title: Forecasting the performance status of head and neck cancer patient treatment by an interval arithmetic pruned perceptron.
abstract: The integration of chemotherapy and radiotherapy for the treatment of advanced head and neck cancer is still a matter of clinical investigation. An important limitation is that the concomitant administration of chemotherapy and radiotherapy still induces severe toxicity. In this paper, a simple artificial neural network is used to predict, on the basis of biological and clinical data, if the cumulative toxicity of the combined chemo-radiation treatment itself would be tolerated. The resulting method, tested on clinical data from a phase II trial, proved to be able to forecast which patients will tolerate a combined chemo-radiotherapeutic approach. This result should open a new perspective in the clinical approach, by supplying a potential predictive indicator for toxicity.
authors.affiliation: Istituto per i Circuiti Elettronici-Consiglio Nazionale delle Ricerche, Genova, Italy.
authors.forename: Gian Paolo
authors.initials: GP
authors.lastname: Drago
authors.forename: Ernesto
authors.initials: E
authors.lastname: Setti
authors.forename: Lisa
authors.initials: L
authors.lastname: Licitra
authors.forename: Diego
authors.initials: D
authors.lastname: Liberati
mesh_terms: D000970:Antineoplastic Agents / Q000009:adverse effects / Q000627:therapeutic use; D017322:Clinical Trials, Phase II as Topic; D006258:Head and Neck Neoplasms / Q000188:drug therapy* / Q000401:mortality / Q000532:radiotherapy*; D006801:Humans; D017567:Karnofsky Performance Status / Q000706:statistics & numerical data*; D015233:Models, Statistical; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D018714:Radiotherapy, Adjuvant; D012307:Risk Factors; D016019:Survival Analysis; D016896:Treatment Outcome
chemical_list: D000970:Antineoplastic Agents