Exploratory Analysis of Factors Influencing Efficacy and Safety of Camidanlumab Tesirine: Data from the Open-Label, Multicenter, Phase 2 Study of Patients with Relapsed or Refractory Classical Hodgkin Lymphoma (R/R cHL)
Bibliographic record
Abstract
INTRODUCTION: Despite most patients with cHL being cured with standard therapies, a proportion of patients are refractory or relapse after first- and second-line treatments (1L/2L), including stem cell transplantation, and there are limited treatment options available after failure of brentuximab vedotin (BV) and PD-1 blockade. Camidanlumab tesirine (Cami) is an antibody-drug conjugate comprising an anti-CD25 monoclonal antibody conjugated through a cleavable linker to a pyrrolobenzodiazepine (PBD) dimer. Cami has shown notable single-agent anti-tumor activity and manageable toxicity in the Phase 2 trial of patients with R/R cHL (Carlo-Stella et al, Hemasphere 2022;6:102-103). OBJECTIVES: To assess the clinical response and safety of Cami by subgroups based on demographics, known risk factors impacting outcomes in patients with R/R cHL, and factors with potential relevance to Cami's mechanism of action. METHODS: This analysis was based on the open-label, multicenter, Phase 2 study of Cami monotherapy in patients with R/R cHL after ≥3 prior lines of therapy (NCT04052997). Cami was administered (30-minute infusion) on day 1 of each 3-week cycle at 45 µg/kg for 2 cycles, then 30 µg/kg for subsequent cycles. Subgroup analyses (data cutoff: March 16, 2022) were conducted (Table 1). Efficacy outcomes included the overall response rate (ORR) and median duration of response (mDOR); statistical significance was assessed by comparison of 95% confidence intervals. Safety was assessed by incidence of treatment emergent adverse events (TEAEs). [...]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".