A plain language summary of results from the GARNET study of dostarlimab in patients with endometrial cancer
Bibliographic record
Abstract
WHAT IS THIS SUMMARY ABOUT?: Dostarlimab, also known by the brand name JEMPERLI, is a medicine that can be used to treat certain types of endometrial cancer. GARNET is an ongoing phase 1 clinical study that is testing the safety and side effects of dostarlimab and the best way to administer it to patients. The results presented in this summary are from a time point in the middle of the study. WHAT WERE THE RESULTS?: The results from the GARNET study published in 2022 showed how well dostarlimab worked for people participating in the study. Dostarlimab was found to reduce the size of tumors in patients with certain types of endometrial cancer. The patients treated with dostarlimab had side effects that could be managed and few severe side effects. WHAT DO THE RESULTS MEAN?: The results of the GARNET study led to dostarlimab being approved to treat patients with certain types of endometrial cancer. For patients with advanced-stage endometrial cancer, or endometrial cancer that has come back after chemotherapy (recurrent), there are few treatment options. The results suggest that dostarlimab may provide long-term benefits for these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".