BI06 Global perspective on skin cancer in organ transplant recipients with skin of colour: a systematic review
Bibliographic record
Abstract
Abstract Organ transplant recipients (OTRs) are at an increased risk of developing skin cancer due to long-term immunosuppression. Much of the existing literature focuses on White OTRs, and data on skin cancer incidence, presentation and outcomes in OTRs with skin of colour are limited. This systematic review aims to evaluate the current global literature on the epidemiology of skin cancer in OTRs with skin of colour including clinical presentation, risk factors and outcomes. A comprehensive literature search was conducted using four databases: MEDLINE, Embase, Web of Science Core Collection and CINAHL. Screening, full-text review and data extraction were performed in duplicate; one independent reviewer resolved any conflicts. There were no restrictions on publication date or language. Abstracts without full-text articles were excluded. Demographic data were collected including ethnicity and/or skin type, and information related to the type of organ transplant, duration and type of immunosuppression, type and number of skin cancer(s), skin cancer treatment and outcomes. Quality assessment was performed using the Newcastle–Ottawa Scale. Following deduplication, 725 articles were screened for eligibility and 267 were included for full-text review; 81 articles were included for data extraction (66 observational studies and 15 case reports) – the case reports were eventually excluded. The majority of studies were conducted in the USA (28 of 66, 42%) or East Asia (14 of 66, 21%). Data from patients of Black, Hispanic and Asian ethnicities were most frequently reported in these studies; however, there was significant heterogeneity in the reporting of ethnicities across papers and limited correlation with skin type. Most data were from kidney transplant recipients, and cutaneous squamous cell carcinoma (SCC) and SCC in situ were the most commonly reported skin cancers. Comparative data relating to risk factors, treatment and outcomes across ethnicities were minimal. Although several observational studies have assessed the burden of skin cancer in OTRs with skin of colour, comparative data are limited, as is the global distribution of these studies. Pooled analyses and further longitudinal research are needed to better define the risk of specific skin cancers in OTRs of different ethnicities and skin types. Factors such as age, sex, transplant type, immunosuppression regimen and duration, as well as comorbidities like HIV, should also be considered. Moving forward, a more granular approach – such as differentiating risk by specific ethnicities and skin types rather than broad racial categories – is essential for individualized risk stratification and tailored preventative care in this diverse, and vulnerable, patient population.
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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 | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".