Sunitinib in Relapsed or Refractory Diffuse Large B Cell Lymphoma: Results of a Phase II Multi-Center Study of the NCIC Clinical Trials Group.
Bibliographic record
Abstract
Abstract Abstract 2729 Poster Board II-705 Background: There are limited effective treatment options for patients with diffuse large B cell lymphoma who relapse post autologous stem cell transplant or are transplant-ineligible. The detection of vascular endothelial growth factor (VEGF )A, B and C isoforms and their receptors on many large cell lymphoma samples suggests that the VEGF pathway is critically important and may contribute to disease progression. Sunitinib maleate, is an orally bioavailable inhibitor of VEGF receptor-1 (VEGFR-1), -2, and -3, PDGFR-α and β as well as KIT, FLT3, RET and CSF-1 (Chow, LQ JCO 2007). We tested the efficacy, safety and biomarker activity of sunitinib in patients with relapsed diffuse large B cell lymphoma in a multi-center prospective phase II study. Methods: Eligibility included age 18 or older, histologically confirmed relapsed or refractory diffuse large B-cell (DLBCL), primary mediastinal (PMBCL), or transformed indolent lymphoma, at least one and no more than 2 prior chemotherapy regimens (one anthracycline-containing). The primary endpoint was objective response defined by 1999 Cheson criteria. The secondary endpoints were progression-free and overall survival, toxicity and the effect of sunitinib on peripheral blood circulating endothelial cells (CECs) and their precursors (CEPs). Patients self administered sunitinib 37.5 mg po daily with no breaks in 4 week cycles for up to 1 year. CT imaging was performed every 2 cycles and CEC/CEP assays were done at baseline, day 1 of cycles 2, 3 then q 3 months thereafter. A Simon 2-stage design was used with at least 1 response needed after 15 evaluable patients to complete a planned accrual of 25 patients total. Results: Between Feb 2007 and September 2008 we enrolled 19 patients at 7 Canadian sites - 17 were eligible and are evaluable for toxicity and 15 are evaluable for response. The median age was 65 and patients were a median of 20.3 months(m) from diagnosis (range 5.8–132 m). Fourteen (82%) had a diagnosis of DLBCL, 10 (58%) had responded to their preceding line of chemotherapy - 5 (29%) had relapsed post high dose chemotherapy. The median number of cycles of sunitinib received was 2 (1–5) with only 5 patients remaining on drug for 3 or more cycles. Only 35% of patients received > 90% planned dose intensity with 14 patients missing doses and 5 undergoing dose reductions necessitated by toxicities. Hematological toxicity (grade 3 neutropenia in 5 pts, grades 3–4 thrombocytopenia in 6 pts) and was the most common reason for dose omission. Of the 15 evaluable pts, no objective responses were seen, and 9 achieved stable disease (median duration 3.4 m); and 6 had primary progressive disease. As a result, the study was closed at the end of the first stage. With limited serial sampling, there was no discernable relationship between the change in absolute or apoptotic CEC over time with clinical response as measured by best response or change in bi-dimensional measurements. Conclusions: Sunitinib 37.5 mg po daily showed no evidence of anti-tumour activity in relapsed/refractory large B cell lymphoma and is associated with greater than expected hematological toxicity. Disclosures: Buckstein: Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Off Label Use: It is being tested in NHL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".