A dedicated structured data set for reporting of invasive carcinoma of the breast in the setting of neoadjuvant therapy: recommendations from the International Collaboration on Cancer Reporting (<scp>ICCR</scp>)
Bibliographic record
Abstract
AIMS: The International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter-)national pathology and cancer organisations, is an initiative aimed at providing a unified international approach to reporting cancer. ICCR recently published new data sets for the reporting of invasive breast carcinoma, surgically removed lymph nodes for breast tumours and ductal carcinoma in situ, variants of lobular carcinoma in situ and low-grade lesions. The data set in this paper addresses the neoadjuvant setting. The aim is to promote high-quality, standardised reporting of tumour response and residual disease after neoadjuvant treatment that can be used for subsequent management decisions for each patient. METHODS: The ICCR convened expert panels of breast pathologists with a representative surgeon and oncologist to critically review and discuss current evidence. Feedback from the international public consultation was critical in the development of this data set. RESULTS: The expert panel concluded that a dedicated data set was required for reporting of breast specimens post-neoadjuvant therapy with inclusion of data elements specific to the neoadjuvant setting as core or non-core elements. This data set proposes a practical approach for handling and reporting breast resection specimens following neoadjuvant therapy. The comments for each data element clarify terminology, discuss available evidence and highlight areas with limited evidence that need further study. This data set overlaps with, and should be used in conjunction with, the data sets for the reporting of invasive breast carcinoma and surgically removed lymph nodes from patients with breast tumours, as appropriate. Key issues specific to the neoadjuvant setting are included in this paper. The entire data set is freely available on the ICCR website. CONCLUSIONS: High-quality, standardised reporting of tumour response and residual disease after neoadjuvant treatment are critical for subsequent management decisions for each patient.
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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 | 0.430 | 0.459 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.018 | 0.015 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.016 | 0.012 |
| Research integrity | 0.010 | 0.018 |
| Insufficient payload (model declined to judge) | 0.005 | 0.007 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".