50P Can we learn from failures? A systematic review and metanalysis of phase III trials in platinum resistant ovarian cancer
Bibliographic record
Abstract
Despite considerable efforts, little advances have been made in the treatment of platinum resistant ovarian cancer (PROC) in the last decade. The reasons for these dismal results remain controversial. Understanding phase (Ph) 3 randomized controlled trials (RCT) design and outcomes in PROC patients might provide indications for the development of future research. We performed a systematic review searching in PubMed, Embase and CENTRAL for Ph3 RCT enrolling PROC patients, published between 2010 and 2022. For the meta-analysis, effect sizes (ES) for progression free survival (PFS) and overall survival (OS) were calculated using random-effect models with restricted maximum likelihood estimate. After screening and eligibility assessment, 15 records reporting the results of 13 RCT were included, for a total of 4606 patients. Experimental arm employed targeted agents in 6 trials, chemotherapy (Cht) in 4, immunotherapy in 2 and antibody-drug conjugate in 1. Control treatment was Cht in all studies. Only 3 trials included a biomarker-selected population. PFS and/or OS were the (co-)primary endpoints in all studies but one. Median PFS ranged from 1.9 to 6.7 months (m) in the experimental arms and from 1.2 to 5.7 m in the control arms; median OS ranged from 8.8 to 16.6 m in experimental arms and from 8.4 to 22.2 m in the control arms. All but two trials (TRINOVA1 and AURELIA) failed to show any PFS benefit in PROC patients and none had positive OS results. Overall ES for PFS was -0.03 (95% CI -0.23, 0.16), with high heterogeneity (I283.3%) while ES for OS was -0.02 (95% CI -0.10, 0.05) with negligible heterogeneity (I2<0.0001). Of the included Ph3 RCT, 6 were preceded by a single arm and 3 by a randomized Ph2 study. The two RCT testing the anti-angiogenic agents bevacizumab and trebananib combined with Cht were the only reporting a PFS benefit in PROC. The lack of robust predictive biomarkers, of adequate preclinical and early clinical results and of a proper methodology might partly explain these disappointing outcomes. A better understanding of PROC biology and its implementation in study design are crucial to improve drug development in this population.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.017 | 0.001 |
| 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) | 0.001 | 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 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".