Impact of adjuvant chemotherapy for patients with locally advanced upper tract urothelial carcinoma in real-world clinical practice
Bibliographic record
Abstract
INTRODUCTION: The impact of adjuvant chemotherapy (ACT) using regimens including gemcitabine and platinum on the improvement of the prognosis of patients with locally advanced upper tract urothelial carcinoma (UTUC) has been recently demonstrated. This study aimed to determine the utility of ACT for patients with locally advanced UTUC in real-world clinical practice and the differences in efficacy among regimens. METHODS: Of 206 UTUC patients who underwent radical nephroureterectomy, 78 were pathologically diagnosed as T3 or higher and/or had pathologically identified lymph node metastasis; 36 in the ACT group and 42 in the non-ACT group were evaluated for patient background, recurrence, and prognosis. In the ACT group, either cisplatin (GC group, 12 cases) or carboplatin (GCa group, 24 cases) was administered as the platinum agent to be combined with gemcitabine. RESULT: The median patient age in the ACT group and that in the non-ACT group was 71 and 79 years, respectively (p<0.0001). There was no significant difference between these two groups in terms of other patient parameters. The two- and five-year cancer-specific survival (CSS ) and the two- and five-year disease-free survival (DFS) for the ACT group were 81.7%, 66.0%, 60.6%, and 56.6%, respectively, and for the non-ACT group were 68.4%, 40.5%, 42.8%, and 29.3%, respectively (p=0.0399 for CSS and p=0.0814 for DFS). There was no significant difference in CSS and DFS between the GC group and GCa group (p=0.9846 and p=0.9389, respectively). CONCLUSIONS: In real-world clinical practice in Japan, UTUC patients who receive ACT after radical nephroureterectomy may be expected to have better cancer control than those who do not receive ACT.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".