Correlation of multiple peripheral blood parameters with metastasis and invasion of papillary thyroid cancer: a retrospective cohort study

Objective The primary progression mechanisms of papillary thyroid cancer (PTC) involve the development of lymph node metastasis and thyroid capsular invasion. This study aimed to identify high-risk populations for these conditions in PTC based on various peripheral blood tests, and to investigate the factors significantly associated with such populations. Methods A total of 4,557 patients with papillary thyroid cancer were retrospectively analyzed in this study. Principal Component Analysis (PCA) and cluster analysis were conducted using the results from 45 different peripheral blood tests. High-risk and low-risk clusters were defined by comparing the prevalence of metastasis and invasion across different clusters. Key indicators that significantly differed between clusters were identified to examine the correlation between peripheral blood parameters and tumor progression. Results Preoperative examination measures categorized patients into two distinct clusters. Patients in Cluster 0 exhibited a significantly higher rate of tumor metastasis and invasion compared to those in Cluster 1, and were thus categorized as the high-risk group. Following PCA, four principal components showing the most significant differences between the clusters were identified. These components were further analyzed to determine the most crucial peripheral blood parameters. Subsequent multiple logistic regression analysis revealed that parameters such as transaminase levels, white blood cell and red blood cell counts, coagulation time, and thyroid hormones were significantly associated with membership in Cluster 0. Conclusion Several peripheral blood parameters, including transaminase levels, white and red blood cell counts, coagulation time, and thyroid hormones, are linked to the metastasis and invasion of papillary thyroid cancer. These findings suggest that peripheral blood parameters hold potential predictive value for disease progression in PTC, offering a basis for more targeted and effective clinical management.