Efficacy and Safety of Capivasertib (AZD5363), a Potent, Oral Pan-AKT Inhibitor, in Patients with Relapsed or Refractory B-cell Non–Hodgkin Lymphoma (CAPITAL)
Bibliographic record
Abstract
PURPOSE: An unmet treatment need remains for relapsed/refractory (R/R) non-Hodgkin lymphoma (NHL), including the follicular lymphoma (FL), mantle cell lymphoma (MCL), and marginal zone lymphoma (MZL) subtypes. The PI3K/AKT/mTOR pathway is dysregulated and associated with poor prognosis in NHL. The AKT inhibitor capivasertib has preclinical activity in hematologic malignancy models. PATIENTS AND METHODS: NCT05008055 was a modular, open-label, multicenter phase II study that examined oral capivasertib monotherapy in patients with R/R B-cell NHL who had received ≥2 prior lines of therapy. Patients had R/R FL (cohort 1A), MZL (cohort 1B), or MCL (cohort 1C). Capivasertib 480 mg twice daily was administered orally 4 days on/3 days off. The primary objective was to determine the objective response rate (ORR) by blinded independent central review. RESULTS: Thirty patients were enrolled (of 272 planned). The ORR for patients with R/R FL, MZL, and MCL were 18.8% (three of 16), 33.3% (one of three), and 30% (three of 10), respectively; 62.5% (10 of 16) of patients with R/R FL had stable disease. Baseline tumor PTEN expression was deficient/undetectable in the two patients who had a complete response and three of five patients who had a partial response. The most common capivasertib-related adverse events (AE) were diarrhea (63.3%), nausea (20%), vomiting (13.3%), and hyperglycemia (10%). Capivasertib-related grade ≥3 AE or serious AE were observed in nine and three patients, respectively. CONCLUSIONS: The study was terminated early with a small sample size, limiting interpretation, although antitumor activity was limited. Future studies of capivasertib in hematologic malignancies would likely require biomarker-directed patient selection and/or combination therapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".