Using nomograms to predict the presence of papillary thyroid carcinoma.
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ABSTRACT:
SUBMITTER: van Velsen EFS
PROVIDER: S-EPMC10425651 | biostudies-literature | 2023 Jul
REPOSITORIES: biostudies-literature
Publications
Using nomograms to predict the presence of papillary thyroid carcinoma.
van Velsen Evert F S EFS Verburg Frederik A FA
Translational cancer research 20230620 7
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Project description:BackgroundLateral lymph node metastasis (LLNM) is a risk factor of poor prognosis in papillary thyroid cancer (PTC). We aimed to determine predictive factors and develop the nomograms for LLNM in patients with papillary thyroid microcarcinoma (PTMC) and macro-PTC.MethodsWe reviewed the medical records of 1,106 patients who underwent surgery between January 2019 and January 2022. Patients were divided into a PTMC and a macro-PTC group. We developed preoperative and postoperative nomograms for predicting LLNM based on results of multivariate analysis. Internal calibration was performed for these models.ResultsThe number of metastatic lymph nodes in lateral compartment was higher in macro-PTC patients. LLNM was independently associated with gender, the number of foci, location, shape, and central lymph node metastasis (CLNM) in PTMC patients. For macro-PTC patients, chronic lymphocytic thyroiditis, the number of foci, location, margin, CLNM, and central lymph node ratio were all independent predictors for LLNM. All the above factors were incorporated into nomograms, which showed the perfect discriminative ability.ConclusionThe diameter of the tumor has an impact on the rate of LLNM. Separate predictive systems should be used for PTMC and macro-PTC patients for more accurate clinical assessment of lateral lymph node status. Through these nomograms, we can not only detect high-risk patients with occult LLNM preoperatively, but also form appropriate treatment protocols for postoperative management of PTC patients with different risks.
| S-EPMC9554485 | biostudies-literature
Project description:Papillary thyroid carcinomas are the most common thyroid cancers and constitute more than 70% of thyroid malignancies. The most common etiologic factor is radiation, but genetic susceptibility and other factors also contribute to the development of papillary thyroid carcinoma. The most common variants include conventional, follicular variant and tall cell variant. However, many other uncommon variants have been described including oncocytic, columnar cell, diffuse sclerosing and solid forms. Immunohistochemical staining with TTF-1 and thyroglobulin is very useful in confirming the diagnosis of papillary thyroid carcinoma especially in metastatic sites. Markers such as HBME-1 and CITED1 can assist in separating some difficult cases of follicular variants of papillary thyroid carcinomas from follicular adenomas. Molecular studies have shown that the BRAF V600E mutation is found mainly in papillary and anaplastic thyroid carcinomas. Other molecular markers such as HMGA2 and insulin-like growth factor II mRNA binding protein 3 have been used recently as molecular tests to separate papillary thyroid carcinoma and its variants from follicular adenomas and other benign thyroid nodules.
| S-EPMC3037461 | biostudies-literature
Project description:BackgroundAs a rare but aggressive papillary thyroid carcinoma (PTC) variant, the genetic changes of hobnail variant of PTC (HVPTC) are still unclear.ResultsThe prevalence of HVPTC was 1.69% (18/1062) of all PTC diagnosed in our cohort. 73 samples from 55 patients (17 HVPTC, 26 CPTC, 7 PDTC and 5 ATC) were successfully analyzed using targeted NGS with an 18-gene panel. Thirty-seven mutation variant types were identified among 11 genes. BRAF V600E mutation was the most common mutation, which is present in almost all HVPTC samples (16/17, 94%), most CPTC samples (20/26, 77%), and none of the ATC and PDTC samples. TERT promoter mutation (C228T) was identified in 2 ATC and one HVPTC patient. RAS and TP53 mutation are almost exclusively present among ATC and PDTC samples although TP53 mutation was also observed in 3 HVPTC patients. Six different GNAS mutations were identified among 8 CPTC patients (31%) and none of the HVPTC patients. The only patient who died of disease progression harbored concomitant TERT C228T mutation, BRAF V600E mutation and TP53 mutation.MethodsHVPTC cases were identified from a group of 1062 consecutive surgical specimens diagnosed as PTC between 2000 and 2010. Targeted next-generation sequencing (NGS) was applied to investigate the mutation spectrum of HVPTC, compared to classical PTC (CPTC), poorly differentiated thyroid carcinoma (PDTC) and anaplastic thyroid carcinoma (ATC).ConclusionAs an aggressive variant of PTC, HVPTC has relatively specific molecular features, which is somewhat different from both CPTC and ATC/PDTC and may underlie its relatively aggressive behavior.
| S-EPMC5400643 | biostudies-literature
Project description:Background:The purpose of this study was to evaluate the factors associated with lateral lymph node metastasis (LLNM) in patients with papillary thyroid carcinoma (PTC), and to develop two web-based nomograms that predict the probability of level-II and level-III/IV LLNM in these patients. Methods:The records of 653 patients with PTC were retrospectively reviewed. Univariate and multivariate analyses were performed to identify risk factors associated with LLNM in 460 patients ("derivation group"). Two models [including and excluding the subregions of central lymph node metastasis (CLNM)] were used to predict the probability of level-II LLNM; the same two models were also used for level-III/IV LLNM. Model performance was assessed using receiver operating characteristic (ROC) analysis and decision curve analysis (DCA) in 193 patients ("validation group"). Two web-based nomograms were established. Results:Increased tumor size, a tumor in the upper lobe, and prelaryngeal and ipsilateral paratracheal lymph node metastasis (LNM) were significantly associated with level-II LNM (P<0.05). Increased tumor size, a tumor in the upper lobe, and certain subregions of CLNM were associated with level-III/IV LNM (P<0.05). Use of ROC analysis of each model indicated that including subgroups of CLNM led to better model performance than excluding these subgroups. We quantified the benefit of each model by using DCA analysis in the validation group. Conclusions:Our web-based nomograms provide quantification of risk for LLNM in patients with PTC before and during surgery.
| S-EPMC7225478 | biostudies-literature
Project description:As the predominant thyroid cancer, papillary thyroid cancer (PTC) accounts for 75‑85% of thyroid cancer cases. This research aimed to investigate transcriptomic changes and key genes in PTC. Using RNA‑sequencing technology, the transcriptional profiles of 5 thyroid tumor tissues and 5 adjacent normal tissues were obtained. The single nucleotide polymorphisms (SNPs) were identified by SAMtools software and then annotated by ANNOVAR software. After differentially expressed genes (DEGs) were selected by edgR software, they were further investigated by enrichment analysis, protein domain analysis, and protein‑protein interaction (PPI) network analysis. Additionally, the potential gene fusion events were predicted using FusionMap software. A total of 70,172 SNPs and 2,686 DEGs in the tumor tissues, as well as 83,869 SNPs in the normal tissues were identified. In the PPI network, fibronectin 1 (FN1; degree=31) and transforming growth factor β receptor 1 (TGFβR1; degree=22) had higher degrees. A total of 7 PPI pairs containing the non‑synonymous risk SNP loci in the interaction domains were identified. Particularly, the interaction domains involved in the interactions of FN1 and 5 other proteins (such as FN1‑tenascin C, TNC) had non‑synonymous risk SNP loci. Furthermore, 11 and 4 gene fusion events were identified in all of the tumor tissues and normal tissues, respectively. Additionally, the NK2 homeobox 1‑surfactant associated 3 (NKX2‑1‑SFTA3) gene fusion was identified in both tumor and normal tissues. These results indicated that TGFβR1 and the NKX2‑1‑SFTA3 gene fusion may be involved in PTC. Furthermore, FN1 and TNC containing the non‑synonymous risk SNP loci might serve a role in PTC by interacting with each other.
| S-EPMC5865774 | biostudies-literature
Project description:ObjectivesThyroid cancer incidence increased over 200% from 1992 to 2018, whereas mortality rates had not increased proportionately. The increased incidence has been attributed primarily to the detection of subclinical disease, raising important questions related to thyroid cancer control. We developed the Papillary Thyroid Carcinoma Microsimulation model (PATCAM) to answer them, including the impact of overdiagnosis on thyroid cancer incidence.MethodsPATCAM simulates individuals from age 15 until death in birth cohorts starting from 1975 using 4 inter-related components, including natural history, detection, post-diagnosis, and other-cause mortality. PATCAM was built using high-quality data and calibrated against observed age-, sex-, and stage-specific incidence in the United States as reported by the Surveillance, Epidemiology, and End Results database. PATCAM was validated against US thyroid cancer mortality and 3 active surveillance studies, including the largest and longest running thyroid cancer active surveillance cohort in the world (from Japan) and 2 from the United States.ResultsPATCAM successfully replicated age- and stage-specific papillary thyroid cancers (PTC) incidence and mean tumor size at diagnosis and PTC mortality in the United States between 1975 and 2015. PATCAM accurately predicted the proportion of tumors that grew more than 3 mm and 5 mm in 5 years and 10 years, aligning with the 95% confidence intervals of the reported rates from active surveillance studies in most cases.ConclusionsPATCAM successfully reproduced observed US thyroid cancer incidence and mortality over time and was externally validated. PATCAM can be used to identify factors that influence the detection of subclinical PTCs.
| S-EPMC10922958 | biostudies-literature
Project description:Papillary thyroid carcinoma (PTC) is the most common adult thyroid malignancy and often presents with multiple anatomically distinct foci within the thyroid, known as multifocal papillary thyroid carcinoma (MPTC). The widespread application of the next-generation sequencing technologies in cancer genomics research provides novel insights into determining the clonal relationship between multiple tumours within the same thyroid gland. For eight MPTC patients, we performed whole-exome sequencing and targeted region sequencing to identify the non-synonymous point mutations and gene rearrangements of distinct and spatially separated tumour foci. Among these eight MPTCs, completely discordant mutational spectra were observed in the distinct cancerous nodules of patients MPTC1 and 5, suggesting that these nodules originated from independent precursors. In another three cases (MPTC2, 6, and 8), the distinct MPTC foci of these patients had no other shared mutations except BRAF V600E, also indicating likely independent origins. Two patients (MPTC3 and 4) shared almost identical mutational spectra amongst their separate tumour nodules, suggesting a common clonal origin. MPTC patient 7 had seven cancer foci, of which two foci shared 66.7% of mutations, while the remaining cancer foci displayed no common non-synonymous mutations, indicating that MPTC7 has multiple independent origins accompanied by intraglandular disease dissemination. In this study, we found that 75% of MPTC cases arose as independent tumours, which supports the field cancerization hypothesis describing multiple malignant lesions. MPTC may also arise from intrathyroidal metastases from a single malignant clone, as well as multiple independent origins accompanied by intrathyroidal metastasis.
| S-EPMC5706659 | biostudies-literature
Project description:BackgroundThis work explores the clinical significance of Delphian lymph nodes (DLN) in thyroid papillary carcinoma (PTC). At the same time, a nomogram is constructed based on clinical, pathological, and ultrasonic (US) features to evaluate the possibility of DLN metastasis (DLNM) in PTC patients. This is the first study to predict DLNM using US characteristics.MethodsA total of 485 patients, surgically diagnosed with PTC between February 2017 and June 2021, all of whom underwent thyroidectomy, were included in the study. Using the clinical, pathological, and US information of patients, the related factors of DLNM were retrospectively analyzed. The risk factors associated with DLNM were identified through univariate and multivariate analyses. According to clinical + pathology, clinical + US, and clinical + US + pathology, the predictive nomogram for DLNM was established and validated.ResultsOf the 485 patients with DLN, 98 (20.2%) exhibited DLNM. The DLNM positive group had higher positive rates of central lymph node metastasis (CLNM), lateral lymph node metastasis (LLNM), and T3b-T4b thyroid tumors than the negative rates. The number of CLNM and LLNM lymph nodes in the DLNM+ group was higher as compared to that in the DLNM- group. Multivariate analysis demonstrated that the common independent risk factors of the three prediction models were male, bilaterality, and located in the isthmus. Age ≥45 years, located in the lower pole, and nodural goiter were protective factors. In addition, the independent risk factors were classified as follows: (I) P-extrathyroidal extension (ETE) and CLNM based on clinical + pathological characteristics; (II) US-ETE and US-CLNM based on clinical + US characteristics; and (III) US-ETE and CLNM based on clinical +US + pathological features. Better diagnostic efficacy was reported with clinical + pathology + US diagnostic model than that of clinical + pathology diagnostic model (AUC 0.872 vs. 0.821, p = 0.039). However, there was no significant difference between clinical + pathology + US diagnostic model and clinical + US diagnostic model (AUC 0.872 vs. 0.821, p = 0.724).ConclusionsThis study found that DLNM may be a sign that PTC is more invasive and has extensive lymph node metastasis. By exploring the clinical, pathology, and US characteristics of PTC progression to DLNM, three prediction nomograms, established according to different combinations of features, can be used in different situations to evaluate the transfer risk of DLN.
| S-EPMC8733604 | biostudies-literature
Project description:ObjectiveTo summarize the clinicopathological characteristics and prognostic factors of papillary renal cell carcinoma (pRCC) and to construct clinical and molecular prognostic nomograms using existing databases.MethodsClinical prognostic models were developed using the Surveillance, Epidemiology, and End Results (SEER) database, while molecular prognostic models were constructed using The Cancer Genome Atlas (TCGA) database. Cox regression and LASSO regression were employed to identify clinicopathological features and molecular markers related to prognosis. The accuracy of the prognostic models was assessed using ROC curves, C-index, decision curve analysis (DCA) curves, and calibration plots.ResultsIn the 2004-2015 SEER cohort, Cox regression analysis revealed that age, grade, AJCC stage, N stage, M stage, and surgery were independent predictors of overall survival (OS) and cancer-specific survival (CSS) in pRCC patients. ROC curves, C-index, and DCA curves indicated that the prognostic nomogram based on clinical independent predictors had better predictive ability than TNM staging and SEER staging. Additionally, in the TCGA cohort, M stage, clinical stage, and the molecular markers IDO1 and PLK1 were identified as independent risk factors. The prognostic nomogram based on molecular independent risk factors effectively predicted the 3-year and 5-year OS and CSS for pRCC patients.ConclusionsThe clinical and molecular nomograms constructed in this study provide robust predictive tools for individualized prognosis in pRCC patients, offering better accuracy than traditional staging systems.
| S-EPMC11655765 | biostudies-literature
Project description:Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Here, we describe the genomic landscape of 496 PTCs. We observed a low frequency of somatic alterations (relative to other carcinomas) and extended the set of known PTC driver alterations to include EIF1AX, PPM1D, and CHEK2 and diverse gene fusions. These discoveries reduced the fraction of PTC cases with unknown oncogenic driver from 25% to 3.5%. Combined analyses of genomic variants, gene expression, and methylation demonstrated that different driver groups lead to different pathologies with distinct signaling and differentiation characteristics. Similarly, we identified distinct molecular subgroups of BRAF-mutant tumors, and multidimensional analyses highlighted a potential involvement of oncomiRs in less-differentiated subgroups. Our results propose a reclassification of thyroid cancers into molecular subtypes that better reflect their underlying signaling and differentiation properties, which has the potential to improve their pathological classification and better inform the management of the disease.
| S-EPMC4243044 | biostudies-literature