Safety and efficacy of the anti-PD-1 monoclonal antibody dostarlimab in patients with recurrent or advanced dMMR endometrial cancer
Bibliographic record
Abstract
Objectives Dostarlimab (TSR-042) is a humanized programmed death (PD)-1 receptor monoclonal antibody that blocks interaction with PD-1 ligands, PD-L1 and PD-L2. The objective of this interim analysis was to assess the safety and efficacy of dostarlimab in patients with mismatch repair deficient (dMMR) endometrial cancer (EC) who enrolled in the GARNET trial (NCT02715284). Materials and Methods The trial enrolled patients with immunohistochemistry-confirmed dMMR EC with recurrent/advanced disease that progressed on a platinum-doublet regimen. Patients received 500 mg Q3W of dostarlimab for 4 cycles, then 1000 mg Q6W until disease progression/discontinuation. Primary endpoints were objective response rate (ORR) and duration of response (DOR) as assessed against Response Evaluation Criteria in Solid Tumors v1.1 by blinded independent central review. Results As of the data cutoff, 104 patients with dMMR EC were enrolled and dosed. Of these, 71 had measurable disease at baseline and ≥6 months of follow-up. The confirmed ORR was 42.3% (95% CI, 30.6%-54.6%); confirmed complete and partial response rates were 12.7% and 29.6%, respectively. Responses were durable; the median DOR was not reached (median follow-up was 11.2 months). The estimated likelihood of maintaining response at 6 and 12 months was 96.4% and 76.8%, respectively. Anemia (2.9%), colitis (1.9%), and diarrhea (1.9%) were the most common grade ≥3 treatment-related adverse events. There were no deaths assessed as related to dostarlimab treatment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".