AUTHOR=Zhao Lingqian , Zhou Tianhan , Zhang Wenhao , Wu Fan , Jiang Kecheng , Lin Bei , Zhan Siqi , Hu Tao , Tang Tian , Zhang Yu , Luo Dingcun TITLE=Blood immune indexes can predict lateral lymph node metastasis of thyroid papillary carcinoma JOURNAL=Frontiers in Endocrinology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2022.995630 DOI=10.3389/fendo.2022.995630 ISSN=1664-2392 ABSTRACT=Objective

To explore the clinical significance of blood immune indexes in predicting lateral lymph node metastasis (LLNM) of thyroid papillary carcinoma (PTC).

Methods

The 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.

Results

According 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.

Conclusion

Blood 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.