Targeted Molecular Therapeutics for Bladder Cancer—A New Option beyond the Mixed Fortunes of Immune Checkpoint Inhibitors?
Bibliographic record
Abstract
The fact that there are now five immune checkpoint inhibitor (ICI) monoclonal antibodies approved since 2016 that target programmed cell death protein 1 or programmed death ligand-1 for the treatment of metastatic and refractory bladder cancer is an outstanding achievement. Although patients can display pronounced responses that extend survival when treated with ICIs, the main benefit of these drugs compared to traditional chemotherapy is that they are better tolerated and result in reduced adverse events (AEs). Unfortunately, response rates to ICI treatment are relatively low and, these drugs are expensive and have a high economic burden. As a result, their clinical efficacy/cost-value relationship is debated. Long sought after targeted molecular therapeutics have now emerged and are boasting impressive response rates in heavily pre-treated, including ICI treated, patients with metastatic bladder cancer. The antibody-drug conjugates (ADCs) enfortumab vedotin (EV) and sacituzumab govitecan (SG) have demonstrated the ability to provide objective response rates (ORRs) of 44% and 31% in patients with bladder tumor cells that express Nectin-4 and Trop-2, respectively. As a result, EV was approved by the U.S. Food and Drug Administration for the treatment of patients with advanced or metastatic bladder cancer who have previously received ICI and platinum-containing chemotherapy. SG has been granted fast track designation. The small molecule Erdafitinib was recently approved for the treatment of patients with advanced or metastatic bladder cancer with genetic alterations in fibroblast growth factor receptors that have previously been treated with a platinum-containing chemotherapy. Erdafitinib achieved an ORR of 40% in patients including a proportion who had previously received ICI therapy. In addition, these targeted drugs are sufficiently tolerated or AEs can be appropriately managed. Hence, the early performance in clinical effectiveness of these targeted drugs are substantially increased relative to ICIs. In this article, the most up to date follow-ups on treatment efficacy and AEs of the ICIs and targeted therapeutics are described. In addition, drug price and cost-effectiveness are described. For best overall value taking into account clinical effectiveness, price and cost-effectiveness, results favor avelumab and atezolizumab for ICIs. Although therapeutically promising, it is too early to determine if the described targeted therapeutics provide the best overall value as cost-effectiveness analyses have yet to be performed and long-term follow-ups are needed. Nonetheless, with the arrival of targeted molecular therapeutics and their increased effectiveness relative to ICIs, creates a potential novel paradigm based on 'targeting' for affecting clinical practice for metastatic bladder cancer treatment.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| 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".