Peripheral T-cell lymphoma, not otherwise specified: a report of 340 cases from the International Peripheral T-cell Lymphoma Project
Bibliographic record
Abstract
The International Peripheral T-cell Lymphoma Project is a collaborative effort to better understand peripheral T-cell lymphoma (PTCL). A total of 22 institutions submitted clinical and pathologic material on 1314 cases. One objective was to analyze the clinical and pathologic features of 340 cases of PTCL, not otherwise specified. The median age of the patients was 60 years, and the majority (69%) presented with advanced stage disease. Most patients (87%) presented with nodal disease, but extranodal disease was present in 62%. The 5-year overall survival was 32%, and the 5-year failure-free survival was only 20%. The majority of patients (80%) were treated with combination chemotherapy that included an anthracycline, but there was no survival advantage. The International Prognostic Index (IPI) was predictive of both overall survival and failure-free survival (P < .001). Multivariate analysis of clinical and pathologic prognostic factors, respectively, when controlling for the IPI, identified bulky disease (≥ 10 cm), thrombocytopenia (< 150 × 10(9)/L), and a high number of transformed tumor cells (> 70%) as adverse predictors of survival, but only the latter was significant in final analysis. Thus, the IPI and a single pathologic feature could be used to stratify patients with PTCL-not otherwise specified for novel and risk-adapted therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".