A Pan-Canadian Consensus Statement on First-Line PARP Inhibitor Maintenance for Advanced, High-Grade Serous and Endometrioid Tubal, Ovarian, and Primary Peritoneal Cancers
Bibliographic record
Abstract
The majority of patients with advanced, high-grade epithelial-tubo ovarian cancer (EOC) respond well to initial treatment with platinum-based chemotherapy; however, up to 80% of patients will experience a recurrence. Poly(ADP-ribose) Polymerase (PARP) inhibitors have been established as a standard of care maintenance therapy to prolong remission and prevent relapse following a response to first-line platinum-chemotherapy. Olaparib and niraparib are the PARP inhibitors currently approved for use in the first-line maintenance setting in Canada. Selection of maintenance therapy requires consideration of patient and tumour factors, presence of germline and somatic mutations, expected drug toxicity profile, and treatment access. This paper discusses the current clinical evidence for first-line PARP inhibitor maintenance therapy in patients with advanced, high-grade EOC and presents consensus statements and a treatment algorithm to aid Canadian oncologists on the selection and use of PARP inhibitors within the Canadian EOC treatment landscape.
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 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 | 0.020 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".