Randomized Phase II Study Evaluating Akt Blockade with Ipatasertib, in Combination with Abiraterone, in Patients with Metastatic Prostate Cancer with and without PTEN Loss
Bibliographic record
Abstract
Abstract Purpose: PI3K–Akt–mTOR and androgen receptor (AR) signaling are commonly aberrantly activated in metastatic castration-resistant prostate cancer (mCRPC), with PTEN loss associating with poor prognosis. We therefore conducted a phase Ib/II study of the combination of ipatasertib, an Akt inhibitor, with the CYP17 inhibitor abiraterone in patients with mCRPC. Patients and Methods: Patients were randomized 1:1:1 to ipatasertib 400 mg, ipatasertib 200 mg, or placebo, with abiraterone 1,000 mg orally. Coprimary efficacy endpoints were radiographic progression-free survival (rPFS) in the intent-to-treat population and in patients with PTEN-loss tumors. Results: rPFS was prolonged in the ipatasertib cohort versus placebo, with similar trends in overall survival and time-to-PSA progression. A larger rPFS prolongation for the combination was demonstrated in PTEN-loss tumors versus those without. The combination was well tolerated, with no treatment-related deaths. Conclusions: In mCRPC, combined blockade with abiraterone and ipatasertib showed superior antitumor activity to abiraterone alone, especially in patients with PTEN-loss tumors. See related commentary by Zhang et al., p. 901
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".