Role of Chemoablation Using UGN-101 in Upper Tract Urothelial Carcinoma: A Systematic Review and MetaAnalysis of Available Evidence
Bibliographic record
Abstract
To examine the safety and efficacy of chemoablation using UGN-101 in patients with upper tract urothelial cancer (UTUC). We conducted a systematic search through 7 databases/registries to identify key observational and experimental studies reporting either the efficacy or safety of UGN-101 in UTUC patients regardless of the risk or grade of the disease. The outcomes included efficacy (complete/partial/no response, survival, death, recurrence, or progression) and safety endpoints. All meta-analyses were conducted through STATA. The prevalence rate and its 95% CI were pooled across studies. A subgroup meta-analysis was conducted on follow-up. The quality was assessed using the Newcastle Ottawa Scale. Twenty studies (1051 patients) were analyzed. Complete response was reported in 49% (39%-60%) of cases, and 5% (0%- 15%) had disease progression. Treatment cessation was reported in 13% (3%-27%) of patients. Four percent of cases needed radical nephroureterectomy. Recurrence and death occurred in 14% (7%-23%) and 6% (2%-10%) of patients. Complications occurred in 63% (39%-85%), the majority of which were of grades I, II, and III. Ureteral stenosis was the most common complication accounting for 35% of cases. Chemoablationrelated complications occurred more than procedure-related ones. Based on available evidence, the intracavitary instillation of UGN-101 gel provides an alternative therapeutic option for upper tract urothelial cancer. Chemoablation provides good clinical outcomes in terms of complete response, disease progression and recurrence, and the need to undergo nephroureterectomy. Complications were encountered in more than half the population; however, most of them were of low grades.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.029 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".