Imaging Radiation Doses and Associated Risks and Benefits in Subjects Participating in Breast Cancer Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Medical imaging is commonly required in breast cancer (BC) clinical trials to assess the efficacy and/or safety of study interventions. Despite the lack of definitive epidemiological data linking imaging radiation with cancer development in adults, concerns exist about the risks of imaging radiation-induced malignancies (IRIMs) in subjects exposed to repetitive imaging. We estimated the imaging radiation dose and IRIM risk in subjects participating in BC trials. MATERIALS AND METHODS: The imaging protocol requirements in 10 phase III trials in the adjuvant and advanced settings were assessed to estimate the effective radiation dose received by a typical and fully compliant subject in each trial. For each study, the excess lifetime attributable cancer risk (LAR) was calculated using the National Cancer Institute's Radiation Risk Assessment Tool, version 3.7.1. Dose and risk calculations were performed for both imaging intensive and nonintensive approaches to reflect the variability in imaging performed within the studies. RESULTS: The total effective imaging radiation dose was 0.4-262.2 mSv in adjuvant trials and 26-241.3 mSv in metastatic studies. The dose variability resulted from differing protocol requirements and imaging intensity approaches, with computed tomography, multigated acquisition scans, and bone scans as the major contributors. The mean LAR was 1.87-2,410/100,000 in adjuvant trials (IRIM: 0.0002%-2.41% of randomized subjects) and 6.9-67.3/100,000 in metastatic studies (IRIM: 0.007%-0.067% of subjects). CONCLUSION: IRIMs are infrequent events. In adjuvant trials, aligning the protocol requirements with the clinical guidelines' surveillance recommendations and substituting radiating procedures with equivalent nonradiating ones would reduce IRIM risk. No significant risk has been observed in metastatic trials, and potential concerns on IRIMs are not justified. IMPLICATIONS FOR PRACTICE: Medical imaging is key in breast cancer (BC) clinical trials. Most of these procedures expose patients to ionizing radiation, and the risk of second cancer development after imaging has prompted recent concerns and controversy. Using accepted calculation models, the number of malignancies were estimated that were potentially attributable to the imaging procedures performed during a patient's participation in BC clinical trials. The results show that for patients participating in metastatic trials, the risk of imaging radiation-induced malignancies is negligible. In adjuvant trials, some second cancers due to imaging could be expected, and measures can be taken to reduce their risk.
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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 | 0.007 | 0.005 |
| 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 | 0.000 |
| 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".