喉頭食道癌化学療法導入後の喉頭食道機能不全予測のためのマルチオミクスフレームワーク

Pre-treatment predictors of laryngeal preservation (LP) and survival in advanced laryngeal-hypopharyngeal squamous-cell carcinoma (LHSCC) represent an unmet clinical need.

A multicentric, international, retrospective series of LHSCC patients undergoing induction chemotherapy (IC) within an LP protocol was analyzed. The primary objective was to develop a predictive model by exploiting multiomics data (clinical, genomics, radiomics). Endpoints were laryngo-esophageal dysfunction (LED), response to IC, overall survival (OS), and progression-free survival (PFS). Patients were divided into three groups: group A (no LED); group B (responders to IC with LED); group C (non-responders to IC with LED). Several algorithms (support vector machine, random forest, C5.0, k-nearest neighbors, XGBoost, and naive Bayes) were run and compared in terms of multiclass area under the curve (AUC) score and classification error.

One hundred and ninety-one LHSCC patients were included (median age 60 years, 72% laryngeal, 80% T1-T3, and 58% N+). Responders to IC were 85%, while 66% suffered from LED. The 5-year PFS and OS were 58.4% and 64.7%, respectively. When comparing the three predictive models (clinical, clinical + genomics, clinical + radiomics), the addition of genomics provided the highest AUC. Then, we selected a 64-gene signature and 6 clinical variables (comorbidities, primary site, smoking, T category, N category, performance status) to build up the PRESERVE model. It showed a classification error of 28.9% and an AUC of 87.4%. Risks of major misclassification were low (group A to C, 1.13%; group C to A, 7.38%). Decision analysis confirmed the efficiency of the model.

The PRESERVE model proved to be efficient and accurate in predicting LED and response to IC in LHSCC. External validation is needed before clinical application.