Systemic anaplastic large‐cell lymphoma: Results from the non‐Hodgkin's lymphoma classification project
Bibliographic record
Abstract
Anaplastic large-cell lymphoma (ALCL) is a heterogeneous process that may have a T-cell, B-cell, or indeterminant (null) phenotype and which may or may not express the anaplastic lymphoma kinase (ALK) oncoprotein. Because the clinical significance of these variants of ALCL is unclear, we evaluated the cases of ALCL-T/null and ALCL-B identified in the Non-Hodgkin's Lymphoma Classification Project. We evaluated 1,378 cases of non-Hodgkin's lymphoma (NHL), and a consensus diagnosis of ALCL-T/null was made in 33 patients (2.4%) with a diagnostic accuracy of 85%. Compared to 96 patients with other forms of peripheral T-cell lymphoma (PTCL), those with ALCL-T/null were significantly younger, less likely to have advanced-stage disease or bone marrow involvement, more likely to have a low International Prognostic Index score, and had a significantly better survival. Among those with ALCL-T/null, there were no significant differences in the clinical features or survival on the basis of ALK expression. A consensus diagnosis of ALCL-B was made in 15 patients (1.1%), and the diagnostic accuracy was 67%. However, compared to 366 patients with other forms of diffuse large B-cell lymphoma (DLBCL), those with ALCL-B were no different with regard to clinical features or survival. We conclude that patients with ALCL-T/null have favorable prognostic features and excellent survival and should be separated from those with other forms of PTCL for prognostic and therapeutic purposes. In contrast, patients with ALCL-B appear to be similar to those with other forms of DLBCL.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".