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Personalized Risk Stratification Model of Follicular Lymphoma Patients

Multilayer Model for Personalized Risk Stratification of Follicular Lymphoma Patients

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03436602
Enrollment
370
Registered
2018-02-19
Start date
2018-03-01
Completion date
2026-10-31
Last updated
2025-11-18

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Follicular Lymphoma

Keywords

Personalized risk assessment, Risk stratification model

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.

Interventions

None listed

Sponsors

Azienda Ospedaliero Universitaria Maggiore della Carita
CollaboratorOTHER
Azienda USL Reggio Emilia - IRCCS
CollaboratorOTHER_GOV
Institute of Pathology, Locarno, Ticino, Switzerland
CollaboratorUNKNOWN
Oncology Institute of Southern Switzerland
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

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.

Design outcomes

Primary

MeasureTime frameDescription
Accuracy of multilayer personalized stratification model24 months after first line treatmentAssessment of multilayer personalized stratification model accuracy in the identification of patients who are progression free at 24 months after first line therapy plus the proportion of patients correctly identified as progressed within 24 months after first line therapy

Secondary

MeasureTime frameDescription
Progression free survivalFrom treatment start to progression / death / last follow-up, up to 13 years of follow-upTime elapsed from treatment start to progression (event), death (event) or last follow-up (censoring)
Overall survivalFrom treatment start to death / last follow-up, up to 13 years of follow-upTime elapsed from treatment start to death (event) or last follow-up (censoring)
Time to transformationFrom treatment start to transformation or progression without transformation or death or last follow-up, up to 13 years of follow-upTime elapsed between treatment start and transformation (event), progression without transformation (censoring), death (censoring) or last follow-up (censoring)

Countries

Italy, Switzerland

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026