Can high Ki67 predict distant recurrence in early-stage breast cancer with low Oncotype Dx score?
Bibliographic record
Abstract
e12561 Background: Ki-67 is a marker of proliferating cells. The recurrence score based on the 21-gene breast cancer assay also called Oncotype Dx provides prognostic and predictive information for recurrence in early stage breast cancer patients. We previously showed that there is a moderate correlation between Ki67 and oncotype Dx recurrence score. In this retrospective study, we aimed to examine whether high Ki67 could predict the distant recurrence in early stage breast cancer with low oncotype Dx scores ( < 25). Methods: This retrospective study included 278 consecutive cases of hormone receptor-positive, HER2 negative (T1-2 N0 M0) breast cancer who were diagnosed between 2008 and 2015 with low oncotype Dx ( < 25). Patients’ clinical outcome in terms of distant recurrence after breast surgery was determined up to December 2020 (median follow-up of 7 years). Patients were divided in to low risk (Ki67 < 15%) and high risk (Ki67 > = 15%) groups. Results: Of 278 cases with average and median age of 59 and 60 respectively, 148 (53%) were in Ki67 low risk and 130 (47%) were in Ki67 high risk group. Average and median oncotype Dx were 13.86 and 15 respectively in Ki67 low risk versus 15.23 and 16 respectively in Ki67 high risk group. 13 patients (4%) experienced distant metastasis in lung, liver, bone and skin. Of these 13 cases with average and median oncotype Dx 15.84 and 19 respectively, 12 (92%) were in the Ki67 high risk group and only 1 (8%) belonged to the low risk category. High Ki67 patients were overrepresented in group with recurrent distant metastasis compare to group without recurrent disease (Pearson Chi-Square = 51.18 with 1 degree of freedom and P = < 0.001). Conclusions: Ki67 high patients in the low risk oncotype Dx group are relapsing at a significantly higher rate suggesting that Ki67 combined with low oncotype Dx further refines the risk of distant relapse.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".