Association of HLA Antigen Mismatch With Risk of Developing Skin Cancer After Solid-Organ Transplant
Bibliographic record
Abstract
Importance: Risk factors for the development of skin cancer after solid-organ transplant can inform clinical care, but data on these risk factors are limited. Objective: To study the association between HLA antigen mismatch and skin cancer incidence after solid-organ transplant. Design, Setting, and Participants: This retrospective cohort study is a secondary analysis of the multicenter Transplant Skin Cancer Network study of 10 649 adults who underwent a primary solid-organ transplant between January 1, 2003, and December 31, 2003, or between January 1, 2008, and December 31, 2008. These participants were identified through the Scientific Registry of Transplant Recipients standard analysis files, which contain data collected mostly by the Organ Procurement and Transplantation Network. Participants were matched to skin cancer outcomes by medical record review. This study was conducted from August 1, 2016, to July 31, 2017. Main Outcomes and Measures: The primary outcome was time to diagnosis of posttransplant skin cancer, including squamous cell carcinoma, melanoma, and Merkel cell carcinoma. The HLA antigen mismatch was calculated based on the 2016 Organ Procurement and Transplantation Network guidelines. Risk of skin cancer was analyzed using a multivariate Cox proportional hazards regression model. Results: In total, 10 649 organ transplant recipients (6776 men [63.6%], with a mean [SD] age of 51 [12] years) contributed 59 923 years of follow-up. For each additional mismatched allele, a 7% to 8% reduction in skin cancer risk was found (adjusted hazard ratio [HR], 0.93; 95% CI, 0.87-0.99; P = .01). Subgroup analysis found the protective effect of HLA antigen mismatch to be statistically significant in lung (adjusted HR, 0.70; 95% CI, 0.56-0.87; P = .001) and heart (adjusted HR, 0.75; 95% CI, 0.60-0.93; P = .008) transplant recipients but not for recipients of liver, kidney, or pancreas. The degree of HLA-DR mismatch, but not HLA-A or HLA-B mismatch, was the most statistically significant for skin cancer risk (adjusted HR, 0.85; 95% CI, 0.74-0.97; P = .01). Conclusions and Relevance: The HLA antigen mismatch appears to be associated with reductions in the risk of skin cancer after solid-organ transplant among heart and lung transplant recipients; this finding suggests that HLA antigen mismatch activates the tumor surveillance mechanisms that protect against skin cancer in transplant recipients and that skin cancer risk may be higher in patients who received a well-matched organ.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".