2023 World Conference on Lung Cancer (Posters)-P1.22. Nomogram Prediction for the Detection of Epidermal Growth Factor Receptor Mutation in Lung Adenocarcinoma Patients in Indonesia

P1.22. Nomogram Prediction for the Detection of Epidermal Growth Factor Receptor Mutation in Lung Adenocarcinoma Patients in Indonesia - PDF(Abstract)

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The study presented at the WCLC 2023 conference focused on developing a nomogram for predicting the presence of epidermal growth factor receptor (EGFR) mutation in patients with lung adenocarcinoma in Indonesia. The examination of EGFR mutations is not routinely available to all patients in Indonesia due to limited resources and high costs. Therefore, the researchers aimed to build a non-invasive prediction model using clinical and radiological parameters.<br /><br />The study included 160 treatment-naïve patients with lung adenocarcinomas, divided into two groups - 80 patients with EGFR mutations and 80 patients with wild-type EGFR. Various factors such as age, gender, smoking status, tumor diameter, tumor location, and radiomics features were analyzed. The study found that being female, a non-smoker, having a smaller tumor diameter, being located in the upper lobe, and having bubble-like lucency and air-bronchogram on chest CT scan were independent risk factors for EGFR mutation.<br /><br />Based on these findings, the researchers developed a nomogram model that showed good predictive performance with an area under the curve of 0.993 in the development group and 0.91 in the validation group. The calibration curve also demonstrated a good agreement between predicted and actual probability. At a cut-off point of 246, the nomogram showed high sensitivity, specificity, positive predictive value, and negative predictive value.<br /><br />The study concluded that the nomogram could provide a non-invasive way to predict the risk of EGFR mutation in patients with lung adenocarcinoma in clinical practice. However, further validation of the nomogram is needed in other areas of Indonesia. This research contributes to improving the availability and affordability of genetic testing for EGFR mutations, particularly in resource-limited settings.

Asset Subtitle

Edwin Njoto

Meta Tag

Speaker Edwin Njoto

Topic Pathology & Biomarkers: Genetic Biomarkers

Keywords

WCLC 2023 conference

epidermal growth factor receptor mutation

lung adenocarcinoma

Indonesia

nomogram

non-invasive prediction model

clinical parameters

radiological parameters

EGFR mutations

treatment-naïve patients