Imaging for metastatic disease in patients with newly diagnosed breast cancer: are doctor's perceptions in keeping with the guidelines?
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: Despite multiple guidelines advocating against routine radiological evaluation for metastases in women with early stage breast cancer, imaging is still frequently overused. The objective of this study was to assess doctor's views on imaging guidelines, and an attempt to establish why personal and local clinical practice patterns regarding imaging may differ from current guidelines. METHODS: Canadian doctors who treat breast cancer were invited by email to complete an online survey developed by members of the research team. RESULTS: Responses were received from 173 physicians (26% response rate). Most (82%) indicated awareness of at least one published imaging guideline. Sixty per cent indicated that they had read the recommendations of the 2012 American Society of Clinical Oncology 'Top 5' list for choosing wisely in oncology imaging and, of those, 81% agreed with it. However, most indicated that this recommendation has not influenced them to order less imaging. Over 95% of doctors identified suspicious history, physical examination findings and inflammatory breast cancer as important factors for performing imaging. The majority did not feel that patient demand, fear of litigation or ease of access to imaging influenced their ordering for imaging. CONCLUSIONS: The majority of breast cancer doctors are aware of and generally agree that guidelines pertaining to staging imaging for early breast cancer are reflective of evidence. Despite this, adherence is variable and factors such as local practice patterns and disease biology may play a role. Alternative strategies, beyond simply publishing recommendations, are therefore required if there is to be a sustained change in doctor behaviour.
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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 | 0.006 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".