Abstract P4-11-09: Comparison of immunohistochemical residual risk panels to predict risk in early breast cancers treated with endocrine therapy
Bibliographic record
Abstract
Abstract Background: We compare two residual risk models combining immunohistochemical (IHC) biomarkers, IHC4 and Mammostrat, in the Edinburgh Breast Conservation Series (BCS) and in the Tamoxifen versus Exemestane Adjuvant Multinational (TEAM) trial. Materials and Methods: The primary cohorts comprised 831 and 2,513 estrogen receptor (ER)-positive patients who did not receive adjuvant chemotherapy from the Edinburgh BCS and TEAM cohorts respectively. We evaluated prognostic scores for distant recurrence-free survival (DRFS). Results: Low scores for both IHC4 and Mammostrat are associated with better DRFS. In multivariate Cox regression analyses the addition of both scores to clinical factors provided independent information on residual risk (p<0.05). In the larger TEAM cohort, IHC4 was the stronger predictor of DRFS but additional information was gained from including the Mammostrat score for all ER-positive patients (p<0.001). Conclusion: The results showed that the scores have different capabilities in predicting DRFS depending on the study and subgroup of patients. However, significant benefit in estimating residual recurrence risk after treatment was observed from a combined use of both marker panels. This provides support for investigating their combined use for risk stratification of ER-positive early breast cancer patients. Citation Format: Jacqueline Stephen, Gordon Murray, David Cameron, Jeremy Thomas, Ian Kunkler, Wilma Jack, Gill Kerr, Tammy Piper, Cassandra Brookes, Daniel Rea, Cornelis van de Velde, Annette Hasenburg, Christos Markopoulos, Luc Dirix, Caroline Seynaeve, John Bartlett. Comparison of immunohistochemical residual risk panels to predict risk in early breast cancers treated with endocrine therapy [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-11-09.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".