Looking Back: International Practice Patterns in Breast Radiation Oncology From a Case-Based Survey Across 54 Countries During the First Surge of the COVID-19 Pandemic
Bibliographic record
Abstract
PURPOSE The COVID-19 pandemic has profoundly affected cancer care worldwide, including radiation therapy (RT) for breast cancer (BC), because of risk-based resource allocation. We report the evolution of international breast RT practices during the beginning of the pandemic, focusing on differences in treatment recommendations between countries. MATERIALS AND METHODS Between July and November 2020, a 58-question survey was distributed to radiation oncologists (ROs) through international professional societies. Changes in RT decision making during the first surge of the pandemic were evaluated across six hypothetical scenarios, including the management of ductal carcinoma in situ (DCIS), early-stage, locally advanced, and metastatic BC. The significance of changes in responses before and during the pandemic was examined using chi-square and McNemar-Bowker tests. RESULTS One thousand one hundred three ROs from 54 countries completed the survey. Incomplete responses (254) were excluded from the analysis. Most respondents were from the United States (285), Japan (117), Italy (63), Canada (58), and Brazil (56). Twenty-one percent (230) of respondents reported treating at least one patient with BC who was COVID-19–positive. Approximately 60% of respondents reported no change in treatment recommendation during the pandemic, except for patients with metastatic disease, for which 57.7% (636/1,103; P < .0005) changed their palliative practice. Among respondents who noted a change in their recommendation during the first surge of the pandemic, omitting, delaying, and adopting short-course RT were the most frequent changes, with most transitioning to moderate hypofractionation for DCIS and early-stage BC. CONCLUSION Early in the COVID-19 pandemic, significant changes in global RT practice patterns for BC were introduced. The impact of published results from the FAST FORWARD trial supporting ultrahypofractionation likely confounded the interpretation of the pandemic's independent influence on RT delivery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".