Postoperative nomogram for predicting involved lymph node in differentiated thyroid carcinoma: an observational study

Area of Science:

• Oncology
• Medical Diagnostics
• Biostatistics

Background:

• Differentiated thyroid cancer (DTC) management requires precise lymph node staging.
• Predicting lymph node metastasis is crucial for tailoring treatment strategies.

Purpose of the Study:

• To develop and validate a nomogram for predicting lymph node involvement in DTC.
• To enhance personalized treatment planning and optimize patient outcomes in DTC.

Main Methods:

• Utilized Least Absolute Shrinkage and Selection Operator (LASSO) and multivariable logistic regression on derivation cohort data.
• Integrated identified predictors into a nomogram, assessing performance in derivation and validation cohorts.
• Evaluated nomogram's discriminative ability, calibration, and clinical utility.

Main Results:

• Identified Thyroglobulin, lymphocyte count, BRAF^V600E, and number of tumor foci as independent predictors.
• Achieved high predictive accuracy: 0.992 in derivation and 0.920 in validation cohorts.
• Demonstrated excellent calibration, discrimination, and clinical applicability.

Conclusions:

• Peripheral lymphocyte counts correlate with lymph node involvement in DTC.
• The developed nomogram aids in personalized postoperative radioactive iodine (RAI) therapy and preoperative assessment for DTC.