Bibliographic record
Abstract
Bladder cancer is common cancer threatening countless people’s lives. Urothelial carcinoma contributes to 90% of bladder cancer cases and has a low average five-year relative survival rate of 6% if metastasized. Finding appropriate therapy for those with metastatic urothelial carcinoma (MUC) is therefore crucial. Most patients cannot get first-line cisplatin-based chemotherapy, and a small number cannot receive any platinum-based treatment. The immune checkpoint inhibitor pembrolizumab blocking the PD-1 with the PD-L1 protein expressed on urothelial carcinoma cells. This blockade reduces immunosuppressive effects and restores effective neoplastic cell eradication. Compared to conventional chemotherapy strategies, pembrolizumab had significant improvement in the safety profile, reduction of adverse effect rate, and elongation of survival under certain conditions. It offers an alternative treatment option for those who are ineligible for chemotherapy. Pembrolizumab has been given the approval to be used in first-line settings for patients who are ineligible for platinum and second-line settings for patients who have already had chemotherapy. This paper summarizes the mechanism and application of pembrolizumab for treating MUC. The drug’s efficacies under different conditions, advantages, current issues, and future investigation directions are discussed.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".