2024 CUA-GUMOC Expert Report: Management of unresectable locally advanced and metastatic urothelial carcinoma
Bibliographic record
Abstract
We conducted a comprehensive literature review evaluating studies of mUC, with an emphasis on RCTs published since the 2019 publication.A search of PubMed, Medline, and Embase, in addition to other published guidelines and abstract presentations at major conferences, were used to identify relevant studies.Wherever possible we sought to align our treatment recommendations with those of international organizations such as American Society of Clinical Oncology (ASCO), National Comprehensive Cancer Network (NCCN), European Society of Medical Oncology (ESMO) and European Association of Urology (EAU); however, full alignment may be limited by differences in clinical practice standards, regional variations, and the availability of approved therapies in Canada.Draft recommendations on various aspects of mUC management, based on best available evidence, were initially developed by the co-first and senior authors.These recommendations were shared with all co-authors via email for input, and revisions were made based on this email discussion.Through this process, consensus was reached by incorporating and addressing all the feedback points, ensuring alignment among the authors.Authorship in this consensus is composed of experts and key opinion leaders in genitourinary medical oncology, uro-oncology, and radiation oncology across Canada.These experts were selected based on their significant clinical experience, academic contributions, and leadership in clinical practice guidelines.A multidisciplinary approach is emphasized, particularly in the setting of locally advanced disease (defined here as cT4b and/or cN1-N3), oligometastatic, or oligoprogressive disease (OPD).Statements pertaining to aspects of management are intended to provide general guidance regarding treatment decision making, however, are not meant to supersede clinical judgement of individual scenarios.
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 | 0.012 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".