Enfortumab Vedotin in urothelial cancer
Bibliographic record
Abstract
The treatment landscape for metastatic urothelial cancer (mUC) beyond first-line platinum-based chemotherapy has changed significantly over the last 5 years with the recent approvals of the immune checkpoint inhibitors (ICIs), fibroblast growth factor receptor (FGFR) inhibitors and most recently Enfortumab Vedotin (EV). EV is a novel antibody-drug conjugate (ADC), that delivers monomethyl auristatin E (MMAE), a microtubule-disrupting agent, inside cells harboring the cell surface nectin-4 receptor. In mUC, EV has shown encouraging response rates and received accelerated approval from the Food and Drug Administration (FDA) in December 2019 in the post-platinum and ICI setting. EV is generally well tolerated, with the main toxicities being neuropathy, skin rash, alopecia and fatigue. Notably EV can also be administered to patients with renal dysfunction, which is commonly a concern in this patient population. EV is now being tested in combination strategies and in earlier disease settings in urothelial cancers. In this review, we will discuss its mechanism of action, clinical trials leading to FDA approval as well as ongoing trials and future directions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".