Diagnostic challenges in the assessment of thyroid neoplasms using nuclear features and vascular and capsular invasion: a multi-center interobserver agreement study.

Background: The diagnosis of thyroid neoplasms necessitates the identification of distinct histological features. Various education/hospital centers located in cities across Indonesia likely result in discordances among pathologists when diagnosing thyroid neoplasms. Methods: This study examined the concordance among Indonesian pathologists in assessing nuclear features and capsular and vascular invasion of thyroid tumors. Fifteen pathologists from different centers independently assessed the same 14 digital slides of thyroid tumor specimens. All the specimens were thyroid neoplasms with known BRAFV600E and RAS mutational status, from a single center. We evaluated the pre- and post-training agreement using the Fleiss kappa. The significance of the training was evaluated using a paired T-test. Results: Baseline agreement on nuclear features was slight to fair based on a 3-point scoring system (k = 0.14 to 0.28) and poor to fair based on an eight-point system (k = -0.02 to 0.24). Agreements on vascular (κ = 0.35) and capsular invasion (κ = 0.27) were fair, whereas the estimated molecular type showed substantial agreement (κ = 0.74). Following the training, agreement using the eight-point system significantly improved (p = 0.001). Conclusions: The level of concordance among Indonesian pathologists in diagnosing thyroid neoplasm was relatively poor. Consensus in pathology assessment requires ongoing collaboration and education to refine diagnostic criteria.

Developing Models to Predict BRAFV600E and RAS Mutational Status in Papillary Thyroid Carcinoma Using Clinicopathological Features and pERK1/2 Immunohistochemistry Expression.

The Cancer Genome Atlas (TCGA) has classified papillary thyroid carcinoma (PTC) into indolent RAS-like and aggressive BRAF-like based on its distinct driver gene mutations. This retrospective study aimed to assess clinicopathology and pERK1/2 expression variations between BRAF-like and RAS-like PTCs and establish predictive models for BRAFV600E and RAS-mutated PTCs. A total of 222 PTCs underwent immunohistochemistry staining to assess pERK1/2 expression and Sanger sequencing to analyze the BRAF and RAS genes. Multivariate logistic regression was employed to develop prediction models. Independent predictors of the BRAFV600E mutation include a nuclear score of 3, the absence of capsules, an aggressive histology subtype, and pERK1/2 levels exceeding 10% (X2 = 0.128, p > 0.05, AUC = 0.734, p < 0.001). The RAS mutation predictive model includes follicular histology subtype and pERK1/2 expression > 10% (X2 = 0.174, p > 0.05, AUC = 0.8, p < 0.001). We propose using the prediction model concurrently with four potential combination group outcomes. PTC cases included in a combination of the low-BRAFV600E-scoring group and high-RAS-scoring group are categorized as RAS-like (adjOR = 4.857, p = 0.01, 95% CI = 1.470-16.049). PTCs included in a combination of the high-BRAFV600E-scoring group and low-RAS-scoring group are categorized as BRAF-like PTCs (adjOR = 3.091, p = 0.001, 95% CI = 1.594-5.995). The different prediction models indicate variations in biological behavior between BRAF-like and RAS-like PTCs.