Monitoring the Response of Cyclin-Dependent Kinase 4/6 Inhibitors with Mean Corpuscular Volume
Bibliographic record
Abstract
Background: Currently, the combination of cyclin-dependent kinase 4/6 (CDK4/6) inhibitors and endocrine therapy is a first-line treatment for hormone-receptor-positive and HER2-negative metastatic breast cancer. This study aimed to assess the impact of changes in Mean Corpuscular Volume (MCV) on predicting responses to treatment and survival in patients with hormone-receptor-positive, HER2-negative metastatic breast cancer receiving CDK4/6 inhibitors and endocrine therapy. Methods: Retrospectively, data on hemoglobin levels, MCV, B12, folate levels, and survival times were collected from 275 patients. Patients were categorized into two groups based on the degree of MCV change (delta MCV ≤ 10 vs. >10). Kaplan–Meier survival analysis was performed, with significance set at p < 0.05. Results: The average age of the patients was 56.1 ± 12.1 years. In total, 72.7% received CDK4/6 inhibitors as first-line treatment, while 27.3% received them as second-line treatment. Before CDK4/6 inhibitor use, the median MCV level was 87.7 fL (IQR: 83–91), which increased to 98 fL (IQR: 92–103) after treatment (p < 0.001). ECOG performance score, CDK4/6 inhibitor treatment line, type of endocrine therapy, and MCV change were identified as independent predictors of progression-free survival in the Cox regression model. The median progression-free survival for the entire group was 28 months. Patients with MCV delta > 10 had a median progression-free survival of 33 months, compared to 23 months for those with MCV delta ≤ 10 (p = 0.029). There was no significant difference in median overall survival times between the two groups (p = 0.158). Conclusion: This study highlights that patients with MCV delta > 10 had longer median progression-free survival compared to those with MCV delta ≤ 10.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".