Abstract P4-10-11: PIK3CA status as a predictor of benefit from drugs targeting the PI3K/AKT/mTOR pathway: A meta-analysis of randomized trials
Bibliographic record
Abstract
Abstract Introduction: A number of different drugs have been developed to target the PI3 kinase/AKT/mTOR pathway. Most randomized trials in breast cancer have been performed in patients unselected for pathway activation although aberrations of components of this pathway are common. Here we explore the predictive value of PIK3CA and AKT mutations in randomized trials of drugs targeting this signaling route. Methods: We searched PubMed for randomized trials of drugs targeting the PI3 kinase/AKT/mTOR pathway in metastatic breast cancer. The search was supplemented by a manual search of recent ASCO and ESMO meetings. Eligible studies needed to report efficacy data based on presence or absence of PIK3CA or AKT status measured either in tumor specimens or in circulating DNA. Hazard ratios (HR) for progression-free survival (PFS) in PIK3CA or AKT mutant and wild-type groups were extracted and pooled in a meta-analysis using generic inverse variance and random effects modeling. Sensitivity analyses were performed based on the mechanism of action of the experimental drug. Results: Of the 15 studies identified, 10 studies comprising of 3615 patients were eligible for analysis. Studies included pan-PI3kinase inhibitors (n=5), alpha-specific PI3kinase inhibitors (n=1), AKT inhibitors (n=2) and mTOR inhibitors (n=2). Approximately 38% of patients had either PIK3CA or AKT mutations. The addition of drugs targeting the PI3 kinase/AKT/mTOR pathway was associated with a significantly longer improvement in PFS in patients with PIK3CA or AKT mutations than in those with wild-type status (HR 0.61, 95% CI 0.50-0.75 versus HR 0.83, 95% CI 0.67-1.02, p for difference = 0.04). Similar results were observed in sensitivity analyses (see Table). Conclusion: Benefit from drugs targeting the PI3 kinase/AKT/mTOR pathway in breast cancer appears to occur exclusively in those with PIK3CA or AKT mutations. Future trials of these drugs should be designed only in biomarker selected patients. TableGroupPIK3CA or AKT mutationPIK3CA and AKT wildtypep for differenceHR95% CIHR95% CIExcluding AKT inhibitors0.640.52-0.790.810.63-1.030.16Excluding pan-PI3 kinase inhibitors0.580.47-0.710.710.51-1.150.24Excluding AKT and alpha-specific PI3 kinase inhibitors0.690.48-1.000.980.83-1.150.09Excluding mTOR inhibitors0.620.49-0.800.920.80-1.060.008 Citation Format: Fahad A Almugbel, Ramy Saleh, Alberto Ocana, Atanasio Pandiella, Eitan Amir. PIK3CA status as a predictor of benefit from drugs targeting the PI3K/AKT/mTOR pathway: A meta-analysis of randomized trials [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-11.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".