Fluorescence Emitted by Papanicolaou-Stained Urothelial Cells Improves Sensitivity of Urinary Conventional Cytology for Detection of Urothelial Tumors
Bibliographic record
Abstract
Background: Urinary conventional cytology (UCCy) is easy to perform, but its low sensitivity, especially for low-grade urothelial neoplasms (LGUNs), limits its indications in the management of patients at risk of bladder cancer. The authors aim at obtaining a complementary test that would effectively increase the sensitivity of UCCy on voided urines by analyzing fluorescence of Papanicolaou-stained urothelial cells with no change of method in slide preparation. Methods: In this retrospective study of 155 patients, 91 Papanicolaou-stained voided urines were considered satisfactory under fluorescence microscopy (FMi). The results of FMi were compared with UCCy (using transmission microscopy) and correlated to cystoscopy, histology and follow-up data. Results: The results are given for all patients and for two groups of them according to the patients’ main complaints (group 1: 33 patients followed up for a previously treated bladder tumor; group 2: 58 patients with persistent urinary symptoms). Overall negative predictive value (NPV) and sensitivity of FMi were 100% vs. 73.7% and 64.3% respectively for UCCy (P = 0.0001). Sensitivity of FMi for LGUN was unexpectedly high with a value of 100% vs. 46.2% for UCCy (P = 0.0002). FMi was significantly superior to UCCy for detecting urothelial tumors in every group of patients and would allow a better characterization of atypical urothelial cells (AUCs) defined by the Paris System for Reporting Urine Cytology (TPS). Conclusions: Because of its sensitivity and NPV of 100%, FMi could complement UCCy to screen voided urines allowing a better detection of primary urothelial tumors or early recurrences of previously treated urothelial carcinoma. Moreover, this “dual screening” would allow completing efficiently cystoscopy to detect flat dysplasia, carcinoma in situ (CIS) and extra bladder carcinoma. World J Oncol. 2020;11(5):204-215 doi: https://doi.org/10.14740/wjon1305
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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 | 0.004 |
| 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 | 0.000 |
| 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".