Comparative outcomes for mature T-cell and NK/T-cell lymphomas in people with and without HIV and to AIDS-defining lymphomas
Bibliographic record
Abstract
There are no studies comparing the prognosis for mature T-cell lymphoma (TCL) in people with HIV (PWH) to people without HIV (PWoH) and to AIDS-defining B-cell lymphomas (A-BCLs) in the modern antiretroviral therapy era. North American AIDS Cohort Collaboration on Research and Design and Comprehensive Oncology Measures for Peripheral T-cell Lymphoma Treatment are cohorts that enroll patients diagnosed with HIV and TCL, respectively. In our study, 52, 64, 101, 500, and 246 PWH with histologic confirmation of TCL, primary central nervous system lymphoma, Burkitt’s lymphoma, diffuse large B-cell lymphoma (DLBCL), and Hodgkin’s lymphoma (HL), respectively, and 450 TCLs without HIV were eligible for analysis. At the time of TCL diagnosis, anaplastic large-cell lymphoma (ALCL) was the most common TCL subtype within PWH. Although PWH with TCL diagnosed between 1996 and 2009 experienced a low 5-year survival probability at 0.23 (95% confidence interval [CI]: 0.13, 0.41), we observed a marked improvement in their survival when diagnosed between 2010 and 2016 (0.69; 95% CI: 0.48, 1; P = .04) in contrast to TCLs among PWoH (0.45; 95% CI: 0.41, 0.51; P = .53). Similarly, PWH with ALCLs diagnosed between 1996 and 2009 were associated with a conspicuously inferior 5-year survival probability (0.17; 95% CI: 0.07, 0.42) and consistently lagged behind A-BCL subtypes such as Burkitt’s (0.43; 95% CI:0.33, 0.57; P = .09) and DLBCL (0.17; 95% CI: 0.06, 0.46; P = .11) and behind HL (0.57; 95% CI: 0.50, 0.65; P < .0001). Despite a small number, those diagnosed between 2010 and 2016 experienced a remarkable improvement in survival (0.67; 95% CI: 0.3, 1) in comparison with PWoH (0.76; 95% CI: 0.66, 0.87; P = .58). Thus, our analysis confirms improved overall survival for aggressive B- and T-cell malignancies among PWH in the last decade.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".