Relationship between Medication-Related Osteonecrosis of the Jaw and CDK4/6 Inhibitors in Breast Cancer
Bibliographic record
Abstract
Objective: We aimed to evaluate the use of CDK4/6 inhibitors as a risk factor for medication-related osteonecrosis of the jaw (MRONJ) in a cohort of patients with metastatic breast cancer treated with denosumab. Methods: This was a multicentre, retrospective, observational study. All patients with breast cancer treated with denosumab (January 2011–December 2022) were included. The relationship between CDK4/6 inhibitors and MRONJ was analysed. Results: A total of 243 patients were included, ninety-five (44.2%) of whom used a CDK4/6 inhibitor. There were 21 patients with MRONJ. In patients treated with denosumab without CDK4/6 inhibitors, the incidence of MRONJ and mean time to the occurrence of MRONJ were 6.6% (8/120) and 16.8 months (SD 7.8), respectively; in patients treated with denosumab and CDK4/6 inhibitor, these values were 13.7% (13/95) and 15.4 months (SD 8.7), respectively. The difference in the incidence was not significant (p = 0.085). Among the 19 patients who used abemaciclib, the probability of MRONJ occurrence was significantly higher compared to patients not using CDK4/6 inhibitors (p = 0.0178). Conclusions: These results suggest that the incidence of MRONJ in patients with metastatic breast cancer treated with denosumab is higher, and the onset of MRONJ occurs earlier in the presence of CDK4/6 inhibitors. The differences were statistically significant in the patients who used abemaciclib. Given that the use of this combination is very common in routine clinical practice, it would be advisable to carry out larger prospective studies to clarify the risk of this association.
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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 | 0.001 | 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".