Development and validation of the nomogram based on ultrasound, thyroid stimulating hormone, and inflammatory marker in papillary thyroid carcinoma: a case-control study.

Abstract

The increase in the number of thyroid cancer cases in recent years has increased not only the medical burden but also the potential for overtreatment. Therefore, it is crucial to distinguish papillary thyroid cancer from benign thyroid nodules before surgery when treating thyroid nodules. The patients were divided into two groups: 117 patients made up the validation cohort and 414 patients made up the primary cohort. As a result of the primary cohort, a preoperative prediction model was developed, which was then validated externally in the validation cohort. Preoperative thyrotropin (thyroid stimulating hormone, TSH), systemic immune-inflammation index (SII), lymphocyte-to-monocyte ratio (LMR), and ultrasonographic features were recorded in both groups. As predictors for the model, the preoperative blood levels of TSH, SII, LMR, echogenicity, margin, calcification, composition, taller-than-wide, and age were chosen. This was the regression equation: Y = -0.070 × (age) + 1.511 × (echogenicity) + 1.664 × (margin) + 1.003 × (calcification) + 0.939 × (composition) + 2.964 × (tall than wide) + 0.305 × (TSH) + 0.558 × (SII) - 1.271 × (LMR) + 0.327. Papillary thyroid carcinoma (PTC) was predicted positively with values of Y ≥0.808. The prediction model's accuracy, sensitivity, and specificity were 88.2%, 85.1%, and 94.9%, respectively. The area under the receiver operating characteristic (ROC) curve was 0.961. The model's external validation produced satisfactory results with accuracy, sensitivity, and specificity of 85.5%, 90.9%, and 75.5%, respectively. Using the preoperative TSH, SII, LMR, and ultrasonographic characteristics, a straightforward and accurate preoperative prediction model for PTC has been developed and validated. The preoperative assessment of PTC in clinical application is enhanced by this approach.