Blood immune indexes can predict lateral lymph node metastasis of thyroid papillary carcinoma

Zhao, Lingqian; Zhou, Tianhan; Zhang, Wenhao; Wu, Fan; Jiang, Kecheng; Lin, Bei; Zhan, Siqi; Hu, Tao; Tang, Tian; Luo, Dingcun

doi:10.3389/fendo.2022.995630

Cited by 6 publications

(4 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Besides, Zhao et al . 116 also arrived at a similar conclusion. In recent years, the tumor immune microenvironment has become a prominent research topic in tumor biology.…”

Section: Molecular Features Of Progressive Ptmcsupporting

confidence: 53%

Clinical and molecular features of progressive papillary thyroid microcarcinoma

Wang,

Ji,

Zhang

et al. 2024

International Journal of Surgery

View full text Add to dashboard Cite

In recent decades, the prevalence of thyroid cancer has risen substantially, with papillary thyroid microcarcinoma (PTMC) constituting over 50% of cases. Although most PTMCs exhibit indolent growth and a favorable prognosis, some present an increased risk of recurrence and an unfavorable prognosis due to high-risk characteristics such as lymph node metastasis, extrathyroidal extension, and distant metastasis. The early identification of clinically progressing PTMC remains elusive. In this review, we summarize findings from PTMC progression-related literature, highlighting that factors such as larger tumor size, cervical lymph node metastasis, extrathyroidal extension, younger age, higher preoperative serum thyroid-stimulating hormone levels, family history, and obesity positively correlate with PTMC progression. The role of multifocality in promoting PTMC progression, however, remains contentious. Furthermore, recent studies have shed light on the impact of mutations, such as BRAF and TERT mutations, on PTMC progression. Researchers have identified several mRNAs, non-coding RNAs, and proteins associated with various features of PTMC progression. Some studies propose that peripheral and tumor tissue-infiltrating immune cells could serve as biomarkers for the clinical progression of PTMC. Collectively, these clinical and molecular features offer a rationale for the early detection and the development of precision theranostic strategies of clinically progressive PTMC.

show abstract

“…Besides, Zhao et al . 116 also arrived at a similar conclusion. In recent years, the tumor immune microenvironment has become a prominent research topic in tumor biology.…”

Section: Molecular Features Of Progressive Ptmcsupporting

confidence: 53%

Clinical and molecular features of progressive papillary thyroid microcarcinoma

Wang,

Ji,

Zhang

et al. 2024

International Journal of Surgery

View full text Add to dashboard Cite

show abstract

“…Given the close relationship between tumour development and the immune status of individuals 45 , previous studies attempted to predict the biological behaviour of thyroid tumours by examining immune indicators in the blood 46 – 48 . In our recent study, we identified tumour diameter and SII as independent risk factors for lateral lymph node metastasis in PTC 49 . Consequently, this study incorporates commonly used blood immune indicators as a crucial predictive dimension.…”

Section: Discussionmentioning

confidence: 97%

Risk stratification of papillary thyroid cancers using multidimensional machine learning

Li,

Wu,

et al. 2023

International Journal of Surgery

Self Cite

View full text Add to dashboard Cite

Background: Papillary thyroid cancer (PTC) is one of the most common endocrine malignancies with different risk levels. However, preoperative risk assessment of PTC is still a challenge in the worldwide. Here, we first report a Preoperative Risk Assessment Classifier for PTC (PRAC-PTC) by multidimensional features including clinical indicators, immune indices, genetic feature, and proteomics. Materials and methods: The 558 patients collected from June 2013 to November 2020 were allocated to three groups: discovery set (274 patients, 274 FFPE), retrospective test set (166 patients, 166 FFPE) and prospective test set (118 patients, 118 FNA). Proteomic profiling was conducted by formalin-fixed paraffin-embedded (FFPE) and fine-needle aspiration (FNA) tissues from the patients. Preoperative clinical information and blood immunological indices were collected. The BRAF V600E mutation were detected by the amplification refractory mutation system (ARMS). Results: We developed a machine learning model of 17 variables based on multidimensional features of 274 PTC patients from a retrospective cohort. The PRAC-PTC achieved areas under the curve (AUC) of 0.925 in the discovery set and validated externally by blinded analyses in a retrospective cohort of 166 PTC patients (0.787 AUC) and a prospective cohort of 118 PTC patients (0.799 AUC) from two independent clinical centres. Meanwhile, the preoperative predictive risk effectiveness of clinicians was improved with the assistance of PRAC-PTC, and the accuracies reached at 84.4% (95% CI 82.9-84.4) and 83.5% (95% CI 82.2-84.2) in the retrospective and prospective test sets, respectively. Conclusion: This study demonstrated that the PRAC-PTC that integrating clinical data, gene mutation information, immune indices, high-throughput proteomics and machine learning technology in multi-centre retrospective and prospective clinical cohorts can effectively stratify the preoperative risk of PTC and may decrease unnecessary surgery or overtreatment.

show abstract

“…Meanwhile, Zhao et al. ( 23 ) discovered that the integration of the preoperative SII index and the tumor diameter is a reliable predictor of lymph node metastasis in patients with PTC. However, despite the inclusion of numerous inflammatory indicators, this study did not observe significant predictive effects of SII, NLR, and MLR in terms of conCLNM or conMVCLNM.…”

Section: Discussionmentioning

confidence: 99%

Nomogram model based on preoperative clinical characteristics of unilateral papillary thyroid carcinoma to predict contralateral medium-volume central lymph node metastasis

Wu,

Huang,

Huang

et al. 2024

Front. Endocrinol.

Self Cite

View full text Add to dashboard Cite

ObjectivesTo explore the preoperative high-risk clinical factors for contralateral medium-volume central lymph node metastasis (conMVCLNM) in unilateral papillary thyroid carcinoma (uPTC) and the indications for dissection of contralateral central lymph nodes (conCLN).MethodsClinical and pathological data of 204 uPTC patients who underwent thyroid surgery at the Hangzhou First People’s Hospital from September 2010 to October 2022 were collected. Univariate and multivariate logistic regression analyses were conducted to determine the independent risk factors for contralateral central lymph node metastasis (conCLNM) and conMVCLNM in uPTC patients based on the preoperative clinical data. Predictive models for conCLNM and conMVCLNM were constructed using logistic regression analyses and validated using receiver operating characteristic (ROC) curves, concordance index (C-index), calibration curves, and decision curve analysis (DCA).ResultsUnivariate and multivariate logistic regression analyses showed that gender (P < 0.001), age (P < 0.001), tumor diameter (P < 0.001), and multifocality (P = 0.008) were independent risk factors for conCLNM in uPTC patients. Gender(P= 0.026), age (P = 0.010), platelet-to-lymphocyte ratio (PLR) (P =0.003), and tumor diameter (P = 0.036) were independent risk factors for conMVCLNM in uPTC patients. A predictive model was established to assess the risk of conCLNM and conMVCLNM, with ROC curve areas of 0.836 and 0.845, respectively. The C-index, the calibration curve, and DCA demonstrated that the model had good diagnostic value.ConclusionGender, age, tumor diameter, and multifocality are high-risk factors for conCLNM in uPTC patients. Gender, age, tumor diameter, and PLR are high-risk factors for conMVCLNM in uPTC patients, and preventive conCLN dissection should be performed.

show abstract

Blood immune indexes can predict lateral lymph node metastasis of thyroid papillary carcinoma

Cited by 6 publications

References 24 publications

Clinical and molecular features of progressive papillary thyroid microcarcinoma

Clinical and molecular features of progressive papillary thyroid microcarcinoma

Risk stratification of papillary thyroid cancers using multidimensional machine learning

Nomogram model based on preoperative clinical characteristics of unilateral papillary thyroid carcinoma to predict contralateral medium-volume central lymph node metastasis

Contact Info

Product

Resources

About