Real-world data on adjuvant bisphosphonate use in a breast cancer center in Mexico.
Bibliographic record
Abstract
e12544 Background: Results from the Early Breast Cancer Trials Collaborative Group (EBCTCG) meta-analysis published in 2015 showed a significant reduction in risk of distant recurrence, bone recurrence and a 10-year breast cancer mortality reduction1. Moreover, Cancer Care Ontario and ASCO issued a guideline regarding the use of adjuvant bisphosphonates (AB) in breast cancer postmenopausal patients2. While these data are compelling, we have no information to support the implementation of this recommendation at Hospital San José’s Breast Cancer Center (HSJBCC). Methods: A retrospective analysis was performed to evaluate our compliance to the current recommendations for AB administration from 2015 through 2019. Inclusion criteria were based on the ASCO guidelines and comprised invasive breast cancer, postmenopausal status and early or locally advanced stage. Furthermore, in AB-treated patients we assessed the percentage of baseline calcium and creatinine measurement, prior dental evaluation, and concurrent calcium and vitamin-D supplementation during AB use. Results: A total of 106 patients met the inclusion criteria. Within the 4-year timeframe, AB was prescribed to 28/106 (26%) patients. Stratifying by year, we observed an increase of AB use rate from 4% in 2015 to 32% in 2019. Moreover, we observed a 93% baseline calcium and creatinine measurement, a 60% prior dental evaluation, and a 43% concurrent calcium and vitamin-D supplementation in the AB-treated population. Conclusions: HSJBCC recommendation for AB use is less than expected in the evaluated eligible patients in the 4-year timeframe. Despite an increase in our compliance to current ASCO guidelines it is not yet the standard of care at HSJBCC. Based on these results, we are currently planning a quality improvement initiative to undertake our low percentage of AB usage. [Table: see text]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".