Abstract P2-10-09: The incidence of false negative of HER2/Neu status in primary breast cancer in the era of standardized testing: a Canadian prospective study.
Bibliographic record
Abstract
Abstract The efficacy of trastuzumab in the treatment of primary breast cancer has mandated accurate and timely testing of all patients with a new diagnosis of breast cancer. Testing is centralized in designated laboratories across Canada with adherence to guidelines and mandatory participation in quality assurance programs. The Canadian testing algorithm recommends starting with immunohistochemistry (IHC) followed by in situ hybridization (ISH) for equivocal cases. Early HER2 testing showed that approximately 25–30% of invasive breast cancer is HER2 positive. Recent data shows that the HER2/neu positive rate in breast cancer in Canada is 17.6%. Design: The study was designed to assess the rate of false-negative HER2 tests based on the IHC-first algorithm used in 8 pathology centres across Canada. Surgical excisions with invasive carcinoma were tested using the standardized local methodology for both IHC and ISH. The cases were scored by the local breast pathologist and in 2 of 8 centers image analysis was used in the evaluation of ISH. We compared consecutive HER2-negative IHC results (score 0/1+) to the corresponding ISH (either silver or fluorescence) result. False negative cases were defined as a negative IHC with an ISH ratio of≥ 2, since these patients are eligible for trastuzumab therapy. Results: 715 cases were analyzed by IHC using Ventana 4B5 (287), HercepTest (253), or SP3 (175), and by ISH kits: Vysis FISH (303), Ventana SISH (412). The HER2 and CEP17 counts were available in all cases. There were 4 cases with an ISH score ≥2 (4B5: 2/4, HercepTest 1/4, SP3 1/4). In 3 additional cases the absolute HER2 copy number was ≥6 but the HER2/CEP17 amplification ratio was <2 due to an increased number of CEP 17 signal (“polysomy 17”) or amplification of the pericentromeric region. The overall rate of false negative cases was 0.98% (7/715). These cases had a low level of amplification (ratio 2 to 2.45) or an absolute HER2 count of 6–8. Conclusion: Our observation confirms that IHC is an adequate test to predict negative HER2 status in primary breast cancer in surgical excision specimens, even when different antibodies and IHC platforms are used. The study supports and justifies the Canadian algorithm of IHC followed by ISH in equivocal cases in view of the extremely low percentage of false negative cases observed. This reflects the strict adherence to internal protocols and mandatory participation in quality assurance programs. These results provide further confirmation that the vast majority of patients eligible for trastuzumab are not deprived from an effective treatment by using this algorithm. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P2-10-09.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".