Impact of routine cell block preparation on results of head and neck fine needle aspirates
Bibliographic record
Abstract
BACKGROUND: Fine needle aspiration (FNA) of head and neck masses is a common technique for providing cytology specimens to guide patient management. Cell blocks made from these specimens can be beneficial. Policy at our institution was changed from production of cell blocks only when requested by the pathologist to routine production for all non-parotid gland head and neck FNAs. The program was evaluated in terms of its impact on diagnosis and specimen turnaround time (TAT). METHODS: A retrospective study was carried out using electronic records at our institution. The Intervention group consisted of FNAs obtained in the 15-month period following implementation of routine cell block preparation (n = 391). The Control group consisted of the same specimens obtained in the 15 months prior to implementation (n = 403). The groups were compared with regards to diagnostic distribution into five categories-Unsatisfactory, Negative/Benign, Abnormal, Suggestive of Malignancy, and Malignant. Cytological-histological correlation and TAT were also compared. Chi square and t tests with P < 0.05 threshold were used. RESULTS: There was no difference in diagnostic distribution between the two groups (P = 0.59) and TAT was unchanged (P = 0.74). Cytological-histological correlation was borderline improved in the Intervention group, with fewer false negatives (33.0% Intervention, 44.3% Control, P = 0.050). The cost of the program was estimated at CAD$53.60/cell block, or CAD$16,771/year. CONCLUSION: Implementation of routine cell blocks for head and neck FNAs did not result in a difference in diagnostic distribution or improve case turnaround time despite incurring substantial cost. Correlation with final histology, however, was borderline improved, with fewer false negatives. Diagn. Cytopathol. 2016;44:880-887. © 2016 Wiley Periodicals, Inc.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".