Altered Recognition of Reparative Changes in ThinPrep Specimens in the College of American Pathologists Gynecologic Cytology Program
Bibliographic record
Abstract
Abstract Context. —Previous studies have shown that the diagnosis of reparative changes in conventional smears in the College of American Pathologists Interlaboratory Comparison Program in Gynecologic Cytology is one of the least reproducible diagnoses. Indeed, the diagnosis of reparative changes consistently yields the highest false-positive rate of any negative for intraepithelial lesions and malignancy (NILM) cytodiagnostic category. It is unknown whether cytologists recognize reparative changes in ThinPrep specimens as well, or less often, as in conventional smears. Objective. —To assess and compare the ability of cytologists to recognize reparative changes in conventional and ThinPrep preparations. Design. —We compiled performance data from the College of American Pathologists Interlaboratory Comparison Program in Gynecologic Cytology from the 2000–2003 program years. More than 400 slides with a reference diagnosis of reparative changes met our study criteria, representing a total of 11 200 individual responses for conventional cases and 1155 individual responses for ThinPrep specimens. We evaluated the results of both individual and laboratory participants using 2 performance criteria: the false-positive discordancy rate and the exact match error rate (any response that does not exactly match the reference diagnosis of 120 [reparative changes]). Results. —Cases with a reference diagnosis of reparative changes made up 1.2% of all ThinPrep slides and 3.7% of all conventional slides in circulation. The false-positive discordancy rate of individual responses on educational slides for conventional smears was significantly higher than the corresponding false-positive discordancy rate for ThinPrep specimens (15.7% for conventional vs 7.1% for ThinPrep specimens, P < .001). Laboratory responses on educational conventional smears and ThinPrep slides showed a similar trend (14.2% for conventional smears vs 2.4% for ThinPrep slides, P = .002). The exact match error rate on educational conventional slides was 41.4% for individual responses, while on educational ThinPrep slides, the overall error rate was 57.5% ( P < .001). For laboratory responses, the exact match error rate was 40.5% for educational conventional smears versus 58.9% for educational ThinPrep smears ( P < .001). Characteristic features of reparative changes were identified in ThinPrep specimens. Conclusions. —In the College of American Pathologists Interlaboratory Comparison Program in Gynecologic Cytology, ThinPrep slides with a reference diagnosis of reparative changes have a lower false-positive discordancy rate than conventional slides. Responses to ThinPrep cases with a reference diagnosis of reparative change show a higher exact match error rate than conventional smears. Since reparative changes in gynecologic cytology are recognized as indicating an increased risk of significant lesions, the clinical significance of these altered patterns of recognition of reparative changes in ThinPrep specimens warrants further investigation.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".