Assessment of Thin-Layer Breast Aspirates for Immunocytochemical Evaluation of HER2 Status
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.
Bibliographic record
Abstract
OBJECTIVE: To determine whether immunocytochemistry (ICC) for HER2 on ThinPrep (TP)-processed breast fine needle aspiration biopsies (Cytyc Corp., Boxborough, Massachusetts, U.S.A.) is comparable to the findings of immunohistochemistry on corresponding surgically removed tissue. STUDY DESIGN: Immunostaining was performed on 63 malignant breast fine needle aspirates and compared to immunostaining on paraffin sections (PSs) from the subsequent biopsies. The HercepTest (Dako, Carpinteria, California, U.S.A.) and TAB250 antibodies were utilized. Cases in which the TP and paraffin HER2 results did not correlate were further assessed for gene amplification by differential polymerase chain reaction (dPCR). RESULTS: HER2 overexpression was found in 9 of the 63 cases (14%). TAB250 had higher specificity on PS versus TP (P = .008), and TAB250 had higher specificity on PS versus the HercepTest on PS and TP (P = .004 and .0001, respectively). CONCLUSION: HER2 immunostaining with both the HercepTest and TAB250 on TP is unreliable due to low specificity (72% and 83% for HercepTest and TAB250, respectively). However, both antibodies have high sensitivity (89% and 100%, respectively); suggesting that this method may have some utility as a preliminary screening test for HER2 status. Negative HER2 staining by ICC is highly predictive of the absence of HER2 overexpression, whereas positive HER2 staining on TP would require further validation by either dPCR of fluorescence in situ hybridization.
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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 | 0.002 | 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) | 0.001 | 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 it