Papillary Thyroid Cancer

2021 ◽  
Vol 10 ◽  
Author(s):  
Luying Gao ◽  
Xuehua Xi ◽  
Qiong Gao ◽  
Jiajia Tang ◽  
Xiao Yang ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Cox Regression ◽  
Area Under The Curve ◽  
Papillary Thyroid ◽  
Predictive Values ◽  
Incomplete Response ◽  
Potential Association ◽  
Contrast Enhanced ◽  
Patient Prognosis

Contrast-enhanced ultrasound (CEUS) can be used to evaluate microcirculation in cancers, which in turn is associated with the biologic features and ultimately patient prognosis. We conducted a retrospective analysis to examine potential association between CEUS parameters and prognosis in patients with papillary thyroid cancer (PTC). The analysis included 306 patients who underwent CEUS prior to thyroidectomy at our center during a period from 2012 to 2019. Subjects with excellent response (ER) were compared to the non-ER group (including indeterminate response, biochemical incomplete response and structural incomplete response). During the median follow-up of 34 months, ER was observed in 195 (63.7%) subjects. The remaining 111 (36.3%) patients developed non-ER events, with distant metastasis in five (1.6%) cases. In a multivariate COX regression, non-ER event was associated with the male sex (OR = 1.83, 95%CI: 1.21–2.76) and blood-rich enhancement in CEUS (OR = 1.69, 95%CI: 1.04–2.75). Based on this finding, we developed a predictive model: high risk for developing non-ER events was defined as having both risk factors; low risk was defined as having none or only one risk. In receiver operating characteristic (ROC) analysis, the area under the curve was 0.59 (95%CI: 0.52–0.66). The sensitivity and specificity were 17.1 and 95.4%, respectively. The positive and negative predictive values were 67.9 and 66.9%, respectively. In conclusion, blood-rich enhancement in CEUS is associated with non-ER events after thyroidectomy in patients with PTC.

scholarly journals Annual Hazard Rate of Recurrence in Middle Eastern Papillary Thyroid Cancer over a Long-Term Follow-Up

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3624
Author(s):  
Abdul K. Siraj ◽  
Sandeep Kumar Parvathareddy ◽  
Zeeshan Qadri ◽  
Khawar Siddiqui ◽  
Saif S. Al-Sobhi ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Hazard Rate ◽  
Tumor Recurrence ◽  
Cox Regression ◽  
Middle Eastern ◽  
Treatment Strategies ◽  
Recurrence Risk ◽  
Papillary Thyroid ◽  
Cox Regression Analysis

Predicting the pattern of recurrence in papillary thyroid cancer (PTC) is necessary to establish optimal surveillance and treatment strategies. We analyzed changes in hazard rate (HR) for tumor recurrence over time in 1201 unselected Middle Eastern PTC patients. The changes in risk were further analyzed according to clinical variables predictive of early (≤5 years) and late (>5 years) recurrence using Cox regression analysis to identify patient populations that remain at risk. Tumor recurrence was noted in 18.4% (221/1201) patients. The annualized hazard of PTC recurrence was highest during the first 5 years (2.8%), peaking between 1 and 2 years (3.7%), with a second smaller peak between 13 and 14 years (3.2%). Patients receiving radioactive iodine (RAI) therapy had lower recurrence hazard compared to those who did not (1.5% vs. 2.7%, p = 0.0001). Importantly, this difference was significant even in intermediate-risk PTC patients (0.7% vs. 2.3%; p = 0.0001). Interestingly, patients aged ≥55 years and having lymph node metastasis were at persistent risk for late recurrence. In conclusion, we confirmed the validity of the double-peaked time-varying pattern for recurrence risk in Middle Eastern PTC patients and our findings could help in formulating individualized treatment and surveillance plans.

scholarly journals Comprehensive Analysis of Prognostic Alternative Splicing Signature Reveals Recurrence Predictor for Papillary Thyroid Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Mian Liu ◽  
Rooh Afza Khushbu ◽  
Pei Chen ◽  
Hui-Yu Hu ◽  
Neng Tang ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Alternative Splicing ◽  
Papillary Thyroid Cancer ◽  
Molecular Mechanisms ◽  
Prediction Models ◽  
Cox Regression ◽  
Prognostic Biomarkers ◽  
Papillary Thyroid ◽  
Network Diagram ◽  
Prognostic Prediction

BackgroundAlternative splicing (AS) plays a key role in the diversity of proteins and is closely associated with tumorigenicity. The aim of this study was to systemically analyze RNA alternative splicing (AS) and identify its prognostic value for papillary thyroid cancer (PTC).MethodsAS percent-splice-in (PSI) data of 430 patients with PTC were downloaded from the TCGA SpliceSeq database. We successfully identified recurrence-free survival (RFS)-associated AS events through univariate Cox regression, LASSO regression and multivariate regression and then constructed different types of prognostic prediction models. Gene function enrichment analysis revealed the relevant signaling pathways involved in RFS-related AS events. Simultaneously, a regulatory network diagram of AS and splicing factors (SFs) was established.ResultsWe identified 1397 RFS-related AS events which could be used as the potential prognostic biomarkers for PTC. Based on these RFS-related AS events, we constructed a ten-AS event prognostic prediction signature that could distinguish high-and low-risk patients and was highly capable of predicting PTC patient prognosis. ROC curve analysis revealed the excellent predictive ability of the ten-AS events model, with an area under the curve (AUC) value of 0.889; the highest prediction intensity for one-year RFS was 0.923, indicating that the model could be used as a prognostic biomarker for PTC. In addition, the nomogram constructed by the risk score of the ten-AS model also showed high predictive efficiency for the prognosis of PTC patients. Finally, the constructed SF-AS network diagram revealed the regulatory role of SFs in PTC.ConclusionThrough the limited analysis, AS events could be regarded as reliable prognostic biomarkers for PTC. The splicing correlation network also provided new insight into the potential molecular mechanisms of PTC.

scholarly journals Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Yongfeng Ding ◽  
Zhuochao Mao ◽  
Jiaying Ruan ◽  
Xingyun Su ◽  
Linrong Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Cox Regression ◽  
Early Stage ◽  
Cox Model ◽  
Staging System ◽  
Papillary Thyroid ◽  
Cox Regression Analysis ◽  
Ajcc Staging

Background and Objectives. The clinicopathological risk factors to predict recurrence of papillary thyroid cancer (PTC) patients remain controversial. Methods. PTC patients treated with thyroidectomy between January 1997 and December 2011 at the First Affiliated Hospital of Zhejiang University (Zhejiang cohort) were included. Multivariate Cox regression analysis was conducted to identify independent recurrence predictors. Then, the nomogram model for predicting probability of recurrence was built. Results. According to Zhejiang cohort (N = 1,697), we found that the 10-year event-free survival (EFS) rates of PTC patients with early-stage (TNM stages I, II, and III) were not well discriminated (91.6%, 89.0%, and 90.7%; P=0.768). The multivariate Cox model identified age, bilaterality, tumor size, and nodal status as independent risk factors for tumor recurrence in PTC patients with TNM stages I–III. We then developed a nomogram with the C-index 0.70 (95% CI, 0.64 to 0.76), which was significantly higher (P<0.0001) than the AJCC staging system (0.52). In the validation group, the C-index remained at a similar level. Conclusions. In this study, we build up a new recurrence predicting system and establish a nomogram for early-stage PTC patients. This prognostic model may better predict individualized outcomes and conduct personalized treatments.

Downregulation of miR-519d-3p is Associated with Poor Outcomes and Facilitates Tumor Progression in Papillary Thyroid Cancer by Regulating FOXQ1

2021 ◽  
Vol 53 (09) ◽  
pp. 625-632
Author(s):  
Pihong Li ◽  
Xiaoyu Pan ◽  
Zhouci Zheng ◽  
Yihan Sun ◽  
Yifan Han ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Tumor Progression ◽  
Papillary Thyroid Cancer ◽  
Cox Regression ◽  
Biological Effects ◽  
Pearson Correlation ◽  
Progression Free Survival ◽  
Luciferase Reporter ◽  
Migration And Invasion ◽  
Papillary Thyroid

AbstractMicroRNA-519d-3p (miR-519d-3p) has emerged as a tumor suppressor in several human cancers. But whether miR-519d-3p is involved in papillary thyroid cancer (PTC) remains elusive. In this study, we investigated the potential relevance of miR-miR-519d-3p in PTC. A retrospective study of 119 PTCs was carried out. The RT-qPCR analysis was used to measure the expression of miR-519d-3p and FOXQ1 in PTC tissues and cells. Chi-square test, Kaplan–Meier curve analysis, and multivariate Cox regression analyses were performed to assess the clinical and prognostic value of miR-519d-3p in PTC. Then cellular experiments were used to explore its biological effects on PTC cells. Finally, the Pearson correlation coefficient, dual-luciferase reporter assay, and rescue experiments were used to analyze the association between miR-519d-3p and FOXQ1. miR-519d-3p was significantly downregulated in PTC tissues and cell lines. The decreased expression of miR-519d-3p was associated with reduced overall survival and progression-free survival of patients. The proliferative, migratory, and invasive abilities of cells were blocked or elevated after upregulation or downregulation of miR-519d-3p, while FOXQ1 reversed these cellular behaviors caused after upregulation or knockdown of miR-519d-3p. In conclusion, miR-519d-3p was downregulated in PTC and associated with OS and PFS of patients. MiR-519d-3p may be a tumor-inhibiting miRNA in PTC, and that miR-519d-3p/FOXQ1 axis mediated PTC tumor progression from cell proliferation, migration, and invasion in PTC cells.

Disease Progression in Papillary Thyroid Cancer with Biochemical Incomplete Response to Initial Therapy

2017 ◽  
Vol 24 (9) ◽  
pp. 2611-2616 ◽  
Author(s):  
Nicole K. Zern ◽  
Roderick Clifton-Bligh ◽  
Anthony J. Gill ◽  
Ahmad Aniss ◽  
Stan Sidhu ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Disease Progression ◽  
Papillary Thyroid Cancer ◽  
Initial Therapy ◽  
Papillary Thyroid ◽  
Incomplete Response

Predictors of incomplete response to therapy among Filipino patients with papillary thyroid cancer in a tertiary hospital

2015 ◽  
Vol 39 (1) ◽  
pp. 55-62
Author(s):  
E. S. Mendoza ◽  
A. A. Lopez ◽  
V. A. U. Valdez ◽  
E. C. Cunanan ◽  
B. J. Matawaran ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Tertiary Hospital ◽  
Response To Therapy ◽  
Papillary Thyroid ◽  
Incomplete Response

scholarly journals Ultrasonic Intelligent Diagnosis of Papillary Thyroid Carcinoma Based on Machine Learning

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Heng Zhou ◽  
Bin Liu ◽  
Yang Liu ◽  
Qunan Huang ◽  
Wei Yan
Keyword(s):  
Machine Learning ◽  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Clinical Experience ◽  
Thyroid Diseases ◽  
Paper Machine ◽  
Contrast Enhanced Ultrasound ◽  
Papillary Thyroid ◽  
Intelligent Diagnosis ◽  
Contrast Enhanced

Thyroid diseases are divided into papillary carcinoma and nodular diseases, which are very harmful to the human body. Ultrasound is a common diagnostic method for thyroid diseases. In the process of diagnosis, doctors need to observe the characteristics of ultrasound images, combined with professional knowledge and clinical experience, to give the disease situation of patients. However, different doctors have different clinical experience and professional backgrounds, and the diagnosis results lack objectivity and consistency, so an intelligent diagnosis technology for thyroid diseases based on the ultrasound image is needed in clinic, which can give objective and reliable diagnosis opinions on thyroid diseases by extracting the texture, shape, and other information of the image and assist doctors in clinical diagnosis. This paper mainly studies the intelligent ultrasonic diagnosis of papillary thyroid cancer based on machine learning, compares the ultrasonic characteristics of PTMC diagnosed by using the new ultrasound technology (CEUS and UE), and summarizes the differential diagnosis effect and clinical application value of the two technology methods for PTMC. In this paper, machine learning, diffuse thyroid image features, and RBM learning methods are used to study the ultrasonic intelligent diagnosis of papillary thyroid cancer based on machine learning. At the same time, the new contrast-enhanced ultrasound (CEUS) technology and ultrasound elastography (UE) technology are used to obtain the experimental phenomena in the experiment of ultrasonic intelligent diagnosis of papillary thyroid cancer. The results showed that 90% of the cases were diagnosed by contrast-enhanced ultrasound and confirmed by postoperative pathology. CEUS and UE have reliable practical value in the diagnosis of PTMC, and the combined application of CEUS and UE can improve the sensitivity and accuracy of PTMC diagnosis.

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