A multiomic framework for predicting laryngo-esophageal dysfunction following induction chemotherapy in hypopharyngeal-laryngeal carcinoma
| dc.contributor.author | Mattavelli, Davide | |
| dc.contributor.author | Compagnoni, Micaela | |
| dc.contributor.author | Calza, Stefano | |
| dc.contributor.author | Plana Serrahima, Maria | |
| dc.contributor.author | Mesía, Ricard | |
| dc.contributor.author | Chiocca, Susanna | |
| dc.contributor.author | Bossi, Paolo | |
| dc.contributor.author | PRESERVE Consortium | |
| dc.date.accessioned | 2026-02-23T13:29:00Z | |
| dc.date.available | 2026-02-23T13:29:00Z | |
| dc.date.issued | 2025-12-29 | |
| dc.date.updated | 2026-02-09T15:14:37Z | |
| dc.description.abstract | Background: Pre-treatment predictors of laryngeal preservation (LP) and survival in advanced laryngealhypopharyngeal squamous-cell carcinoma (LHSCC) represent an unmet clinical need. Materials and methods: 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. Results: 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. Conclusions: 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. | |
| dc.format.extent | 10 p. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.issn | 2059-7029 | |
| dc.identifier.pmid | 41468687 | |
| dc.identifier.uri | https://hdl.handle.net/2445/227221 | |
| dc.language.iso | eng | |
| dc.publisher | Elsevier BV | |
| dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.1016/j.esmoop.2025.105933 | |
| dc.relation.ispartof | ESMO Open, 2025, vol. 11, num. 1, 105933 | |
| dc.relation.uri | https://doi.org/10.1016/j.esmoop.2025.105933 | |
| dc.rights | cc-by-nc-nd (c) Mattavelli, Davide et al., 2025 | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.source | Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL)) | |
| dc.subject.classification | Laringoscòpia | |
| dc.subject.classification | Càncer de pulmó | |
| dc.subject.classification | Malalties de l'orella | |
| dc.subject.other | Laryngoscopy | |
| dc.subject.other | Lung cancer | |
| dc.subject.other | Ear diseases | |
| dc.title | A multiomic framework for predicting laryngo-esophageal dysfunction following induction chemotherapy in hypopharyngeal-laryngeal carcinoma | |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion |
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