Prospective evaluation of patient-reported anxiety and experiences with adaptive radiation therapy on an MR-linac
Bibliographic record
Abstract
Purpose: An integrated magnetic resonance scanner and linear accelerator (MR-linac) was implemented with daily online adaptive radiation therapy (ART). This study evaluated patient-reported experiences with their overall hospital care as well as treatment in the MR-linac environment. Methods: Patients pre-screened for MR eligibility and claustrophobia were referred to simulation on a 1.5 T MR-linac. Patient-reported experience measures were captured using two validated surveys. The 15-item MR-anxiety questionnaire (MR-AQ) was administered immediately after the first treatment to rate MR-related anxiety and relaxation. The 40-item satisfaction with cancer care questionnaire rating doctors, radiation therapists, the services and care organization and their outpatient experience was administered immediately after the last treatment using five-point Likert responses. Results were analyzed using descriptive statistics. Results: 205 patients were included in this analysis. Multiple sites were treated across the pelvis and abdomen with a median treatment time per fraction of 46 and 66 min respectively. Patients rated MR-related anxiety as "not at all" (87%), "somewhat" (11%), "moderately" (1%) and "very much so" (1%). Positive satisfaction responses ranged from 78 to 100% (median 93%) across all items. All radiation therapist-specific items were rated positively as 96-100%. The five lowest rated items (range 78-85%) were related to general provision of information, coordination, and communication. Overall hospital care was rated positively at 99%. Conclusion: In this large, single-institution prospective cohort, all patients had low MR-related anxiety and completed treatment as planned despite lengthy ART treatments with the MR-linac. Patients overall were highly satisfied with their cancer care involving ART using an MR-linac.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".