Preoperative hydronephrosis and diabetes mellitus predict poor prognosis in upper urinary tract urothelial carcinoma
Bibliographic record
Abstract
INTRODUCTION: We assess the impact of traditional prognostic factors, tumour location, degree of hydronephrosis and diabetes mellitus (DM) on the survival of patients treated for upper urinary tract urothelial carcinoma (UUTUC). METHODS: From January 2004 to March 2010, we analyzed data from 114 patients with UUTUC who underwent nephroureterectomy with a bladder cuff excision. Median patient age was 71 years and median follow-up was 26.5 months. The influence of traditional prognostic factors, including DM, tumour stage, grade, location and degree of hydronephrosis, on recurrence-free survival (RFS) rates were analyzed using Kaplan-Meier analysis and Cox proportional hazards regression model. RESULTS: Among 61 renal pelvis and 53 ureteral tumour cases, recurrence was identified in 71 cases (62.3%). Kaplan-Meier analysis showed that degree of hydronephrosis was associated with RFS (p = 0.001). DM and degree of hydronephrosis were independent factors for RFS in Cox proportional regression analysis (HR=1.8 CI: 1.01-3.55, p = 0.04), (HR=3.7, CI: 2.0-6.5, p = 0.001). All patients with ureteral tumour had no worse prognosis than those with renal pelvis tumour, but the pT2 patients with ureteral tumour had a worse prognosis than those with renal pelvis tumour with a median RFS of 9 months (range: 2.6-15.3 months) and 29 months (range: 8.0-13.2 months), respectively (p = 0.028). CONCLUSIONS: Tumour location is not a factor influencing RFS, except in the pT2 stage. However, severe hydronephrosis is associated with a higher recurrence in UUTUC. Also, DM is related to disease recurrence. Further prospective studies are needed to establish the prognostic significance of DM in large populations.
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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 | 0.000 | 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 | 0.001 |
| 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".