Topical therapy for pain management in malignant fungating wounds: A scoping review
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To map and synthesise the existing literature on topical therapies for malignant fungating wounds pain management and the gaps involved. BACKGROUND: Most cancer patients with malignant fungating wounds suffer from wound-related pain, affecting their quality of life. Unfortunately, even though pain is a relevant symptom in cancer and palliative care, little is currently known about topical treatments' availability and impact on pain management. DESIGN: A scoping review following JBI® methodology METHODS: Searches were performed in CINAHL, LILACS, Embase, Web of Science, PubMed, Cochrane, NICE, Scopus, JBISRIR and grey literature, in English, Portuguese and Spanish, with no time limit. Two authors independently reviewed all citations and a third was called in case of divergence, and studies in adults with malignant fungal wounds reporting topical pain interventions were included. In addition, a data extraction tool for synthesis and thematic analysis was developed. This study followed the PRISMA-ScR Checklist. RESULTS: Seventy publications were selected from 796 records retrieved from databases. The studies mainly included non-systematic reviews and case studies with only six clinical trials. According to the narrative synthesis, twenty therapies were identified, including the use of wound dressings (58.6%), analgesic drugs (55.7%), topical antimicrobials (25.7%), skin barriers (15.7%), cryotherapy (5.7%) and negative pressure wound therapy (4.3%). Therapies were recommended to be applied to the wound bed or the periwound skin. In 68.5% of the studies, a standardised assessment for pain was not described. CONCLUSIONS: Topical therapies applied to malignant fungating wounds or periwound areas had been examined for pain management. However, their effectiveness was analysed in a few interventional studies, indicating the need for further primary studies to inform evidence-based practice. IMPLICATION FOR PRACTICE: Highlighted topical therapies for clinical practice consideration are opioids, anaesthetics and antimicrobials, with positive results described in randomised clinical trials. This study did not include patients.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.028 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".