Outcomes of skin cancers in pediatric solid organ transplant patients: A systematic review
Bibliographic record
Abstract
BACKGROUND: The most frequently reported malignancies after solid organ transplant are cutaneous, but data on the risk in pediatric populations varies across studies. OBJECTIVES: To perform a systematic review including reported features and outcomes of skin cancers in pediatric solid organ transplant recipients. METHODS: EMBASE and MEDLINE were systematically searched (Prospero CRD42020201659). RESULTS: The review summarizes data from 20 studies on 337 patients, with a median age ranging from 15.0 to 19.5 years as reported in 4 studies, who developed skin malignancies after pediatric solid organ transplantation. Median ages at transplant and skin cancer diagnosis ranged from 1.5 to 17.0 years and 15.3 to 33.5 years, respectively. Squamous cell carcinoma (SCC) was most commonly reported (218 cases), followed by basal cell carcinoma (BCC) (91 cases), melanoma (18 cases), and unspecified keratinocyte carcinomas (2 cases). The median latency period between transplantation and cancer diagnosis ranged from 2.2 to 21.0 years. Overall, 4 studies reported 17 cases of metastasis in total, and recurrence was reported in one case. Six deaths were reported in one study related to SCC and melanoma metastases. The incidence rate of skin cancer after pediatric transplantation per 100 person-years of follow-up was 2.1 based on 5 studies. CONCLUSION: The most frequent post-transplant malignancy in pediatric organ transplant recipients was SCC.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".