Updated UK Recommendations for HER2 assessment in breast cancer
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
Human epidermal growth factor receptor 2 (HER2) overexpression is present in approximately 15% of early invasive breast cancers, and is an important predictive and prognostic marker. The substantial benefits achieved with anti-HER2 targeted therapies in patients with HER2-positive breast cancer have emphasised the need for accurate assessment of HER2 status. Current data indicate that HER2 test accuracy improved following previous publication of guidelines and the implementation of an external quality assessment scheme with a decline in false-positive and false-negative rates. This paper provides an update of the guidelines for HER2 testing in the UK. The aim is to further improve the analytical validity and clinical utility of HER2 testing by providing guidelines of test performance parameters, and recommendations on the postanalytical interpretation of test results. HER2 status should be determined in all newly diagnosed and recurrent breast cancers. Testing involves immunohistochemistry with >10% complete strong membrane staining defining a positive status. In situ hybridisation, either fluorescent or bright field chromogenic, is used either upfront or in immunohistochemistry borderline cases to detect the presence of HER2 gene amplification. Situations where repeat HER2 testing is advised are outlined and the impact of genetic heterogeneity is discussed. Strict quality control and external quality assurance of validated assays are essential. Testing laboratories should perform ongoing competency assessment and proficiency tests and ensure the reliability and accuracy of the assay. Pathologists, oncologists and surgeons involved in test interpretation and clinical use should adhere to published guidelines and maintain accurate performance and consistent interpretation of test results.
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 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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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