Current Management of Localized Muscle-Invasive Bladder Cancer: A Consensus Guideline from the Genitourinary Medical Oncologists of Canada
Bibliographic record
Abstract
BACKGROUND: Despite recent advances in the management of muscle-invasive bladder cancer (MIBC), treatment outcomes remain suboptimal, and variability exists across current practice patterns. OBJECTIVE: To promote standardization of care for MIBC in Canada by developing a consensus guidelines using a multidisciplinary, evidence-based, patient-centered approach who specialize in bladder cancer. METHODS: A comprehensive literature search of PubMed, Medline, and Embase was performed; and most recent guidelines from national and international organizations were reviewed. Recommendations were made based on best available evidence, and strength of recommendations were graded based on quality of the evidence. RESULTS: Overall, 17 recommendations were made covering a broad range of topics including pathology review, staging investigations, systemic therapy, local definitive therapy and surveillance. Of these, 10 (59% ) were level 1 or 2, 7 (41% ) were level 3 or 4 recommendations. There were 2 recommendations which did not reach full consensus, and were based on majority opinion. This guideline also provides guidance for the management of cisplatin-ineligible patients, variant histologies, and bladder-sparing trimodality therapy. Potential biomarkers, ongoing clinical trials, and future directions are highlighted. CONCLUSIONS: This guideline embodies the collaborative expertise from all disciplines involved, and provides guidance to further optimize and standardize the management of MIBC.
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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| 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".