Neoplasms

Mouth and Tooth Diseases

Ear, Nose, and Throat Diseases

All Conditions

Symptoms and General Pathology

Rare Diseases

Nasopharyngeal Carcinoma

Carcinoma

Neoplasm Metastasis

Nasopharyngeal Neoplasms

Neoplastic Cells, Circulating

Neoplasms, Glandular and Epithelial

Neoplasms by Histologic Type

Pharyngeal Neoplasms

Otorhinolaryngologic Neoplasms

Head and Neck Neoplasms

Nasopharyngeal Diseases

Pharyngeal Diseases

Stomatognathic Diseases

Otorhinolaryngologic Diseases

the number of circulating tumor cells

Ming-Yuan Chen, MD, PhD

A circulating tumor cell (CTC) count is an established prognostic factor in some malignancies such as metastatic breast cancer. However, the value of CTC in diagnosis and outcome prediction of metastatic nasopharyngeal carcinoma (mNPC) patients is not unknown. Through the observational prospective clinical trial, sensitivity, specificity, positive and negative predictive values of CTC in diagnosis of mNPC patients will be gained. Further, the value of CTC in outcome prediction of mNPC patients will be uncovered.

The blood after separation and purification along with or without CTC.

The Value of Diagnosis and Outcome Prediction in CTC for Metastatic NPC Patients

Using Circulating Tumor Cells to Diagnose and Predict Prognosis in Metastatic Nasopharyngeal Carcinoma Patients

number of true positives divided by (number of true positives plus number of false negatives)

number of true negatives divided by (number of true negatives plus number of false positives)

number of true positives divided by number of positive calls

number of true negatives divided by number of negative calls

Sun Yat-sen University

Prof.

Respiratory Tract (Lung and Bronchial) Diseases

Carcinoma, Squamous Cell

Laryngeal Diseases

Squamous Cell Carcinoma of Head and Neck

Bernd Kremer, MD, PhD

Bernd Lethaus, MD, PhD

Ernst-Jan Speel, MD, PhD

The purpose of the biobank is to enable future genomic based research on this Head and Neck Cancer patient population. The investigators will try to identify tumor factors that will predict cancer-related outcome in order to improve the outcome prediction after treatment in a patient-individualized manner.

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 overall survival.

Primary Objective: To build a biobank of tumor tissue from all HNSCC patients for future genomic analyses.

Secondary Objective: To improve the outcome prediction, based on both clinical factors and tumour gene expression profiles.

Hypothesis:

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.

Study parameters/endpoints:

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.

mucosal HNSCC oropharynx, hypopharynx, larynx, nasopharynx, oral cavity

The Head and Neck Tumor Biobank

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".

Maastricht Radiation Oncology

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Uterine Cervical Neoplasms

Uterine Neoplasms

Genital Neoplasms, Female

Urogenital Neoplasms

Uterine Cervical Diseases

Uterine Diseases

Genital Diseases, Female

Genital Diseases

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

philippe Lambin

Observational study based on the routine clinical treatment and diagnostic course, to correlate imaging features with outcome objectives. Outcome will evaluated as clinical response to the standard treatment and as recurrence and survival in the follow up. The study hypothesis is that data extracted form FDG-PETCT used in the routine clinical practice can predict outcomes following standard treatment.

This study will prospectively collect patients undergoing to the standard diagnostic and treatment protocol in Maastro Clinic. Any difference in the normal procedure will be adopted. The aim is to extrapolate form the PET images some features of the metabolic tumor activity to associate with different outcomes and tumor behaviours.

Prediction of Clinical Response and Outcome in Uterine Cervix Cancer

Predicting Clinical Response and Outcome After Definitive Irradiation With MRI-Guided Adaptive Brachytherapy in Uterine Cervix Cancer

* Standard Uptake Value Max (SUV- defined as the ratio of tissue radioactivity concentration (e.g. in MBq/kg=kBq/g) at time t, c(t), and the injected activity ( in MBq) at the time of injection (t=0) divided by the body weight in kg),
* Metabolic Volume (MV) calculated in cc:volume of the evaluable metabolic activity on the PET scan calculated in a specific Region of Interest (ROI) semiautomatically delineated on the primary tumor in the uterine Cervix

* Standard Uptake Value Max (SUV- defined as the ratio of tissue radioactivity concentration (e.g. in MBq/kg=kBq/g) at time t, c(t), and the injected activity ( in MBq) at the time of injection (t=0) divided by the body weight in kg),
* Ratio of Pre/Post treatment SUV MAX,

* We will apply a high throughput approach to convert medical images to minable data, where it is hypothesized that it will improve tumor characterization and treatment outcome prediction.
* Extracted imaging features consist firstly of global properties, providing information on the first order histogram of voxel intensity values within the tumor VOI.
* Local and regional textural features describing patterns and spatial distribution of voxel intensities, are calculated from respectively gray level co-occurrence and gray level run-length matrix representations. Images will be discretized before texture analysis, which allows for a direct comparison of all calculated textural features between patients. Co-occurrence and gray level run-length matrices are determined considering 26-connected voxels (i.e. voxels were considered to be neighbors in all 13 directions in three dimensions) and a distance of 1 between consecutive voxels. Features derived from the co-occurrence and gray

* GTV volume in cc contoured by 5 different observers on pretreatment scan: the difference in cc between each contour obtained will be scored
* GTV Overlapping fraction rate: the overlapping rate of GTV volume between contours

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
The Value of Diagnosis and Outcome Prediction in CTC for Metastatic NPC Patients	NCT02505139	Nasopharyngeal ...	the number of c...	18 Years - 65 Years	Sun Yat-sen University
The Value of Diagnosis and Outcome Prediction in CTC for Metastatic NPC Patients	NCT02505139	Nasopharyngeal ...	the number of c...	18 Years - 65 Years	Sun Yat-sen University
The Head and Neck Tumor Biobank	NCT01644786	Head and Neck S...		18 Years -	Maastricht Radiation Oncology
The Head and Neck Tumor Biobank	NCT01644786	Head and Neck S...		18 Years -	Maastricht Radiation Oncology
The Value of Diagnosis and Outcome Prediction in CTC for Metastatic NPC Patients	NCT02505139	Nasopharyngeal ...	the number of c...	18 Years - 65 Years	Sun Yat-sen University
Prediction of Clinical Response and Outcome in Uterine Cervix Cancer	NCT01764217	Cervix Cancer		18 Years -	Maastricht Radiation Oncology

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