Abstract TC1-3-1: Ki 67 Ki67 – a clinically relevant biomarker or just <i>nice to have</i> information?
Bibliographic record
Abstract
Abstract Ki67 is an immunohistochemical marker indicating the growth fraction of cycling cells from G1 to S-phase in tumor specimens. In breast cancer, Ki67 is a prognostic marker with high values indicating poor outcome. Over the last decades, obstacles for its wide-spread use in clinical practice included lack of methodological standardization and lack of specific cut-off values for clinical decision making, i.e. discrimination of luminal A vs. B early breast cancer (EBC), chemotherapy indication in HR+/HER2- EBC. However, recently, the International Ki67 working group has put forward consensus statements for a standardized methodology. In general, reproducibility of Ki67 values at extreme sides of the spectrum such as 10% or ≥ 35% is much higher than in the intermediate range and quality assurance programs substantially improve laboratory performance. Moreover, clinical utility has also become apparent in two specific settings of HR±/HER2- EBC. First, the monarchE trial evaluating adjuvant abemaciclib in node-positive high-risk disease used a Ki67 cut-off of 20% as a criterion for aggressive disease and as a sole inclusion criterion for patients with 1-3 lymph nodes (cohort2). While data for this cohort have not yet been reported, Ki67 was a strong prognostic factor in the overall trial population with patients with high Ki67 having worse outcome than those with Ki67 &lt; 20%. Benefit from abemaciclib was independent of Ki67 index. Nevertheless, some health authorities included Ki67 in their abemaciclib label as the absolute benefit was greater in tumors with Ki67 ≥ 20%. Second, Ki67 response after a short (2-4 week) preoperative endocrine therapy allows endocrine response assessment by determining Ki67 in the surgical specimen. This information is widely used in drug development. Ki67post 10% has been defined as endocrine response. In the POETIC trial, endocrine response was associated with improved outcome compared to tumors with Ki67 ≥ 10% after 2-weeks of preoperative AI in postmenopausal patients. In the WSG ADAPT trial, patients with 0-3 lymph nodes, Recurrence Score 25 and endocrine response had excellent outcome with adjuvant endocrine therapy alone independent of menopausal status (5-year dDFS ≥ 95%). In postmenopausal women, probability of endocrine response with an AI is around 80% whereas in premenopausal patients with tamoxifen it is only around 40%. Yet, in premenopausal women addition of GnRH substantially improves endocrine response probability reaching about 80% with GnRH and AI as recently shown by interim analysis of the WSG ADAPTcycle trial (about 2500 patients). Endocrine response probabilities seen in the ADAPT trial (≥ 5000 patients) were validated in ADAPTcycle demonstrating clinical validity of this biomarker. In conclusion, Ki67 is a clinically relevant biomarker that can be used for clinical decision making, particularly in HR+/HER2- EBC. As there is no single generally accepted Ki67 cut-off value to discriminate prognostically favorable from aggressive EBC, Ki67 needs to be used in the context of tumor burden and tumor biology. Currently, next to its use in allocating patients to adjuvant abemaciclib in countries where Ki67 index is included in the label, it provides clinically important information after short-term preoperative endocrine therapy regarding endocrine response in HR+/HER2 EBC. Given its easy and inexpensive determination method, its analytical validity within quality assurance programs, and its clinical usefulness, Ki67 needs to be integrated in our biomarker portfolio in EBC. Citation Format: Nadia Harbeck, Torsten Nielson. Ki 67 Ki67 – a clinically relevant biomarker or just nice to have information? [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr TC1-3-1.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 0.004 |
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; both teacher heads 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".