The Rationale for Post-Operative Radiation in Localized Bladder Cancer
Bibliographic record
Abstract
Local-regional recurrence for patients with ≥pT3 disease after radical cystectomy is a significant problem. Chemotherapy has not been shown to reduce the risk of local-regional recurrences in randomized prospective trials, and salvage therapies for local-regional failure are rarely successful. There is promising evidence, particularly from a recent Egyptian NCI trial, that radiation therapy plus chemotherapy can significantly reduce local recurrences compared to chemotherapy alone, and that this improvement in local-regional control may translate to meaningful improvements in disease-free and overall survival with acceptable toxicity. In light of the high rates of local failure following cystectomy for locally advanced disease and the progress that has been made in identifying patients at high risk of failure and the patterns of failure in the pelvis, the NCCN guidelines were revised in 2016 to include post-operative radiotherapy as an option to consider for patients with ≥pT3 disease. Despite advances in our understanding of the problem of local-regional failure after cystectomy and the potential role of adjuvant radiotherapy, the question of whether adjuvant radiotherapy should have a defined role for patients with locally advanced urothelial carcinoma has not yet been determined. The results of the NRG, European, Indian, and Egyptian trials on adjuvant radiotherapy are eagerly awaited. While none of these trials on their own may provide definitive conclusions, their aggregate outcomes will help clarify whether this treatment should have a role in the management of patients with locally advanced bladder cancer.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".