False negative rate and concordance of ThyGeNEXT®+ThyraMIR® testing with post-thyroidectomy histopathology

Objective: This study aimed to assess the false negative rate (FNR) and concordance of pre-operative ThyGeNEXT®+ThyraMIR® testing in Bethesda category III-V thyroid nodules by comparing results with post-surgical histopathology in thyroid cancer. Methods: A retrospective review was conducted on 19 patients with Bethesda III-V thyroid nodules who underwent ThyGeNEXT®+ThyraMIR® testing followed by total thyroidectomy with histopathology confirming thyroid cancer. Fine needle aspiration (FNA) cytology, molecular test results, post-surgical histopathology and comprehensive genomic profiling reports (when available) were examined. Concordance was assessed by comparing pre-operative test results (mutations or malignant miRNA expression) to post-surgical histopathology. Discrepancies were further explored using Tempus xT genomic profiling for additional mutations and evaluation of tumor heterogeneity. The FNR was calculated accordingly. Results: FNR was 10.5 % and there was a high positive concordance with 89.5 % of cases testing positive for mutations or malignant miRNA classifiers. TERT c.-146C>T, NRAS Q61R, and BRAF V600E were among mutations identified. Comprehensive genomic profiling clarified false negatives, revealing insights into the impact of tumor heterogeneity. The miRNA classifier proved effective in detecting malignancy, in cases with subthreshold and RAS mutations or without common genetic alterations. Reliable results were obtained from diverse specimen types. Conclusions: The low false-negative rate and positive concordance with histopathology highlights the utility of ThyGeNEXT® + ThyraMIR® in enhancing risk stratification and guiding personalized management of indeterminate thyroid nodules and thyroid cancer.

Abstract licence: CC BY-NC-ND

1. 8.

   Performance of a Multigene Genomic Classifier in Thyroid Nodules With Indeterminate Cytology · 2019

25 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.