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Record W1566673280 · doi:10.1002/cncy.21477

Accuracy and risk of malignancy for diagnostic categories in urine cytology at a large tertiary institution

2014· article· en· W1566673280 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Cytopathology · 2014
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCytologyMedicineMalignancyUrine cytologyConcordanceBiopsyAtypiaInternal medicineCancerPathologyBladder cancer

Abstract

fetched live from OpenAlex

BACKGROUND: At a high-volume center, it became necessary to provide benchmarks for the accuracy and risk of malignancy per urine cytology diagnostic category. The additive sensitivity for the determination of the residual risk of disease was calculated with the goal of determining the performance of cytology and optimal triage, including the number of urine samples, before the detection of malignancy in surveillance patients. METHODS: A 2-year laboratory information system-based search was conducted, and it yielded 587 subjects (695 biopsy and cytology pairs) with histological follow-up. The sensitivity and specificity of cytology for urothelial malignancy, the risk of malignancy per diagnostic category, the additive sensitivity, and the time for conversion from a negative initial cytology result to a positive cytology result were examined. RESULTS: The overall average sensitivity and specificity of cytology were 48.9% and 83.0%, respectively. The additive sensitivity increased with each subsequent cytology and peaked with the third cytology. A median conversion time of 22.2 months from a negative initial cytology result to a positive cytology result and a decline in predictive positive cytology after the fourth cytology were noted. Subcategorization of the atypical category failed to show statistical significance in predicting outcomes of biopsy. Surveillance subjects, as compared to primary subjects, showed a higher sensitivity for the detection of high and low grade cancers. CONCLUSIONS: The findings suggest that atypia favoring malignancy is being appropriately flagged. However, further definition of the atypical category is needed to increase specificity with a better qualitative or quantitative morphological algorithm. This study provides a risk of malignancy for each category for benchmarking and clinical triage. The data suggest that follow-up should include at least 4 consecutive urine specimens over a period of 22.2 months.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.292
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it