Long-term outcome of primary Papillary Urothelial Neoplasm of Low Malignant Potential (PUNLMP) including PUNLMP with inverted growth
Bibliographic record
Abstract
BACKGROUND: Few larger studies have evaluated the long-term outcome after a diagnosis of papillary urothelial neoplasm of low malignant potential (PUNLMP), demonstrating a broad range of recurrence and progression rates. Additionally, no study has addressed the outcome of PUNLMP exhibiting inverted growth. We evaluated the long term clinical outcome of primary papillary urothelial neoplasm of low malignant potential (PUNLMP), including PUNLMP with inverted growth in a large single center study. METHODS: We evaluated 189 primary PUNLMP (177 exophytic, 12 inverted), diagnosed from January 1, 2000 to December 31, 2009, in a centralized uropathology practice. We excluded PUNLMP diagnosed after a previous or with a concurrent urothelial neoplasm. Recurrence was defined as any subsequent urothelial neoplasm, regardless of the grade. Progression was defined as any subsequent higher-grade or invasive urothelial neoplasm. Recurrence and progression were established only if documented on a subsequent biopsy. Descriptive statistical analysis was performed using Microsof Excel software package. RESULTS: The location of PUNLMP included bladder (187) and renal pelvis and ureter (1 each). After a median follow-up of 61 months (range, 9-128 months), 20.1% patients developed a recurrence. Recurrence with PUNLMP only was found in 9% of patients. Subsequent low-grade urothelial carcinoma was documented in 9.5% of patients. Progression to high-grade urothelial carcinoma was found in 1.6% patients (1% with muscle invasion). No patients with recurrent PUNLMP or subsequent low-grade carcinoma demonstrated invasion. All patients with PUNLMP exhibiting an inverted growth had no recurrence or progression on follow-up. CONCLUSION: In this study, primary PUNLMP recurred primarily either as PUNLMP or low grade urothelial carcinoma. Primary PUNLMP rarely progressed to high grade or invasive carcinoma on long term follow-up. No recurrence or progression was documented on follow-up for PUNLMP that demonstrated exclusively inverted growth. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1332825572154074.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".