Progression-Free Survival in Advanced Ovarian Cancer: A Canadian Review and Expert Panel Perspective
Bibliographic record
Abstract
Ovarian cancer is leading cause of gynecologic cancer mortality in Canada. To date, overall survival (os) has been the most-used endpoint in oncology trials because of its relevance and objectivity. However, as a result of various factors, including the pattern of sequential salvage therapies, measurement of os and collection of os data are becoming particularly challenging. Phase ii and iii trials have therefore adopted progression-free survival (pfs) as a more convenient surrogate endpoint; however, the clinical significance of pfs remains unclear. This position paper presents discussion topics and findings from a pan-Canadian meeting of experts that set out to evaluate the relevance of pfs as a valid endpoint in ovarian cancer;reach a Canadian consensus on the relevance of pfs in ovarian cancer; andtry to address how pfs translates into clinical benefit in ovarian cancer.Overall, the findings and the group consensus posit that future studies should ensure that trials are designed to evaluate pfs, os, and other clinically relevant endpoints such as disease-related symptoms or quality of life;incorporate interim futility analyses intended to stop accrual early when the experimental regimen is not active;stop trials early to declare superiority only when compelling evidence suggests that a new treatment provides benefit for a pre-specified, clinically relevant endpoint such as os or symptom relief; anddiscourage early release of secondary endpoint results when such a release might increase the frequency of crossover to the experimental intervention.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".