Clinical trial NCT03436602: Personalized Risk Stratification Model of Follicular Lymphoma Patients
Official title: Multilayer Model for Personalized Risk Stratification of Follicular Lymphoma Patients
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Follicular Lymphoma
Keywords: Personalized risk assessment
Risk stratification model
Lead sponsor: Oncology Institute of Southern Switzerland
Sponsor class: OTHER
Collaborators: name: Azienda Ospedaliero Universitaria Maggiore della Carita
name: Azienda USL Reggio Emilia - IRCCS
name: Institute of Pathology, Locarno, Ticino, Switzerland
First posted: 2018-02-19
Enrollment: 370
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Follicular lymphoma patients

Brief summary: 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.

Detailed description: 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.

Eligibility criteria: 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.

Primary outcomes:
measure: Accuracy of multilayer personalized stratification model
timeFrame: 24 months after first line treatment
Secondary outcomes:
measure: Progression free survival
timeFrame: From treatment start to progression / death / last follow-up, up to 13 years of follow-up
measure: Overall survival
timeFrame: From treatment start to death / last follow-up, up to 13 years of follow-up
measure: Time to transformation
timeFrame: From treatment start to transformation or progression without transformation or death or last follow-up, up to 13 years of follow-up
Other outcomes:
Locations:
city: Reggio Emilia
country: Italy
facility: Arcispedale Santa Maria Nuova, AUSL IRCSS, Hematology Department
state: RE
city: Novara
country: Italy
facility: Azienda Ospedaliera Universitaria Maggiore della Carità
city: Bellinzona
country: Switzerland
facility: Institute of Oncology Research
state: Tessin
city: Locarno
country: Switzerland
facility: Institute of Pathology
state: Tessin
Study officials:
affiliation: Oncology Institute of Southern Switzerland
name: Davide Rossi, MD, PhD
role: PRINCIPAL_INVESTIGATOR
References: