Donor to recipient ratios in the surgical treatment of vitiligo and piebaldism: a systematic review
Bibliographic record
Abstract
Abstract Stabilized vitiligo resistant to conventional therapy (e.g. segmental vitiligo) and piebaldism lesions can be treated with autologous cellular grafting techniques, such as non‐cultured cell suspension transplantation (NCST) and cultured melanocyte transplantation (CMT). These methods are preferred when treating larger surface areas due to the small amount of donor skin needed. However, the donor to recipient expansion ratios and outcomes reported in studies with cellular grafting vary widely, and to date, no overview or guideline exists on the optimal ratio. The aim of our study was to obtain an overview of the various expansion ratios used in cellular grafting and to identify whether expansion ratios affect repigmentation and colour match. We performed a systematic literature search in MEDLINE and EMBASE to review clinical studies that reported the expansion ratio and repigmentation after cellular grafting. We included 31 eligible clinical studies with 1591 patients in total. Our study provides an overview of various expansion ratios used in cellular grafting for vitiligo and piebaldism, which varied from 1:1 up to 1:100. We found expansion ratios between 1:1 and 1:10 for studies investigating NCST and from 1:20 to 1:100 in studies evaluating CMT. Pooled analyses of studies with the same expansion ratio and repigmentation thresholds showed that when using the lowest (1:3) expansion ratio, the proportion of lesions achieving >50% or >75% repigmentation after NCST was significantly better than when using the highest (1:10) expansion ratio (χ2 P = 0.000 and χ2 P = 0.006, respectively). Less than half of our included studies stated the colour match between different expansion ratios, and results were variable. In conclusion, the results of our study indicate that higher expansion ratios lead to lower repigmentation percentages after NCST treatment. This should be taken into consideration while determining which expansion ratio to use for treating a patient.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".