ObjectiveTo explore the clinical significance of blood immune indexes in predicting lateral lymph node metastasis (LLNM) of thyroid papillary carcinoma (PTC).MethodsThe pathological data and preoperative blood samples of 713 patients that underwent thyroid surgery at affiliated Hangzhou First People’s Hospital Zhejiang University School of Medicine from January 2013 to June 2021 were collected as the model group. The pathological data and preoperative blood samples of 177 patients that underwent thyroid surgery in the same hospital from July 2021 to October 2021 were collected as the external validation group. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors of LLNM in PTC patients. A predictive model for assessing LLNM in PTC patients was established and externally validated using the external data.ResultsAccording to univariate and multivariate logistic regression analyses, tumor diameter (P < 0.001, odds ratios (OR): 1.205, 95% confidence interval (CI): 1.162–1.249) and the preoperative systemic immune-inflammation index (SII) (P = 0.032, OR: 1.001, 95% CI: 1.000–1.002) were independent risk factors for distinguishing LLNM in PTC patients. When the Youden index was the highest, the area under the curve (AUC) was 0.860 (P < 0.001, 95% CI: 0.821–0.898). The externally validated AUC was 0.827 (P < 0.001, 95% CI: 0.724–0.929), the specificity was 86.4%, and the sensitivity was 69.6%. The calibration curve and the decision curve indicated that the model had good diagnostic value.ConclusionBlood immune indexes can reflect the occurrence of LLNM and the biological behavior of PTC. The predictive model established in combination with SII and tumor diameter can effectively predict the occurrence of LLNM in PTC patients.
BackgroundAccurate evaluation of the risk of papillary thyroid microcarcinoma (PTMC) is the key to treatment. However, the maximum diameter (MD), which is currently used in various staging systems, may not truly reflect the aggressiveness of multifocal tumors.MethodsClinical and pathological data for 1001 patients with papillary thyroid carcinoma who underwent surgery at the Hangzhou First People’s Hospital were retrospectively analyzed. First, the relationship between total tumor diameter (TTD) and clinicopathological features in multifocal PTMC was explored. Then, patients were divided into subgroups according to the TTD. The baseline was consistent after using the propensity score matching method, and the differences between groups were compared. In addition, the effectiveness of TTD and MD in evaluating central lymph node metastasis (CLNM) was analyzed and compared.ResultsTTD is associated with a range of clinicopathological features, including lymph node metastasis, extrathyroidal extension, and risk stratification. Assuming the same MD and number of foci, the invasiveness of multifocal PTMC with TTD >1 cm was significantly higher than that with TTD <1 cm, and even higher than unifocal non-PTMC. Moreover, the efficiency of TTD in predicting CLNM was also significantly higher than that of MD.ConclusionFor multifocal PTMC, TTD is a more realistic indicator of tumor biological characteristics than MD. The aggressiveness of PTMC with TTD >1 cm was significantly enhanced, and surgical treatment should be actively sought in such cases.
Background: The incidence and recurrence rate of papillary thyroid carcinoma (PTC) are high. Thus, it is critical to accurately identify patients at high risk of recurrence. Pyroptosis is a type of programmed cell death closely related to the progression and prognosis of cancer. However, the role of pyroptosis in PTC remains unclear. Methods: Transcriptome data for PTC patients were obtained from The Cancer Genome Atlas database. The expression level of pyroptosis-related genes (PRGs) in PTC and normal tissues was identified. Based on these differentially expressed genes, a risk score model of disease-free survival (DFS) was established using least absolute shrinkage and selection operator Cox regression. In-cluster and quantitative real-time PCR validations were carried out. A nomogram, in combination with clinical factors, was also established. In addition, its relationship with immune characteristics and tumor gene mutations is discussed. Results: A risk score model with four PRGs, including CASP6, CASP9, IL-18, and NOD1, was established. The samples were divided into high- and low-risk clusters, according to the risk score, revealing significant differences in DFS between the two clusters. A nomogram was established combining age, lymph node metastasis and extrathyroidal extension. The area under the curve (AUC) of predicting one-, five-, and 10-year DFS in PTC patients was 0.745, 0.801, and 0.803, respectively. The low-risk cluster showed higher levels of immune infiltration and immune checkpoint gene expression, while the high-risk cluster demonstrated a higher tumor mutation burden. Conclusion: A predictive DFS model was established, based on PRGs, which may aid in identifying patients at high risk of recurrence. The present study helps to better understand the role of pyroptosis in the progression and prognosis of PTC.
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