Higher Risk of Infections with PI3K–AKT–mTOR Pathway Inhibitors in Patients with Advanced Solid Tumors on Phase I Clinical Trials
Bibliographic record
Abstract
PURPOSE: Novel antitumor therapies against the PI3K-AKT-mTOR pathway are increasingly used to treat cancer, either as single agents or in combination with chemotherapy or other targeted therapies. Although these agents are not known to be myelosuppressive, an increased risk of infection has been reported with rapamycin analogues. However, the risk of infection with new inhibitors of this pathway such as PI3K, AKT, mTORC 1/2, or multikinase inhibitors is unknown. EXPERIMENTAL DESIGN: In this retrospective case-control study, we determined the incidence of infection in a group of 432 patients who were treated on 15 phase I clinical trials involving PI3K-AKT-mTOR pathway inhibitors (cases) versus a group of 100 patients on 10 phase I clinical trials of single agent non-PI3K-AKT-mTOR pathway inhibitors (controls) which did not involve conventional cytotoxic agents. We also collected data from 42 patients who were treated with phase I trials of combinations of PI3K-AKT-mTOR inhibitors and MEK inhibitors and 24 patients with combinations of PI3K-AKT-mTOR inhibitors and cytotoxic chemotherapies. RESULTS: The incidence of all grade infection was significantly higher with all single-agent PI3K-AKT-mTOR inhibitors compared with the control group [27% vs. 8%, respectively, OR, 4.26; 95% confidence intervals (CI), 1.9-9.1, P = 0.0001]. The incidence of grade 3 and 4 infection was also significantly higher with PI3K-AKT-mTOR inhibitors compared with the control group (10.3% vs. 3%, OR, 3.74; 95% CI, 1.1-12.4; P = 0.02). Also, the combination of PI3K-AKT-mTOR inhibitors and chemotherapy was associated with a significantly higher incidence of all grade (OR, 4.79; 95% CI, 2.0-11.2; P = 0.0001) and high-grade (OR, 2.87; 95% CI, 1.0-7.6; P = 0.03) infection when compared with single-agent PI3K-AKT-mTOR inhibitors. CONCLUSIONS: Inhibitors of the PI3K-AKT-mTOR pathway can be associated with a higher risk of infection. Combinations of PI3K-AKT-mTOR inhibitors and cytotoxic chemotherapy significantly increase the risk of infection. This should be taken into consideration during the design and conduct of trials involving PI3K-AKT-mTOR pathway inhibitors, particularly when combined with chemotherapy or myelosuppressive agents.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".