Autologous stem cell transplantation for anaplastic large‐cell lymphomas: results of a prospective trial
Bibliographic record
Abstract
Autologous stem cell transplantation (ASCT) in the front line treatment of non-Hodgkin's lymphoma (NHL) remains controversial. Anaplastic large-cell lymphoma (ALCL) is known to have its own clinical and biological features. The outcome of ALCL patients treated with high-dose chemotherapy and ASCT as part of their first-line therapy was analysed in 202 intermediate or high-grade NHL patients in a prospective randomized trial. First-line chemotherapy comprised two alternating anthracycline-containing regimens. Responding patients were autografted after a BEAM (BCNU, cytarabine, etoposide and melphalan) regimen. Patients with bulky or residual masses were irradiated. Fifteen patients with ALCL were identified by morphological and immunological features (CD30 was expressed in 14 out of 15 patients, three patients expressed B-cell markers, five patients expressed T-cell markers and seven patients did not express cell markers). Anaplastic lymphoma kinase (ALK) expression was confirmed in seven cases. The median age was 39 years with a predominant male sex ratio (2.75). Thirteen patients were stage >/= III and six presented with two or more adverse prognostic factors. According to the international age-adjusted prognostic index, the expected complete remission (CR), event-free survival (EFS) and overall survival (OS) rates were 69%, 71% and 69%. Two deaths were observed (one due to interstitial pneumonitis, one due to pulmonary carcinoma). All patients entered CR, no relapse occurred and EFS and survival reached 87% with a follow-up of more than 5 years. These results differ significantly from those observed in the other 176 lymphoma patients: event-free survival was only 53 +/- 5% and OS reached 60 +/- 4% with a median follow-up of 56 months (P = 0.006). Intensified chemotherapy with autologous stem cell support appeared effective in the treatment of ALCL, offering patients the real chance of a cure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".