Predicting thyroid nodule malignancy at several prevalence values with a combined Bethesda-molecular test

Area of Science:

• Endocrinology
• Oncology
• Genetics

Background:

• Fine-needle aspiration cytology (FNAC) for thyroid nodules yields indeterminate results in up to 30% of cases using the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC).
• Accurate preoperative diagnosis of thyroid nodule malignancy is crucial for appropriate patient management and avoiding unnecessary surgeries.

Purpose of the Study:

• To develop and validate a combined Bethesda-molecular predictor for improved accuracy in diagnosing thyroid nodule malignancy.
• To assess the performance of this combined predictor in reducing unnecessary thyroidectomies.

Main Methods:

• A molecular test utilizing a transcriptomic array of 20 genes was performed on FNAC samples from 128 thyroid nodules.
• A logistic regression model identified an optimal set of seven genes for the molecular signature.
• The combined predictor (TBSRTC + molecular) performance was compared to TBSRTC alone using ROC curve analysis and evaluated across different malignancy prevalence and benefit-to-harm ratios (B/Hr).

Main Results:

• The combined predictor demonstrated a higher area under the ROC curve (AUC) of 93.5% compared to TBSRTC alone (P = 0.004).
• In the study population with 36% malignancy prevalence and B/Hr of 1, the combined predictor achieved 95% specificity and 76% sensitivity.
• For indeterminate nodules (30% malignancy prevalence), the predictor allowed avoidance of 64% of unnecessary surgeries with a B/Hr of 4 (favoring sensitivity), at the cost of one false-positive result.

Conclusions:

• The combined Bethesda-molecular predictor significantly enhances the accuracy of thyroid nodule malignancy detection.
• This predictor offers a valuable tool for preoperative diagnosis, considering malignancy prevalence and benefit-to-harm ratios.
• Implementation of this predictor can lead to a substantial reduction in unnecessary thyroidectomies.