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ROSELLA: A phase 3 study of relacorilant in combination with nab-paclitaxel versus nab-paclitaxel monotherapy in patients with platinum-resistant ovarian cancer (GOG-3073, ENGOT-ov72).

2025· article· en· W4411026891 on OpenAlexaff
Alexander Olawaiye, Laurence Gladieff, Lucy Gilbert, Jae‐Weon Kim, Mariana Scaranti, Vanda Salutari, Elizabeth Hopp, Linda Mileshkin, Alix Devaux, Michael McCollum, Ana Oaknin, Aliza Leiser, Nicoletta Colombo, Andrew R. Clamp, Boglárka Balázs, Giuseppa Scandurra, Emilie Kaczmarek, Hristina I. Pashova, Sachin Gopalkrishna Pai, Domenica Lorusso

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectron Spin Resonance Studies
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicinePaclitaxelNab-paclitaxelOvarian cancerInternal medicineOncologyChemotherapyCancer

Abstract

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LBA5507 Background: Relacorilant is an investigational, oral, selective glucocorticoid receptor antagonist (SGRA) that increases tumor sensitivity to chemotherapy-induced apoptosis. In a phase 2 study, the addition of relacorilant to nab-paclitaxel improved progression-free survival (PFS) and showed a trend towards improved overall survival (OS), with a comparable safety profile to nab-paclitaxel monotherapy, in patients with platinum-resistant ovarian cancer (PROC). The aim of this phase 3 study is to confirm the efficacy and safety of relacorilant + nab-paclitaxel in a larger population. Methods: ROSELLA (NCT05257408) is a randomized, controlled, open-label, global study of relacorilant + nab-paclitaxel compared to nab-paclitaxel monotherapy in patients with PROC. Patients were randomized 1:1 to either relacorilant (150 mg the day before, day of, and day after nab-paclitaxel) + nab-paclitaxel (80 mg/m 2 on days 1, 8, and 15 of each 28-day cycle) or nab-paclitaxel alone (100 mg/m 2 on the aforementioned schedule). Randomization was stratified by prior lines of therapy and region. Key eligibility criteria included 1–3 prior lines of anticancer therapy and prior bevacizumab. The dual primary endpoints are PFS by blinded independent central review (BICR) and OS. Secondary endpoints include PFS by investigator, objective response rate, best overall response, duration of response, and safety. PFS and OS endpoints were analyzed using Kaplan-Meier methods. A 2-sided stratified log-rank test was used to compare treatment groups. Hazard ratios (HR) were estimated with a Cox regression model. Results: A total of 381 women were randomized, all baseline characteristics were well balanced and 39% had received prior therapy in the PROC setting. ROSELLA met its primary endpoint: Patients receiving relacorilant + nab-paclitaxel had a statistically significant improvement in PFS by BICR compared to nab-paclitaxel monotherapy (HR 0.70, 95% CI 0.54-0.91, median 6.5 v 5.5 months, P=0.008); PFS by investigator showed a consistent benefit (HR 0.71, P=0.003). At an interim analysis, there was a clinically significant improvement in OS with the addition of relacorilant to nab-paclitaxel (HR 0.69, 95% CI 0.52-0.92, median 16.0 v 11.5 months, P=0.01). Adverse events (AEs) were comparable across study arms, relacorilant + nab-paclitaxel was well tolerated with no new safety signals. The most frequently reported AEs were known toxicities of nab-paclitaxel: anemia (58%), neutropenia (56%), and nausea (39%). Conclusion: Relacorilant + nab-paclitaxel is the first treatment regimen to demonstrate a PFS and OS benefit in patients with PROC compared to a weekly taxane, the most efficacious comparator. These positive efficacy data and a favorable safety profile position relacorilant + nab-paclitaxel as a new standard for patients with PROC, without the need for biomarker selection. Clinical trial information: NCT05257408 .

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.421
Teacher spread0.388 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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