A Phase II Randomized Trial of Chemoradiation with or without Metformin in Locally Advanced Cervical Cancer
Bibliographic record
Abstract
PURPOSE: Tumor hypoxia is associated with poor response to radiation (RT). We previously discovered a novel mechanism of metformin: enhancing tumor RT response by decreasing tumor hypoxia. We hypothesized that metformin would decrease tumor hypoxia and improve cervical cancer response to RT. PATIENTS AND METHODS: A window-of-opportunity, phase II randomized trial was performed in stage IB-IVA cervical cancer. Patients underwent screening positron emission tomography (PET) imaging with hypoxia tracer fluoroazomycin arabinoside (FAZA). Only patients with FAZA uptake (hypoxic tumor) were included and randomized 2:1 to receive metformin in combination with chemoRT or chemoRT alone. A second FAZA-PET/CT scan was performed after 1 week of metformin or no intervention (control). The primary endpoint was a change in fractional hypoxic volume (FHV) between FAZA-PET scans, compared using the Wilcoxon signed-rank test. The study was closed early due to FAZA availability and the COVID-19 pandemic. RESULTS: Of the 20 consented patients, 6 were excluded due to no FAZA uptake and 1 withdrew. FHV of 10 patients in the metformin arm decreased by an average of 10.2% (44.4%-34.2%) ± SD 16.9% after 1 week of metformin, compared with an average increase of 4.7% (29.1%-33.8%) ± 11.5% for the 3 controls (P = 0.027). Those with FHV reduction after metformin had significantly lower MATE2 expression. With a median follow-up of 2.8 years, the 2-year disease-free survival was 67% for the metformin arm versus 33% for controls (P = 0.09). CONCLUSIONS: Metformin decreased cervical tumor hypoxia in this trial that selected for patients with hypoxic tumor. See related commentary by Lyng et al., p. 5233.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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, 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".