Brain imaging screening (BIS) in metastatic breast cancer (MBC): patients’ and physicians’ perspectives
Bibliographic record
Abstract
Background: Routinely BIS in patients with MBC without neurological symptoms is not currently recommended, as no survival/quality-of-life improvements have been demonstrated. We investigated physicians and patients’ perspectives. Methods: Anonymous questionnaires for BC patients and BC-treating physicians were distributed online between 05/2023-02/2024. Data on demographics, treatments and physicians’/patients’ preferences were collected. Results: 545 patients from 14 European countries completed the questionnaire. Median age was 50 years and most had high education levels (73%). 86% had MBC, 51% hormone receptor-positive (HR+)/HER2-negative, 31% HER2-positive and 18% triple negative (TN) BC. 86% of patients, especially younger ones (p=0.02) and with HR- disease (p=0.03), were willing to undergo BIS for asymptomatic brain metastases (BM), despite the uncertain clinical benefit. 529 physicians from 50 countries (80% Europe) completed the questionnaire. Most were medical oncologists (71%) working in academic hospitals (53%). 52% of physicians sometimes/rarely request BIS, mainly when extracranial progression occurs and especially for HER2+ and TN MBC. Among physicians never recommending BIS (35%), 59% would do it if recommended by guidelines, 93% in case of clinical benefit and 32% if ≥ 30% likelihood of BM detection. Notably, 86% of patients would like to receive information on BM development while only 13% of physicians always address the issue. Conclusions: Our results highlight the need of dedicated clinical trials investigating the clinical value of BIS for asymptomatic MBC. They also underline the willingness of BC patients to know more about the possibility and implications of BM development. Publication History Article published online: 01 October 2024 © 2024. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.003 | 0.013 |
| 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 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".