Pilot evaluation of Mepitel Film and StrataXRT for the prophylaxis of radiation dermatitis in Chinese breast cancer patients undergoing adjuvant radiotherapy in Hong Kong
Bibliographic record
Abstract
Objective: Radiation dermatitis (RD) can significantly impact the quality of life in breast cancer (BC) patients undergoing radiation therapy (RT). Barrier products, such as Mepitel Film (MF) and StrataXRT, were reported in the literature to be effective in preventing RD but their efficacy and tolerance in Chinese patients have not been studied. This is a feasibility study of preventing RD in Chinese BC patients with MF and StrataXRT. Methods: Chinese BC patients from Union Oncology Centre (UOC) who started the use of MF and StrataXRT as RD prophylaxis from August 2023 to December 2023 were retrospectively reviewed. The incidence and severity of RD during treatment, two weeks and 3 months after RT were collected. Patients were assessed by an oncologist or a trained radiation therapist with the Common Terminology Criteria for Adverse Events (CTCAE) and Radiation-Induced Skin Reaction Assessment Scale (RISRAS) (researcher part). Patients completed the Skin Symptom Assessment (SSA) and RISRAS (patient part). Patients' compliance and side effects were assessed. This study was approved by the Union Hospital Research Ethics Committee (EC033). Results: Twenty patients fulfilled the inclusion criteria, but 3 did not apply the products during the entire course of RT because of skin reactions to the products (1 MF, 2 StrataXRT), leaving 17 evaluable patients. None reported discomfort from product use, and all had good compliance. No grade 3 RD were observed in all evaluable patients. The 2 cohorts appeared to be largely similar in all assessment parameters. The costs of MF (including costs for nursing care) were approximately three folds compared to StrataXRT. Conclusions: MF and StrataXRT were well tolerated and safe in Chinese BC patients. Larger randomized studies are needed to understand which patients could benefit more from these products.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".