Long-term results of retroperitoneoscopic nephroureterectomy for upper urinary tract transitional cell carcinoma in China
Bibliographic record
Abstract
OBJECTIVE: We compared long-term clinical outcomes of upper urinary tract transitional cell carcinoma (TCC) patients treated by retroperitoneoscopic nephroureterectomy (RNU) or open radical nephroureterectomy (ONU). METHODS: Upper urinary tract TCC patients were treated with RNU (n = 86) or ONU (n = 72) and followed-up for more than three years. Demographic and clinical data, including preoperative indexes, intraoperative indexes and long-term clinical outcomes, were retrospectively compared to determine long-term efficacy of the two procedures. RESULTS: The RNU and ONU groups were statistically similar in age, gender, previous bladder cancer history, tumour location, pathologic tumour stage, pathologic node metastasis or tumour pathologic grade. The original surgery time required for both RNU and ONU was statistically similar, but RNU was associated with a significantly smaller volume of intraoperative estimated blood loss and shorter length of postoperative hospital stay. Follow-up (average: 42.4 months, range: 3-57) revealed that the RNU 3-year recurrence-free survival rate was 62.8% and the 3-year cancer specific survival rate was 80.7%. In the ONU group, the 3-year recurrence-free survival and the three-year cancer-specific survival rates were 59.2% and 80.3%, respectively. Neither of the survival rates were statistically different between the two groups. T stage, grade, lymph node metastasis and bladder tumour history were risk factors for tumour recurrence; the operation mode and the bladder cuff incision mode had no correlation with the recurrence-free survival. CONCLUSION: The open surgery strategy and the retroperitoneoscopic nephroureterectomy strategy are equally effective for treating upper urinary tract TCC. However, the RNU procedure is less invasive, and requires a shorter duration of postoperative hospitalized care; thus, RNU is recommended as the preferred strategy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".