Perspectives on the future of urothelial carcinoma therapy: chemotherapy and beyond
Bibliographic record
Abstract
INTRODUCTION: Despite recent developments in the landscape of urothelial carcinoma (UC) treatment, platinum combination chemotherapy still remains a milestone. Recently immunotherapeutic agents have gained ever-growing attractivity, particularly in the metastatic setting. Novel chemotherapeutic strategies and agents, such as antibody-drug conjugates (ADCs), and powerful combination regimens have been developed to overcome the resistance of most UC to current therapies. AREAS COVERED: Herein, we review the current standard-of-care chemotherapy, the development of ADCs, the rationale for combining therapy regimens with chemotherapy in current trials, and future directions in UC management. EXPERT OPINION: Immunotherapy has prompted a revolution in the treatment paradigm of UC. However, only a few patients experience a long-term response when treated with single-agent immunotherapies. Combination treatments are necessary to bypass resistance mechanisms and broaden the clinical utility of current options. Current evidence supports the intensification of standard-of-care chemotherapy with maintenance immunotherapy. However, the optimal sequence, combination, and duration must be determined to achieve individual longevity with acceptable health-related quality of life. In that regard, ADCs appear as a promising alternative for single and combination strategies in UC, as they specifically target the tumor cells, thereby, theoretically improving treatment efficacy and avoiding extensive off-target toxicities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".