Use of adjuvant bisphosphonate therapy in breast cancer by Indian oncologists: An implementation science study.
Bibliographic record
Abstract
e13667 Background: Several clinical trials, expert consensus and guidelines have recommended the use of bisphosphonates (BP) in reducing the breast cancer recurrence risk in postmenopausal women. The 2019 St. Gallen Panel voted 83.7% in favour of the routine use of bisphosphonates in postmenopausal women. Similarly, the 2022 ASCO-Ontario Health guidelines for breast cancer supports the recommendation. However, the uptake of these recommendations in routine clinical practice is poorly studied. We aimed to investigate the use of adjuvant BP therapy by Indian oncologists (implementation science study). Methods: A cross sectional survey study design was used to investigate our research question. Physicians in India who treat patients with breast cancer were presented with a clinical vignette of a young woman with postmenopausal (induced) non-metastatic high risk hormone receptor-positive breast cancer. A snowball sampling strategy was employed to avoid sampling bias. Participants were requested to state their gender, primary qualification, practice setting, number of years of practice as an oncologist and proportion of patients with breast cancer in their practice. Instead of providing the option of BP therapy, we asked an open-ended question whether they would recommend any additional therapy other than surgery, radiation, chemotherapy and anti-estrogen therapy. We asked them to write in the name or class of drug if they would prescribe an additional therapy to the patient. Results: The survey was completed by 74 Oncologists. The response rate is unknown as a snowball sampling strategy was employed. Majority of the respondents were male (74%), were non-teaching private practitioners (42%), medical oncologists (62%) with up to 10 years of experience (65%), and breast cancer patients make up to 50% of their patients (84%). Most of the oncologists responded no to our question on additional therapy (76%). Of those who responded yes, only 8 suggested BP therapy (11%). Conclusions: Despite strong evidence and guidelines, adjuvant BP therapy in high-risk early breast cancer was only recommended by very few oncologists in our survey study. Steps to bridge this gap between academic research and clinical application is urgently warranted. Implementation of clinical guidelines has to be monitored routinely which may be facilitated by provider and patient surveys. This can also assist in identifying and addressing the concerns with newer recommendations.
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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 | 0.019 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".