Primary Mediastinal B Cell Lymphoma Treated with CHOP-Like Chemotherapy with or without Rituximab: 5-Year Results of the Mabthera International Trial Group (MInT) Study
Bibliographic record
Abstract
Abstract Abstract 1612 Purpose The aim of this subgroup analysis of the MInT study was to evaluate the impact of chemotherapy and rituximab in primary mediastinal B cell lymphoma (PMBCL) in comparison to other diffuse large B-cell lymphoma (DLBCL). Extended follow-up was needed to establish long-term effects. Patients and Methods Eligible for the randomized open-label MInT study were patients aged 18–60 years with DLBCL who had 0–1 risk factors according to age-adjusted International Prognostic Index (aaIPI), stage II-IV disease, or stage I disease with bulk. Patients were randomly assigned to six cycles of CHOP-like regimens with or without rituximab. Consolidating radiotherapy was given to sites of primary bulky disease. Results Of 824 patients enrolled, 87 had PMBCL and 627 other types of DLBCL. Rituximab increased the rates of complete remission (unconfirmed) in both PMBCL (from 54% to 80%; p =.015) and DLBCL (from 72% to 87%; p<.001). In PMBCL rituximab virtually eliminated progressive disease (PD) (2.5% vs 24%; p =.006), whereas without rituximab PD was more frequent in PMBCL than in DLBCL (24% vs 10%; p =.023). With a median observation time of 62 months for PMBCL and 73 months for DLBCL, the 5-year event-free survival was improved by rituximab for PMBCL (79.1% vs 47.3%; p =.011) and for DLBCL (76.9% vs 59.7%; p <.001). Furthermore, 5-year progression-free survival was improved by rituximab for PMBCL (89.8% vs 60.1%; p=.006) and DLBCL (81.1% vs. 67.8%; p <.001). Overall survival benefit was similar for DLBCL (92.0% vs 80.9%; p <.001) and PMBCL (90.2% vs 78.3%; p =.234). Conclusion Addition of rituximab to 6 cycles of CHOP-like chemotherapy improved long-term outcome for young patients with PMBCL and aaIPI 0–1 and eliminated differences in outcome between PMBCL and DLBCL. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".