Aesthetic Medicine Procedures in Cancer Survivors – A Literature Review
Bibliographic record
Abstract
Background: Advances in oncology have significantly increased long-term survival rates, creating a growing need to manage persistent physical and psychosocial consequences of treatment in cancer survivors, including scarring, alopecia, pigmentation changes, and tissue damage. Objective: To systematically review literature on aesthetic medicine procedures in cancer survivors, evaluating therapeutic potential, safety, and clinical implications. Methods: A systematic search was conducted in PubMed, Embase, and Cochrane Library (January 2000 – March 2025). Keywords included “cancer survivor,” “aesthetic medicine,” “botulinum toxin,” “fillers,” “platelet-rich plasma,” and “laser therapy.” Eligible studies included clinical trials, cohort studies, case series, and reviews reporting outcomes of aesthetic interventions in oncology patients. Two independent reviewers screened 356 records; 34 studies were included. Quality assessment used GRADE and Newcastle-Ottawa Scale. Results: Interventions included botulinum toxin (n=8), fillers (n=9), platelet-rich plasma (n=6), laser therapy (n=7), and scalp cooling (n=4). Procedures were generally safe, with mild and transient adverse events, and were associated with improvements in quality of life, self-image, and functional recovery. Conclusions: Aesthetic medicine procedures can be a valuable adjunct in survivorship care. Multidisciplinary collaboration and evidence-based protocols are recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".