Incidence, predictors and significance of severe toxicity in patients with human immunodeficiency virus-associated Hodgkin lymphoma
Bibliographic record
Abstract
The incidence of Hodgkin lymphoma (HL) is rising among individuals infected with human immunodeficiency virus (HIV). Standard treatment regimens include vinblastine, which is known to cause neurotoxicity (NT) and is metabolized by cytochrome 3A4 (CYP3A4). This is inhibited by protease inhibitors (PIs), possibly increasing vinblastine exposure. There is little information on how interactions affect clinical outcome. A retrospective review of 32 patients with HIV-HL receiving chemotherapy with curative intent was performed to identify the frequency and risk factors for NT, hematologic toxicity (HT) and lung toxicity (LT). Treatment was: ABVD (doxorubicin, bleomycin, vinblastine, dacarbazine) in 90%, MOPP/ABV (mechlorethamine, vincristine, procarbazine, prednisone/doxorubicin, bleomycin, vinblastine) in 10% and HAART (highly active anti-retroviral therapy) in 63%. Seventeen potential risk factors and 18 individual anti-retroviral (ARV) agents were examined, and only ritonavir or lopinavir use was found to have a significant association with toxicity. Grade 3-4 NT occurred in five patients, grade 3-4 HT in 17, infectious complications in 10 and bleomycin LT in three. Ritonavir and lopinavir use was associated with grade 3-4 NT (p = 0.03 and p = 0.01, respectively), and ritonavir with any HT (p = 0.04). Patients with HIV-HL experienced an increased incidence of NT and possibly HT. The use of ritonavir or lopinavir was associated with NT, suggesting a clinically significant interaction with vinblastine. Prospective pharmacokinetic studies to devise a rational dosing strategy for vinblastine in patients receiving ritonavir/lopinavir are warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".