ATHENA–MONO (GOG-3020/ENGOT-ov45): A randomized, double-blind, phase 3 trial evaluating rucaparib monotherapy versus placebo as maintenance treatment following response to first-line platinum-based chemotherapy in ovarian cancer.
Bibliographic record
Abstract
LBA5500 Background: While PARP inhibitors have shown efficacy as first-line (1L) maintenance treatment for patients (pts) with ovarian cancer (OC), questions remain about the pt population that may benefit from their use. ATHENA (NCT03522246) was designed to test if rucaparib may be effective as 1L maintenance treatment in a broad pt population, including those without BRCA mutations or other evidence of homologous recombination deficiency (HRD), or high-risk clinical characteristics such as residual disease. Here we report results from the ATHENA–MONO comparison of rucaparib vs placebo. Methods: Pts with stage III–IV high-grade OC who had completed cytoreductive surgery (R0 permitted) and 4–8 cycles of 1L platinum-doublet (bevacizumab allowed with chemotherapy) with a response were randomized 4:1 to oral rucaparib 600 mg BID or placebo. Pts were stratified by HRD status (as determined by FoundationOne CDx), residual disease status after chemotherapy, and timing of surgery. The primary endpoint of investigator-assessed PFS per RECIST was assessed in a step-down procedure first in the HRD population (BRCA mutant or BRCA wild-type/loss of heterozygosity [LOH] high carcinoma) and then in the intent-to-treat (ITT) population. Blinded independent central review (BICR)–assessed PFS was a stand-alone, secondary endpoint. PFS in BRCA mutant and HRD-negative pts (BRCA wild-type/LOH low) were exploratory endpoints. Results: As of Mar 23, 2022 (visit cutoff), 427 and 111 pts were randomized to rucaparib monotherapy or placebo (median time on treatment, 14.7 and 9.9 mo). PFS data are shown in the Table. Most common grade ≥3 TEAEs were anemia (rucaparib, 28.7% vs placebo, 0%), neutropenia (14.6% vs 0.9%), and ALT/AST increased (10.6% vs 0.9%). Rucaparib dose reduction, interruption, and discontinuation due to TEAEs occurred in 49.4%, 60.7%, and 11.8% of pts. Conclusions: Rucaparib monotherapy is effective as 1L maintenance with significant benefit vs placebo observed in the ITT and HRD populations, as well as the non-nested subgroup of pts without known HRD. Clinical trial information: NCT03522246. [Table: see text]
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".