Dermal Filler Use in Patients Undergoing Chemotherapy and Radiation Therapy
Bibliographic record
Abstract
Unlabelled: Dermal fillers have gained increasing popularity for their ability to enhance facial symmetry, restore volume, and improve skin texture. However, their use in patients with cancer undergoing active chemotherapy and radiation therapy poses unique challenges, as these treatments can alter both the safety profile and efficacy of filler procedures. Chemotherapy can interfere with normal wound healing and immune responses, warranting a more cautious and individualized approach when considering dermal fillers in this population. Although rare, dermal fillers have been associated with adverse outcomes in a limited number of diseases, including cellulitis, autoimmune/inflammatory syndrome induced by adjuvants, and a possible predisposition to malignancy. Other effects include localized inflammatory, systemic hypersensitivity, and delayed granulomatous formation, and these could be more severe in patients undergoing antineoplastic therapy. Furthermore, chemotherapy is often paired with adjuvant radiation therapy in cancer treatment, making it important to note the potential changes radiation can have on the skin. More research is needed to examine the direct interactions of chemotherapy and radiation on various filler materials injected within the skin, and how these can alter one's risk of adverse effects. The lack of research on this topic further emphasizes that clinicians should thoroughly educate patients receiving chemotherapy and adjuvant radiation treatment about the heightened potential risks associated with dermal filler injections and treatment regimens should be planned accordingly to minimize any adverse events.
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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 | 0.000 | 0.000 |
| 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".