Clinical follow up and the impact of the Paris system in the assessment of patients with atypical urine cytology
Bibliographic record
Abstract
BACKGROUND: Urinary cytology is routinely used in the diagnosis of urothelial neoplasms, with good sensitivity for high-grade urothelial carcinoma (HGUC) but less so for low-grade urothelial neoplasm (LGUN). There is significant interobserver and interinstitutional variability, especially for the atypical category. The Paris system for reporting urinary cytology (TPS) was introduced to better define the various categories, especially atypical cytology. METHODS: We retrospectively reviewed 630 atypia of undetermined significance (AUS) cases and reclassified them based on TPS. In total, 501 cases previously reported as negative for malignancy had their medical records reviewed to serve as negative controls. RESULTS: Of 630 AUS cases, 299 (47.5%) were reclassified as negative for HGUC (NHGUC), 313 (49.7%) as atypical urothelial cells (AUCs) and 18 (2.9%) as suspicious for HGUC (SHGUC). Based on our institution's previous reporting system, the rate of underlying or subsequent HGUC was 2.8% for AUS, and 0% for negative. When AUS cases were reclassified under TPS, the rates were 1.5% for NHGUC, 4.8% for AUC, and 0% for SHGUC. Review of medical records showed that patients with AUS were more likely to be followed-up compared with those with negative urine cytology (77.8% compared with 54.3%), particularly those under the care of non-urologists. CONCLUSIONS: AUS diagnosis is associated with more patient follow up compared with NEG urine particularly among non-urologists. Reclassifying according to TPS results in significant reduction in the rate of AUS and thus unnecessary testing. This reduction however may be at the expense of slightly decreased detection rate of HGUC.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".