Patient perceptions and expectations regarding imaging for metastatic disease in early stage breast cancer
Bibliographic record
Abstract
PURPOSE: The probability of detecting radiologically evident metastatic disease in asymptomatic women with newly diagnosed operable breast cancer is low. Despite the recommendations of most practice guidelines imaging is still frequently performed. Relatively little is known about what patients believe is important when it comes to radiologic staging. METHODS: Patients with early stage breast cancer who had completed their definitive breast surgery were surveyed about their personal experiences, perceptions, and expectations on the issue of perioperative imaging for distant metastatic disease. RESULTS: Over a 3 month period, 245 women with primary operable breast cancer completed the questionnaire (87.0% response rate) and 80.8% indicated having had at least one imaging test for distant metastatic disease. These were either of the thorax (72.2%), abdomen (55.9%) or skeleton (65.3%) with a total of 701 imaging tests (average of 3.5 tests per patient imaged) performed. Overall, 57.1% indicated that they would want imaging done if the chance of detecting metastases was ≤10%. Although 80.0% of patients indicated that, "doing whatever their doctor recommended" was important to them, 70.4% also noted that they would be uncomfortable if their physician did not order imaging, even if this was in keeping with practice guidelines. CONCLUSIONS: Most patients with early stage breast cancer recall having imaging tests for distant metastases. Given the choice, most would prefer having imaging performed, even if this is not in line with current guidelines. If patient expectations are, in part, driving excessive imaging, new strategies addressing this are required.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".