A phase <scp>II</scp> study of cyclophosphamide, etoposide, vincristine and prednisone ( <scp>CEOP</scp> ) Alternating with Pralatrexate (P) as front line therapy for patients with peripheral T‐cell lymphoma ( <scp>PTCL</scp> ): final results from the T‐ cell consortium trial
Bibliographic record
Abstract
Peripheral T-cell lymphomas (PTCL) have suboptimal outcomes using conventional CHOP (cyclophosphamide, doxorubicin, vincristine, prednisone) chemotherapy. The anti-folate pralatrexate, the first drug approved for patients with relapsed/refractory PTCL, provided a rationale to incorporate it into the front-line setting. This phase 2 study evaluated a novel front-line combination whereby cyclophosphamide, etoposide, vincristine and prednisone (CEOP) alternated with pralatrexate (CEOP-P) in PTCL. Patients achieving a complete or partial remission (CR/PR) were eligible for consolidative stem cell transplantation (SCT) after 4 cycles. Thirty-three stage II-IV PTCL patients were treated: 21 PTCL-not otherwise specified (64%), 8 angioimmunoblastic T cell lymphoma (24%) and 4 anaplastic large cell lymphoma (12%). The majority (61%) had stage IV disease and 46% were International Prognostic Index high/intermediate or high risk. Grade 3-4 toxicities included anaemia (27%), thrombocytopenia (12%), febrile neutropenia (18%), mucositis (18%), sepsis (15%), increased creatinine (12%) and liver transaminases (12%). Seventeen patients (52%) achieved a CR. The 2-year progression-free survival and overall survival, were 39% (95% confidence interval 21-57) and 60% (95% confidence interval 39-76), respectively. Fifteen patients (45%) (12 CR) received SCT and all remained in CR at a median follow-up of 21·5 months. CEOP-P did not improve outcomes compared to historical data using CHOP. Defining optimal front line therapy in PTCL continues to be a challenge and an unmet need.
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 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".