Bevacizumab and cyclosphosphamide, doxorubicin, vincristine and prednisone in combination for patients with peripheral T-cell or natural killer cell neoplasms: an Eastern Cooperative Oncology Group study (E2404)
Bibliographic record
Abstract
Peripheral T-cell lymphoma (PTCL) and natural killer (NK) cell lymphoma have poor survival with conventional cytotoxic chemotherapy. Because angiogenesis plays an important role in the biology of PTCL, a fully humanized anti-vascular endothelial growth factor (VEGF) antibody, bevacizumab (A), was studied in combination with standard cyclosphosphamide, doxorubicin, vincristine and prednisone (CHOP) chemotherapy (ACHOP) to evaluate its potential to improve outcome in these patients. Patients were treated with 6-8 cycles of ACHOP followed by eight doses of maintenance A (15 mg/kg every 21 days). Forty-six patients were enrolled on this phase 2 study from July 2006 through March 2009. Forty-four patients were evaluable for toxicity and 39 were evaluable for response, progression and survival. A total of 324 cycles (range: 2-16, median 7) were administered to 39 evaluable patients and only nine completed all planned treatment. The overall response rate was 90% with 19 (49%) complete response/complete response unconfirmed (CR/CRu) and 16 (41%) a partial response (PR). The 1-year progression-free survival (PFS) rate was 44% at a median follow-up of 3 years. The median PFS and overall survival (OS) rates were 7.7 and 22 months, respectively. Twenty-three patients died (21 from lymphoma, two while in remission). Grade 3 or 4 toxicities included febrile neutropenia (n = 8), anemia (n = 3), thrombocytopenia (n = 5), congestive heart failure (n = 4), venous thrombosis (n = 3), gastrointestinal hemorrhage/perforation (n = 2), infection (n = 8) and fatigue (n = 6). Despite a high overall response rate, the ACHOP regimen failed to result in durable remissions and was associated with significant toxicities. Studies of novel therapeutics are needed for this patient population, whose clinical outcome remains poor.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".