DEVELOPMENT AND INTERNAL VALIDATION OF A PREDICTIVE MODEL FOR INDIVIDUAL CANCER RISK ASSESSMENT FOR THYROID NODULES.

Objective: The objective of this study was to develop and validate a predictive model for assessment of the individual risk of malignancy of thyroid nodules based on clinical, ultrasound, and analytical variables. Methods: A retrospective case-control study was carried out with 542 patients whose thyroid nodules were analyzed at our endocrinology department between 2013 and 2018 while undergoing treatment for thyroidectomy. Starting with a multivariate logistic regression analysis, which included clinical, analytical, and ultrasound variables, a predictive model for thyroid cancer (TC) risk was devised. This was then subjected to a cross-validation process, using resampling techniques. Results: In the final model, the independent predictors of the risk of malignancy were: being male, age of the extremes, a family history of TC, a TSH level > 4.7 mcU/L, the presence of autoimmune thyroiditis, a solid consistency, hypoechogenicity, irregular or microlobed borders, nodules that are taller than they are wide, microcalcifications, and suspicious adenopathy. With a cut-off point of 50% probability of thyroid cancer, the predictive model had an area under the ROC curve of 0.925 (95% confidence interval 0.898-0.952). Finally, using the ten-fold cross-validation method, the accuracy of the model was found to be 88.46%, with a kappa correlation coefficient of 0.62. Conclusions: A predictive model for the individual risk of malignancy of thyroid nodules was developed and validated using clinical, analytical, and ultrasound variables. An online calculator ( https://obgynreference.shinyapps.io/calccdt/ ) was developed from this model to be used by clinicians to improve decision-making in patients with thyroid nodules.