Prognostic value of Ki67 in phyllodes tumor of the breast: A systematic review and meta‑analysis
Bibliographic record
Abstract
Numerous clinicopathological features have been examined as predictive factors for adverse outcomes in patients with phyllodes tumor (PT) of the breast, but there are still no definitive predictive markers to guide management, despite the persistent risk of recurrence, even in benign disease. Whether Ki67 has prognostic value in PT remains uncertain. Therefore, a systematic review and meta‑analysis were performed to examine whether Ki67 is associated with adverse clinical outcomes, particularly recurrence, in patients with PT. The PubMed/MEDLINE, Web of Science, Scopus, Embase and Cochrane Library databases were searched from inception to July 2024. Study characteristics and outcomes (recurrence and overall survival) according to Ki67 status were extracted from each eligible study, and pooled log odds ratios (OR) with 95% CI were derived using a random‑effects model. A total of five studies comprising 280 cases were eligible for inclusion. The adverse outcome rate for the Ki67high (Ki67 >10 or >11.2%) population was 28.7% (95% CI, 20.1‑38.6%), while the adverse outcome rate for the Ki67low population was 9.4% (95% CI, 5.4‑13.5%). Ki67high was associated with an increased odds of an adverse outcome [log OR, 1.26 (95% CI, 0.38‑2.15; P=0.005)] compared with a Ki67low status. All five studies scored 8 points on the Newcastle‑Ottawa Scale, equivalent to ‘good’ quality according to Agency for Healthcare Research and Quality standards, and no significant publication bias was noted. This was the first meta‑analysis of the predictive value of Ki67 in PT of the breast. A relatively high Ki67 index (>10%) is associated with recurrence. It is timely to re‑evaluate the prognostic value of Ki67 in large retrospective cohorts with long follow‑up to firmly establish whether it could contribute to identifying patients at risk of recurrence, particularly those with histologically benign disease. Doing so could impact clinical practice by refining follow‑up recommendations based on quality evidence.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".