Safety and Efficacy of Chop for Treatment of Diffuse Large B-Cell Lymphoma with Different Combination Antiretroviral Therapy Regimens: Sculpt Study
Bibliographic record
Abstract
BACKGROUND: Use of combination antiretroviral therapy (cART) and cyclophosphamide, doxorubicin, vincristine and prednisone (CHOP) with or without rituximab for treatment of diffuse large B-cell lymphoma (DLBCL) in HIV substantially increases response rates but may also increase toxicity, possibly due to antiretroviral-antineoplastic drug interactions. The objective of this study was to evaluate the frequency of complete remission (CR) of DLBCL in patients treated with CHOP while receiving a protease inhibitor (PI) versus a non-PI-based cART. METHODS: A retrospective multicentre pilot study was conducted in HIV-infected patients on cART treated for DLBCL with CHOP between 2002-2010 in three academic hospitals. RESULTS: A total of 34 patients were included with 65% and 35% of patients receiving a PI and non-PI-based cART, respectively. Baseline characteristics between groups were similar; overall 85% were male, median age was 43 years, 50% had an International Prognostic Index (IPI) of 2-3 and median CD4(+) T-cell count was 225 cells/mm(3). CR was achieved in 77% and 58% of patients in the PI and non-PI groups, respectively (P=0.21), with 65% and 63% of patients achieving 2-year overall survival (P=1.00). A multivariate analysis showed that lower IPI score alone was significantly associated with higher CR rates (P=0.05). Toxicity was similar between both groups. CONCLUSIONS: Similar efficacy and toxicity of CHOP was observed in patients receiving a PI and non-PI-based cART.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".