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Time to subsequent therapy in patients (pts) with primary advanced or recurrent endometrial cancer (pA/rEC) receiving dostarlimab plus carboplatin-paclitaxel (DOST+CP) compared with pts receiving placebo plus CP (PBO+CP) in the ENGOT-EN6-NSGO/GOG-3031/RUBY trial.

2025· article· en· W4410815589 on OpenAlexaff
Cara Mathews, Nicoline Raashouu-Jensen, Carolyn K. McCourt, F. Frühauf, Lucy Gilbert, Evelyn Fleming, Giorgio Valabrega, Noelle Cloven, Dominik Denschlag, Iwona Podzielinski, Ingrid Boere, Joseph Buscema, Kathryn P. Pennington, Nicole Nevadunsky, Eirwen M. Miller, Mark S. Shahin, Grace Antony, Laura K. Austin, Matthew A. Powell, Mansoor Raza Mirza

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicinePaclitaxelCarboplatinInternal medicinePlaceboEndometrial cancerOncologyChemotherapyGynecologyUrologyCancerCisplatinPathology

Abstract

fetched live from OpenAlex

5601 Background: In Part 1 of the phase 3 RUBY trial (NCT03981796), DOST+CP significantly improved progression-free survival (PFS) and overall survival (OS) in pts with pA/rEC, leading to approval for frontline treatment in the US and the EU. Time to first subsequent therapy (TFST) and second subsequent therapy (TSST) can provide further insights on the clinical benefit of a regimen as well as any clinical impact beyond first progression. Methods: Pts were randomized 1:1 to receive DOST+CP or PBO+CP Q3W (6 cycles) followed by DOST or PBO monotherapy Q6W for ≤3 years. Primary endpoints were PFS and OS in the overall population and PFS in the mismatch repair deficient/microsatellite instability-high (dMMR/MSI-H) population. Post hoc TFST and TSST analyses were performed at the second interim analysis (data cut, Sept 22, 2023) in the overall, dMMR/MSI-H, and mismatch repair proficient/microsatellite stable (MMRp/MSS) populations. TFST and TSST were defined as the time from randomization to the date of the first dose of first or second subsequent anticancer therapy after study drug, respectively, or death by any cause, whichever occurred first. Results: Of 494 pts randomized, 118 were dMMR/MSI-H and 376 were MMRp/MSS (Table). TFST and TSST were improved in all three populations. Median TFST was 5.1 and 2.5 mo longer in pts treated with DOST+CP vs PBO+CP in the overall and MMRp/MSS populations, respectively; median TFST was not reached (NR) in the DOST+CP arm of the dMMR/MSI-H population. Median TSST was extended by 11.4 and 8.1 mo in pts treated with DOST+CP vs PBO+CP in the overall and MMRp/MSS populations, respectively; median TSST was NR in the DOST+CP arm of the dMMR/MSI-H population. Hazard ratios favoring DOST+CP remained consistent between TFST and TSST in all populations evaluated. Conclusions: These results indicate prolonged TFST and sustained benefits through TSST with DOST+CP compared with PBO+CP across the overall, dMMR/MSI-H, and MMRp/MSS populations in the RUBY trial. Together with the statistically significant PFS and OS benefits, these findings support the frontline use of dostarlimab + CP as a standard of care in all pts with pA/rEC. Clinical trial information: NCT03981796 . Overall dMMR/MSI-H MMRp/MSS DOST+CP(n=245) PBO+CP(n=249) DOST+CP(n=53) PBO+CP(n=65) DOST+CP(n=192) PBO+CP(n=184) TFST, median (95% CI), mo 15.3 (12.3–20.1) 10.2 (9.1–10.9) NR(19.8–NR) 10.5(7.3–12.0) 12.7(11.4–17.1) 10.2(9.0–10.8) HR (95% CI) 0.63 (0.51–0.78) 0.34 (0.20–0.57) 0.73 (0.58–0.92) TSST, median (95% CI), mo 31.3(24.6–40.8) 19.9(16.3–23.1) NR(NR–NR) 24.0(16.1–39.1) 26.8(22.1–32.6) 18.7(15.3–22.0) HR (95% CI) 0.67 (0.53–0.85) 0.41 (0.23–0.74) 0.73 (0.57–0.94) NR, not reached; TFST, time to first subsequent treatment; TSST, time to second subsequent treatment.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.093
GPT teacher head0.422
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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