ALK− anaplastic large-cell lymphoma is clinically and immunophenotypically different from both ALK+ ALCL and peripheral T-cell lymphoma, not otherwise specified: report from the International Peripheral T-Cell Lymphoma Project
Bibliographic record
Abstract
The International Peripheral T-Cell Lymphoma Project is a collaborative effort designed to gain better understanding of peripheral T-cell and natural killer (NK)/T-cell lymphomas (PTCLs). A total of 22 institutions in North America, Europe, and Asia submitted clinical and pathologic information on PTCLs diagnosed and treated at their respective centers. Of the 1314 eligible patients, 181 had anaplastic large-cell lymphoma (ALCL; 13.8%) on consensus review: One hundred fifty-nine had systemic ALCL (12.1%) and 22 had primary cutaneous ALCL (1.7%). Patients with anaplastic lymphoma kinase-positive (ALK(+)) ALCL had a superior outcome compared with those with ALK(-) ALCL (5-year failure-free survival [FFS], 60% vs 36%; P = .015; 5-year overall survival [OS], 70% vs 49%; P = .016). However, contrary to prior reports, the 5-year FFS (36% vs 20%; P = .012) and OS (49% vs 32%; P = .032) were superior for ALK(-) ALCL compared with PTCL, not otherwise specified (PTCL-NOS). Patients with primary cutaneous ALCL had a very favorable 5-year OS (90%), but with a propensity to relapse (5-year FFS, 55%). In summary, ALK(-) ALCL should continue to be separated from both ALK(+) ALCL and PTCL-NOS. Although the prognosis of ALK(-) ALCL appears to be better than that for PTCL-NOS, it is still unsatisfactory and better therapies are needed. Primary cutaneous ALCL is associated with an indolent course.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".