Ensuring Successful Biomarker Studies in Bladder Preservation Clinical Trials for Non-muscle Invasive Bladder Cancer
Bibliographic record
Abstract
Recent technological advances have created new opportunities for performing biomarker studies within the National Cancer Institute's (NCI's) National Clinical Trials Network (NCTN) clinical trials.These new platforms yield more robust measurements when tissue and blood handling is optimized.At the same time, there is a strong interest in banking tissue and derivatives, such as DNA and RNA, for future biomarker studies using novel platforms that may emerge during the intervening time to trial completion.The NCI recently hosted a Clinical Trials Planning Meeting focused on two trial concepts for bladder preservation in patients with high-risk non-muscle invasive bladder cancer (NMIBC) and the correlative translational research to be integrated into these trials, where experts discussed prioritization for the use of patient samples, and a framework for best practices emerged.The overall goal of this meeting report is to summarize this discussion and to provide the working group's recommendations for biospecimen handling for future bladder preservation studies.
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 | 0.780 | 0.676 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.021 | 0.016 |
| Open science | 0.007 | 0.013 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.009 |
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".