STORAGE OF HEAD AND NECK TUMOR SAMPLES IN A BIOBANK FOR FUTURE GENOMIC-BASED RESEARCH AIMING AT IMPROVED OUTCOME PREDICTION "THE HEAD AND NECK TUMOR BIOBANK"
This is a prospective, non-interventional longitudinal study in patients with HNSCC.
Patients will have their normal routine workup including the standard panendoscopy, during
which usually multiple biopsies for diagnostic histo-pathology are obtained. Part of one of
these biopsies will be stored in the HN Tumor Biobank. There will be no change in the
subsequent proposed treatment, which may consist of primary surgery (with or without
postoperative (chemo-) radiation) or definitive (chemo-) radiation.
The primary and general objective of this project is to develop, validate, and improve
predictive models for different endpoints that are relevant for patients after curatively
intended treatment of HNSCC. These endpoints include loco-regional tumour control and
Primary Objective: To build a biobank of tumor tissue from all HNSCC patients for future
Secondary Objective: To improve the outcome prediction, based on both clinical factors and
tumour gene expression profiles.
Our general hypothesis is that a more accurate estimation of locoregional control and
overall survival can be achieved when prognostic factors are taken into account different
from than the currently used 'classical' prognostic factors, such as TNM-stage.
The investigators hypothesize that the final outcome of this project will allow us to
improve the performance of predictive models for HNSCC. The performance of our prediction
models will be quantified by AUC for binary outcome measures and with the c-statistic for
survival analysis. The ultimate objective will be to achieve an AUC of at least 0.90. Such a
performance will allow us to build a Decision Support System based on these predictive
models that provides information to physicians with regard to the probability of
loco-regional failure and overall survival in individual patients.
Because no specific gene-signature has yet been defined that is applicable to a large
population of HNSCC patients, no specific endpoint can be named.
However, the main study endpoint will be the accuracy of a certain gene-signature that may
contribute or rather improve the outcome prediction of patients. Outcome is defined as
locoregional control and/or survival. The outcome of the patients is currently recorded in
the electronic medical charts of azM and of Maastro Clinic and at the time of analysis,
these clinical outcome data will be coupled blinded to the data generated from the
tumor-biopsy analysis The goal is to achieve an AUC of at least 0.90. Such a performance
will allow us to build a Decision Support System.
Observational Model: Cohort, Time Perspective: Prospective
Philppe Lambin, prof
Netherlands: Medical Ethics Review Committee (METC)