Personalized Risk Stratification Model of Follicular Lymphoma Patients
Multilayer Model for Personalized Risk Stratification of Follicular Lymphoma Patients
Lead Sponsor: Oncology Institute of Southern Switzerland
|Source||Oncology Institute of Southern Switzerland|
The study aims at developping and validating an integrated clinico-molecular model for an accurate identification of FL patients who are progression free and progressed, respectively, at 24 months after treatment.
Already existing and coded tumor biological material and health-related personal data will be retrospectively collected. FL diagnosis will be confirmed by central pathology review. Tumor somatic mutations, immunoglobulin gene rearrangement and mutation status will be analyzed by targeted deep next generation sequencing of tumor genomic DNA. Gene expression profiling will be performed by targeted RNA-Seq of biopsy-derived RNA.
An immunohistochemistry panel assessing both tumor phenotype and microenvironment cellular composition will be assessed by Tissue macroarray. FISH will be performed to characterize the most recurrent follicular lymphoma chromosomal translocations.
The adjusted association between exposure variables and progression free survival will be estimated by Cox regression. This approach will provide the covariates independently associated with progression free survival that will be utilized in the development of a hierarchical molecular model to predict progression free survival at 24 months. The hierarchical order of relevance in predicting 24 months progression free survival among covariates will be established by recursive partitioning analysis. Overall, this approach will allow the development of a multilayer dynamic model for anticipating progression within 24 months from treatment.
The model developed in the training set will be tested in the validation sets and the model performance (c-index and net reclassification improvement) in the validation set will be compared with that in the training set. The accuracy of the multilayer model in predicting progression free survival at 24 months will be compared against the FLIPI using c-index and net reclassification improvement.
|Start Date||March 1, 2018|
|Completion Date||March 2021|
|Primary Completion Date||March 2021|
Sampling Method: Probability Sample
Inclusion Criteria: - Diagnosis of FL after January 1st, 2004 (chemoimmunotherapy era) - Availability of tumor material collected before initiation of medical therapy - Availability of the baseline and follow-up annotations Exclusion Criteria: - None.
- Diagnosis of FL after January 1st, 2004 (chemoimmunotherapy era)
- Availability of tumor material collected before initiation of medical therapy
- Availability of the baseline and follow-up annotations
Minimum Age: 18 Years
Maximum Age: N/A
Healthy Volunteers: No
Last Name: Davide Rossi, MD, PhD
Phone: +41 091 811 8540
Email: [email protected]
Type: Principal Investigator
Investigator Affiliation: Oncology Institute of Southern Switzerland
Investigator Full Name: Davide Rossi
Investigator Title: MD, PhD, Senior Consultant, Hematology Department
|Has Expanded Access||No|
Label: Training cohort
Description: Cohort of follicular lymphoma patients for the development of the multilayer risk stratification model
Label: Validation cohort
Description: Cohort of follicular lymphoma patients for the validation of the developed multilayer risk stratification model
|Study Design Info||
Observational Model: Cohort
Time Perspective: Retrospective