Characterization of skin reactions and pain reported by patients receiving radiation therapy for cancer at different sites
Bibliographic record
Abstract
BACKGROUND: Skin reactions and pain are commonly reported side effects of radiation therapy (RT). OBJECTIVE: To characterize RT-induced symptoms according to treatment site subgroups and identify skin symptoms that correlate with pain. METHODS: A self-report survey-adapted from the MD Anderson Symptom Inventory and the McGill Pain Questionnaire--assessed RT-induced skin problems, pain, and specific skin symptoms. Wilcoxon Sign Ranked tests compared mean severity or pre- and post-RT pain and skin problems within each RT-site subgroup. Multiple linear regression (MLR) investigated associations between skin symptoms and pain. RESULTS: Survey respondents (N = 106) were 58% female and on average 64 years old. RT sites included lung, breast, lower abdomen, head/neck/brain, and upper abdomen. Only patients receiving breast RT reported significant increases in treatment site pain and skin problems (P < or = .007). Patients receiving head/neck/brain RT reported increased skin problems (P < .0009). MLR showed that post-RT skin tenderness and tightness were most strongly associated with post-RT pain (P = .066 and P = .122, respectively). LIMITATIONS: Small sample size, exploratory analyses, and nonvalidated measure. CONCLUSIONS: Only patients receiving breast RT reported significant increases in pain and skin problems at the RT site while patients receiving head/neck/brain RT had increased skin problems but not pain. These findings suggest that the severity of skin problems is not the only factor that contributes to pain and that interventions should be tailored to specifically target pain at the RT site, possibly by targeting tenderness and tightness. These findings should be confirmed in a larger sampling of RT patients.
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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 | 0.000 | 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".