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Rituximab Resistant Follicular Lymphoma: Predictors of Rituximab Resistance, Incidence of Transformation and Prognosis

2011· article· en· W2549385334 on OpenAlexaff
Lee Mozessohn, Matthew C. Cheung, Michael Crump, Rena Buckstein, Neil L. Berinstein, Kevin Imrie, John Kuruvilla, Eugenia Piliotis, Vishal Kukreti

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsRituximabMedicineFollicular lymphomaInternal medicineMaintenance therapyOncologyLymphomaSurgeryGastroenterologyChemotherapy

Abstract

fetched live from OpenAlex

Abstract Abstract 4981 Follicular lymphoma (FL) is an indolent lymphoma characterized by slow growth, initial response to treatment with inevitable relapse. Recent trials have demonstrated improved progression free survival (PFS) with rituximab-containing induction, maintenance rituximab (MR) or both. However, a small subset of patients (pts) will show disease progression during the induction or maintenance phase. We evaluated rituximab resistance (RR) including incidence, predictors, rate of transformation and prognosis for pts demonstrating RR. We defined RR as disease progression during induction, maintenance or within 6 months of last dose of rituximab. We retrospectively identified pts who received rituximab for symptomatic FL from July 2006 to April 2010 at 2 regional cancer centres. Those with a diagnosis of FL grades 1, 2 or 3a with first exposure to rituximab (induction, maintenance or both) were included. Exclusion criteria included FL grade 3b and previous rituximab exposure. Progression was ascertained from clinical notes or radiological investigation as per IWG Criteria (1999). Transformation was defined by confirmatory biopsy and clinical suspicion of transformation was also recorded (nodal growth, rapid rise in LDH or new B symptoms). PFS and overall survival (OS) were measured from initiation of rituximab induction. Log-rank statistics were used to identify univariate predictors for RR and Cox regression for multivariate analysis with outcome as time to early progression (RR). Of the pts screened, 132 met inclusion criteria (112 pts receiving primary therapy, 20 for ≥ 2nd line therapy); 22 pts (16.7%) demonstrated RR. Incidence of RR was similar for pts receiving primary therapy (17.0%). Pt characteristics for rituximab sensitive (RS) and RR groups are shown in Table 1. From induction, median follow-up was 33 months (range 9 to 61 months). In univariate analysis, high risk FLIPI score at induction was predictive of RR (p = 0.002). Partial response to induction (p = 0.082) trended to significance. Other factors not predictive of RR included: age, gender, high grade histology (grade 3a), previous chemotherapy received, time from diagnosis to induction therapy and anthracycline-based induction. A Cox regression model was constructed with FLIPI score and anthracycline-based induction as covariates. FLIPI score was independently and significantly predictive of RR (HR 2.43; 95% CI, 1.4 to 4.1; p = 0.001). Of the 22 pts who were RR, 18 (81.8%) required subsequent chemotherapy with only 9 achieving at least a partial response. Ten pts (45.5%) required more than 1 line of chemotherapy post-progression with a median time to next line of therapy of 9 months (95% CI, 2.9 to 15.1; see figure). Among the RR pts, 5 (22.7%) showed evidence of transformation on biopsy at initial resistance and an additional 3 (13.6%) were clinically suspected. Within 12 months of resistance, a further 3 pts in the RR group demonstrated biopsy-proven transformation. Overall, 10 pts (45.5%) transformed (biopsy-proven) with no transformation in the RS group. During follow-up, 9 deaths occurred, all in those with RR, 5 following biopsy-proven transformation. The median PFS and OS in the RR group were 17 months and 47 months, respectively. Table 1 Characteristics RS (n = 110) RR (n = 22) Age (MEAN) 58.9 58.9 Gender (females) 43.6% 40.9% High histological grade (3a) 8.4% 9.1% Previous treatment (yes) 15.5% 13.6% Alkylator 11.8% 13.6% Number of lines of previous treatment >1 4.5% 4.5% Mean time from diagnosis to induction (months) 30.3 28.1 Induction chemo R-CVP based 78.2% 86.4% R-CHOP based 18.2% 9.1% Other 3.6% 4.5% Response to induction PR 77.3% 72.7% CRu 12.7% 0% CR 10.0% 4.5% SD/PD 0% 22.7% FLIPI score at induction Low (0, 1, 2) 57.8% 18.2% Intermediate (3) 26.6% 40.9% High (4 or 5) 15.6% 40.9% Stage 3 or 4 88.2% 100% High tumor burden at diagnosis (GELF criteria) 43.6% 40.9% We demonstrated that the incidence of rituximab resistance in FL on first exposure to rituximab in our population was 16.7%. FLIPI score was predictive for RR and was independent of anthracycline-based induction regimens. Pts with RR had a high rate of histologic transformation (36.3% within 12 months post RR) and a shorter PFS/OS with a poor response to next therapy. Biopsies to confirm transformation should be performed in all pts demonstrating RR, and new therapies are needed for this group of pts. Disclosures: Crump: Ortho Johnson & Johnson: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Millennium Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees. Kukreti:Celgene: Honoraria; Ortho Biotech: Honoraria; Roche: Honoraria.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.216
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2011
Admission routes1
Has abstractyes

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