Evaluation of Computer-Aided Nodule Assessment and Risk Yield (CANARY) in Korean patients for prediction of invasiveness of ground-glass opacity nodule.

Differentiating the invasiveness of ground-glass nodules (GGN) is clinically important, and several institutions have attempted to develop their own solutions by using computed tomography images. The purpose of this study is to evaluate Computer-Aided Analysis of Risk Yield (CANARY), a validated virtual biopsy and risk-stratification machine-learning tool for lung adenocarcinomas, in a Korean patient population. To this end, a total of 380 GGNs from 360 patients who underwent pulmonary resection in a single institution were reviewed. Based on the Score Indicative of Lung Cancer Aggression (SILA), a quantitative indicator of CANARY analysis results, all of the GGNs were classified as "indolent" (atypical adenomatous hyperplasia, adenocarcinomas in situ, or minimally invasive adenocarcinoma) or "invasive" (invasive adenocarcinoma) and compared with the pathology reports. By considering the possibility of uneven class distribution, statistical analysis was performed on the 1) entire cohort and 2) randomly extracted six sets of class-balanced samples. For each trial, the optimal cutoff SILA was obtained from the receiver operating characteristic curve. The classification results were evaluated using several binary classification metrics. Of a total of 380 GGNs, the mean SILA for 65 (17.1%) indolent and 315 (82.9%) invasive lesions were 0.195±0.124 and 0.391±0.208 (p < 0.0001). The area under the curve (AUC) of each trial was 0.814 and 0.809, with an optimal threshold SILA of 0.229 for both. The macro F1-score and geometric mean were found to be 0.675 and 0.745 for the entire cohort, while both scored 0.741 in the class-equalized dataset. From these results, CANARY could be confirmed acceptable in classifying GGN for Korean patients after the cutoff SILA was calibrated. We found that adjusting the cutoff SILA is needed to use CANARY in other countries or races, and geometric mean could be more objective than F1-score or AUC in the binary classification of imbalanced data.

Assessment of EGFR mutation status in Tunisian patients with pulmonary adenocarcinoma.

BACKGROUND: Despite recent advances, non-small cell lung cancer carries a grim prognosis. For appropriate treatment selection, the updated guidelines recommend broad molecular profiling for all patients with pulmonary adenocarcinoma. Precise histological subtyping and targeted epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) testing are mandatory. METHODS: Herein, we assessed the EGFR mutation status of 26 formalin fixed-paraffin embedded (FFPE) samples of lung adenocarcinoma. Mutational analysis concerned exons 18-21 of EGFR by real-time polymerase chain reaction (Real time-PCR) using the Therascreen EGFR RGQ PCR mutation kit. ALK status was established on 22 among 26 patients using D5F3 antibody with a fully automated Ventana CDx technique. RESULTS: Activating EGFR mutations were found in 3 men among 26 patients (11.5%). Positive ALK expression was found in 2 cases among 22 patients (9.09%). CONCLUSION: Frequency of EGFR mutations in pulmonary adenocarcinomas of our series is similar to that found in the European ones with some particularities. The mutations detected are uncommon. Whereas, we found a high frequency of positive ALK expression in our series compared to frequency reported in literature. Further studies with larger Tunisian series are required to obtain more conclusive results.